S&P Global Stock

Okay. All right. Good morning still, I guess, everybody. Thank you for being here. My name is Manav Patnaik. I cover business and information services for Barclays.

We're very pleased to have with us today from S&P, Eric Aboaf, who's the CFO. Thank you for being here, Eric.

Eric, maybe just a place to start would be you've been now, I think, at the company about 1.5 years almost. So just talk about what you've kind of -- what's kind of surprised you, both positive or negative in the 1.5 years? And perhaps what have you brought to the table differently?

Yes. I think I spent, as you know, 20 years in banking in your corner of the world. And it's been really exciting to come to S&P. I've worked at -- worked with S&P as a partner, a supplier, a vendor, whether it's around ratings, benchmarks for asset management, market data. Energy data is probably the one area that I spent less time on before coming.

And what I found is much as I had expected, just a set of growth businesses focused on transparency, clarity, scenarios and what can make financial institution, corporations and energy companies even more successful. And that's where I spend my time is where do we grow, where can we accelerate, what's next. There's a great innovation engine, which I think is a little different than what you see in banks because banks have to be constrained by definition, and innovation is at the heart of what we do.

And the areas that I focus the most is around creating really transparency in MIS into our commercial activities, some of how we think about pipeline, some of how we think about sales, some of how we think about segments and targeting different segments, how we think about product offerings in one area that supports a different group of clients. Because as we become larger and larger, there's so much to bring to our clients. We have to do over time is measure and operate at scale and that requires a set of insights so that -- and over time, you can launch campaigns, you can roll out products more quickly, you can drive more productivity over time, so that then we can deliver the margin expectations that our shareholders have that we have for ourselves while we reinvest in the business.

Got it. And like yourselves, there's been a lot of new management across the company as well. So maybe just some insights into how that shapes up today and looking forward?

I think Martina and the team have brought a lot to the company over the last 2 years, really thinking about in the -- we've had a great run 5, 10 years and really thinking about how do we drive the next round of growth, the creation of the Chief Commercial Officer organization where we cover 130 clients, which are the top 1/3 of our revenue base, is really a sea change for how we operate. And what we found is it's brought our product lines together at a level of sophistication and seniority where now we're having discussions in the boardroom with CEOs about the wide range of what they're facing out in the marketplace.

You think about all the hyperscaler issuances, for example, you've got CEOs of enormous banks like yours, thinking about what does that mean for underwriting hyperscaler issuance. We've got our ratings understanding and insights there. Some of that's in the public domain, some of that's in the private domain. What kind of market data do I need to really understand that, how do energy supply chains and electricity grids and so forth in different parts of the world play out, how do I want to underwrite electricity prices, which are inherent portions of data centers, which support those hyperscalers and those AI companies.

So there's a wide range of activities that I think Martina has really thought about how do we bring together to our clients that they can really value. And that's really an opportunity, one that we think is unique to us because without the fortitude and the depth in each of those areas, right, we wouldn't be in the C-suite, right? We'd be working with the CEOs of divisions or COOs of various divisions, but that client connectivity really is an opportunity. And what we find is that the stature, the sophistication, the trust that they have in S&P Global is just second to none.

Got it. Okay. Let's move on to, I guess, touch on the segments of the business. So maybe the first question to get it out of the way. I mean there was some market rumors about you potentially considering the Cap IQ business up for review. So just your comments on that.

Well, there's always been speculation just about every industry I've been in, probably you've been in. And as a matter of principle, we're just not going to comment on unwarranted rumors, just isn't -- it's not helpful. I would say that right now, as we said, as late as our second quarter earnings, we're highly focused on growth in MI, right? We've had a very strong, I'd say, solid start to the year. Growth is up north of 6%, comfortably within our guidance of 5.5% to 7% for the year. And we feel comfortable in delivering on that.

And I think importantly, we've also said, look, we'll selectively trim elements of that portfolio, but we talked about small, subscale product lines, which is the kind of thing we've done before. We've done it recently in the Energy business, right, where we thought -- that kind of software layer wasn't as valuable because in truth, we're really a data company and what we're really doing is trying to find share benchmarks and data to our business and our clients.

And some of those underperforming areas that you'd called out, any examples or which broader categories that would fall in? Or is it just on the software side, given the analogy to energy?

It's actually not analogous to Energy because the Market Intelligence data's business is really quite strong. As I said, growth of north of 6% top line first half of the year and comfortably within our guide. Continued growth in platforms, including some big announcements we made in the second quarter around clients. Enterprise Solutions, which is not just software, it's really a system of record software solutions with a data component. That grew 10% year-over-year in the first 2 quarters of the year. So we're seeing real momentum there. That's important.

In the data space, we're growing at high single digits, low double digits, depending on which quarter we're looking at. We're signing up more clients for MCP connectors. We're up to 500, which is 50% more than the prior quarter. And data usage rates through API and LLM call volume is up 5x, 5x Q1 to Q2, and it was 5x 4Q to 1Q, right? So think about the economic value that we're bringing to clients.

And then just recently, we've continued the integration of S&P data into the ChatGPT financial services workflows. And just last week, OpenAI released a study of those workflows and shared how error rates with a trusted, proprietary, branded S&P Global data are below 3%. Our nearest competitor was at just around 6.5% errors, right? And it's something that clients have been telling us over the year, which is that our data is particularly valuable. They trust in it because of its quality. They can ingest it and process it in ways that are, in many cases, better than our peers and brings immediate value. And so I think there's a lot of -- a lot to come over the coming quarters and years as we see AI develop interfaces for clients, develop either within their own organizations through new channels that they're ingesting data for. But that's going to be the heart of growth of the...

Okay. Yes. Just a few follow-ups on that. But before we get into that, you used the Mobility spin-off to resegment some of the numbers. So within MI, can you just remind us again what the new segmentation is? And kind of why did you bucket those in such a way?

MI is segmented in a pretty straightforward way. We've got the Kensho Data & Platform product line, which is about 2/3 of MI, 1/3 of it is the Enterprise Solutions, which is that workflow software. And we did it that way because in Kensho Data & Platforms, what we have is some unique platforms that have been deeply embedded in client workflows. So think about the client franchise that we have there is exceedingly deep and broad at the same time.

And Kensho over the years has brought a set of data and MCP connectivity and so forth to that client base. And what we want to do is accelerate that, right, because we're happy for clients to connect to us through our proprietary platform, but also every other platform that exists out there. And we want to be on the forefront of any evolution that's playing out while we modernize and improve and so forth our own platforms.

And then there's Enterprise Solutions, which is great. And it's not just a software business, right? It's a system of record software business, which is critical to workflows for loan syndications, loan trading, private markets activity with iLEVEL, as an example, and creates an area, right, for clients not only to operate their businesses, but to record their data, ingest our data and unique data that we pool across clients and creates real value and real growth for us.

Got it. In terms of the -- so the segmentation, I think, makes sense. But help us -- I think you have different leaders for each segment, like I think you had Bhavesh running Kensho Data and et cetera. So why separate leadership? Or is it just -- are they still talking to each other a lot, I suppose?

Well, they're definitely talking avidly. What we have is we have integrated multiproduct sales force, right, that has to -- that is really from a go-to-market standpoint, holistic in how it approaches financials, corporates, even Energy clients within MI. But the product set has some uniqueness. And so you want to create innovation and feature functionality and even new products within that product set. And that's why you've got that lineup. And we, from an internal standpoint, look at our business from a client lens, client segments, right, the CCO clients and then all the other groupings of clients of midsize and small clients. We look at a product lens and we look at a regional lens, right? And there are a couple of others, but let me just stick to those 3. And that lets us find opportunities. It lets us spot execution successes in areas of further opportunity and a good way for us to run the business.

Got it. Moving on to the AI aspect of things. You talked about 500 MCP connectors now, the OpenAI project, et cetera, impressive numbers, good growth. Can you just help us appreciate the monetization model? Like how is that going to convert into revenues? And what are the kind of the pluses and minuses of that?

For us, AI is an accelerant, right? Monetization will come over time. And what we want to do is be there for our clients as they're expanding and experimenting. We talked about how some of the client discussions are even taking a little longer. Why? Because we're talking with them about not only our value-based pricing, but also experimenting with some volumetric pricing, right? And clients, on the other hand, are thinking themselves, wow, I need even more of this data from S&P Global. I trust it. It's branded. It's reliable. It's got a curation that is unique. And they want to make sure that they can get as much of that as possible for a reasonable price as well.

And so there's just -- I think there's a development of an economic model or maybe a -- I'll say, we have an economic model around value pricing, which is around what clients use and how much they use and how many people use and what products they're engaged in, that's pretty sophisticated. And I think over time, that will evolve probably a little more towards usage, but that transition will come over time because clients first need to actually experiment and experience it. And you've read about how folks are monitoring token usage and so forth. That's within their own environment.

Typically, we provide the product, the data sets behind that for clients. And as clients work through that evolution, they want us to be fair with them and that will come with time. I think for now, we're extremely willing to encourage, right, and help them take full advantage with our data so long as they do it on our terms, right? Our terms are -- our data is proprietary. It's behind our paywall. It's not to be used for training, right? It's quite unique in ways and we'll maintain that. And at the same time, evolve the economic model as it makes sense.

Got it. One of the concerns, I think with the whole MCP and the AI connections is that customers might use it a la carte or whatever you want to call it for MCP, and that will come at the expense of your platform that they might have subscribed to. Are you seeing some of that trend? Or is that something the MCP pricing might take offset? Just curious your thoughts on the pluses and minuses there.

I'm smiling because we're not seeing an either/or, right? We're actually seeing folks continuing to re-up on some of our proprietary platforms and ask for even more data. Now the data business is growing much more quickly, right, which we're thrilled to have. And in truth, we're agnostic, right? We'd love to grow the data business, not just high single digits, but mid-double-digit teens. We'd like to accelerate it through the breadth of channels. Over time, that's our expectation of what's likely to happen.

And if that means that some of the platform revenue is replaced with data revenue, that's great. If the platform revenue continues to grow, which is what it's doing today and we get data revenue on top of that, that's great as well. So there's a variety of different scenarios that we're looking towards. But in every one of those, there's an economic foundation of where we are today. There's a trusted brand of where we are today. There's control of our data, right, including audit rights and protections that we're going to ensure we have, while we continue to serve our clients and see them grow with us.

Got it. You mentioned token costs. I think one of the things investors are trying to figure out also is who's controlling token costs and how. So maybe a 2-parter, like, specific to MI and then even just broadly stepping back for all of S&P, just some thoughts on what the token costs look like and how you control that.

Yes. Let's maybe take it from the sort of client side, and then we'll talk a little bit about internally. Clients of S&P, whether they're MI clients or Energy clients or what have you, are -- especially the largest clients are building their own environments for large language models within their ecosystems, right, with harnesses and layers and so on and so forth. And they're trading off one model for another and optimizing an open source and so on and so forth.

And what they're doing is we're connecting to them through our energy data sets or financial data sets or corporate data sets, right, and making sure they can access our data in a highly efficient manner and scaled manner. As they do that, right, it's quite natural for them, right, to incur the token cost because it's within their environment. For us, it's just -- we're just fulfilling data. And so primarily, it's a client question. We want to make sure that our data gets them in a highly efficient way, in a highly effective way, so that they're not maxing out, right, of their own cost. And so that's the primary area where it comes to the fore.

The other client area that is -- has some importance is we're building AI functionality within our products and our energy ecosystem, our MI ecosystem. Some of our ratings data is deployed through that. Configuring indices in our Index business can be done by clients and the AI drivers and feature functionality of those products, those tend to be on us, but they're much more -- they're small scale in relation to just enormous amount of data pulling.

And then finally, we're using AI internally on productivity opportunities, whether it's data operations, software development speed, whether it's research, right, that we provide. And there, you'd expect the CFO to do what he or she should be doing, which is just monitoring token costs and seeing who's using it and how much and then asking why. And if why has a good answer, great, let's do more of that because there are paybacks. And if why doesn't have such a hot answer, let's go and look again.

Got it. I'm sure the other thing you're focusing a lot on is all these productivity initiatives are probably creating a margin opportunity. You guys already have pretty healthy margins. But how should we think about if we'll see some of that in the numbers? Or you put that all back into reinvestment? Just some thoughts there.

I think you'll see both. I think we're -- you'll see continued margin expansion and reinvestment into our products, feature functionality, geographic growth and so forth. I think what we're finding with AI is it's just another in the long list of tools, right, that we can put to use. In data operations, where we now see our way to a 20% reduction in costs across $0.5 billion area. And now the discussion is with even the more advanced AI and AI quantitative models, can we go after the next 5%, 10%, 15%, 20% in data operations, right? That's a discussion we're having right now as part of our budget cycle for '27, '28 and '29 as an example.

How exactly we'll get there? We'll figure out over time. But our view is that, for a company of our scale, productivity matters, reinvestment matters and we have continued confidence we can continue to deliver at the margin expansion of the 50 to 75 basis points across the company, and we've even said even higher in certain divisions.

Got it. And just on that comment, maybe just help reiterate kind of the divisional qualitative guidance you gave at Investor Day in terms of margins? Like where are the bigger opportunities?

Yes. We said -- let me take it from 2 directions, right? We said that margin expansion will typically be 50 to 75 basis points for our divisions over time on average and so forth, right? They'll partly depend on the -- where we are in the revenue cycles, but we see that with confidence. We also said that MI, just because it's a higher proportion of the expense base, right, will have -- will be typically at the upper end of that. And to be honest, if you look at the first half results, we had, what, 75 basis points or more growth in margins in Energy and Index.

We had more than 100 basis points of growth in margin in MI, and we had more than 200 basis points so far growth in margin in Ratings. Now half a year to make a year, but it just gives you a sense for the -- our ability to drive not only top line, but also margin expansion, including in areas where we're seeing both acceleration of cycles as well as some other scenarios. So it's been a good year, and we'll continue to do that.

Got it. Before we move on to some of the other segments, you mentioned, obviously, all the leaders within MI are talking a lot to each other. But how is the communication between the leadership of your 4 different segments? Like how closely integrated are those conversations?

It's become increasingly vivid and intense. And I'll -- maybe I'll do it from a couple of vantage points. For example, in our Energy division, we have our supply chain assets and products that we've begun to knit together in a much more holistic offering. Well, that can go to our Energy clients, to our Corporate clients, to our financial clients who are looking at the downstream implications of supply chains on the assets they've been underwriting.

And so it's that kind of connectivity that the Chief Commercial Office has brought together. And so look, we have a client need out there, where do we have products and it doesn't matter which division is. We have other areas that are just coming together because, as I mentioned, some of the largest banks are deeply interested in ratings of that -- of the debt and companies that they're supporting. They're deeply interested in how those ratings compare to benchmarks, right, relative to others, and we've been building partnerships and expanding our own data sets there.

And they're deeply interested in kind of supply chain commodity dependency, including around trade for those underwriting. So the -- I think the depth that we're seeing is -- has really been multiplied by the focus on some of our largest clients and all their needs.

Got it. Okay, let's move to the Ratings business next. So I suppose first question is just around the -- can you remind us of what your issuance guidance that was -- or is for the second half of the year? I think from your data, we saw July was up 8% based on the number you disclosed at least. So just how that flows into kind of the guide for the year?

Yes. The guide for the year is in the -- started off in the low single digits for billed issuance. Now it's the mid- to high single digits. We'll see exactly how it plays out. Remember, last year was a -- had some patterning to it. The first quarter was strong. Second quarter, a lot of concerns post some of the trade discussions, so very low issuances. And then some of that got delayed into third and fourth quarter.

This year, I think, is a little more consistent across the quarters in dollar terms. But as a result, we've had a strong -- a good first quarter, a very strong year-on-year compare in the second quarter. And then because of the very strong third and fourth quarter last year, while we'll have, I think, a very good third and fourth quarter, obviously, market dependent, the year-on-year compare will actually flip just because of the size of the upticks last year.

Got it. And I think one of the things at least so far this quarter has been -- I mean, it's been driven a lot by IG and the high yield has been a little bit weak. So can you just help us how we should think about the mix of issuance coming in and how that might impact how we should model the business?

Yes. Year-to-date, we've had very strong hyperscaler issuance within the investment-grade envelope. But if you actually look at the data, we're in the 40% to 45% range for investment-grade issuance this year. That's along the lines of the 45%-ish that we've seen -- 40% to 45%-ish that we've seen through the last 5, 10 years. So it's roughly in line. I think what we're seeing is a little more hyperscaler, maybe a little less in other areas. But investment grade is doing quite well. Like you say, we're seeing not the same kind of momentum in high yield, but that comes and goes.

What we do know is the refinancing walls for high yield for bank loans and so forth are quite strong. And I think there's also a bit of playing the interest rate rise in credit spreads. Clients are trying to see when they want to issue, do they want to issue in advance or afterwards, and that will play out. What we -- I think what we have also seen is we've seen strong -- in addition to strong refinancing walls and pipelines coming through this year, we've also seen good M&A activity, both announced and actually closed.

That's been supportive environment. So it's been -- while there's a lot of talk about the hyperscaler issuances, I think it's been a pretty broad-based year and one that we feel good about. We talk about structured finance volumes, private markets volumes, public and private ratings are both up very significantly. So I'd say a really nice year and an indication -- every indication is that kind of momentum should continue. Obviously, we'll see what the markets and rates, how they play out. But that should continue in various ways.

Got it. Just one follow-up on the hyperscaler issuance. Obviously, they've been dominating the big headlines. I know you said like the growth has been even broader than hyperscaler. But maybe just a perspective, how much is hyperscaler issuance in your mix? And then the follow-up is kind of just -- is that -- how is the monetization of that? Is that close to what a frequent issuer deal looks like? Or how does that -- because these are big jumbo deals almost for the most part, right?

Yes. I mean it's been helpful to the growth rate, but it's not been dispositive, right? This is piece of many, many portions of the issuance environment around the world and across industry sets. The issuances is different than our frequent issuer program, and they are not in our frequent issuer program. Those tend to be reserved for some of the financials we need to just issue for funding purposes.

These are just classic investment-grade issuances. Because they're so large, price realization is a little lower because we price that way for typically across the investment-grade environment. But it's one where we've gotten very healthy realization that we're pleased with. It's in line with what we've seen over the years for large-scale deals. And it's a place we can be supportive. What's interesting is it's not just vanilla bonds, it's structured finance, it's project finance. And that's an area where 2, 3 years ago, we had really innovated and developed a set of methodologies that are particularly pertinent to the market.

I think we were -- we'd led the market in that regard with methodologies that were deep and robust and rigorous. And so now clients come to us very quickly and say, "Hey, can you help us with a rating?" Obviously, analytics and commercial are completely separate. But it's an area where we built the depth and capability that both public and private issuers are looking.

Got it. And just on the margin side in Ratings, I mean, super impressive margins, super high incremental margins. It sounds like there's almost no ceiling. But how do you manage what the opportunity there is? Like is there kind of a range of margins that you try and make sure you're modeling towards?

I think I'll think about it in 2 perspectives. One is, as part of the Investor Day back in November, we talked about 50 to 75 basis points of margin expansion across our various product lines and divisions. And so that includes Ratings. We think that there's continuing opportunity there. At the same time, when we have very substantive growth in Ratings, just like in any division, we think about how do we reinvest that, right? Part of it is we're doing a lot of work, or we describe it as the Analysts of the Future, how do we leverage our analysts and help them get to all of our clients faster response times, how do we automate some of their surveillance work to make it even more efficient for them? And that lets us add more analytic talent back into areas that are developing.

One of the ways we funded a lot of the structured finance work is we found ways to automate other categories and then add analytical horsepower and capacity in some of these newer market areas or will reinvest by cross training, right, our analysts as they cover multiple zones. So there are ways we do that, and then it's -- it also gives us the opportunity to flex and think about where are there areas to tactically expand.

You saw us do the small bolt-on of a Nigerian and African rating service, right? That supplements what we have. It's not only through acquisition, but there's a set of organic investments that we've been deploying and building, and that will continue to do so that the franchise has the same robustness 5, 6, 7, 10 years from now as it does today by getting away -- getting ahead of those opportunities.

Got it. And maybe just a broader question. I mean, I think we've seen it on the Ratings side where your headcount has been almost flattish. And I'm guessing AI productivity, all that stuff helps. Is that a trend we should expect for the rest of the organization as well?

I think you'll see more limited headcount growth than we have before, right? We've talked about it in some of our areas, the Enterprise Data Organization. We've reached peak headcount and now headcount will actually trend down as we just don't need to do as much hiring, and we have just a natural turnover that we can take advantage of in general. And selectively, we'll adjust proactively.

But the tool set has been so effective in that area, in particular, that we can see headcount trends actually coming down. There are other areas where we're just seeing much more productivity. Software development is one that I think many industries are seeing. Researching is another analytical work. But we don't need to add headcount each year to actually service growth, right, because we're doing it through productivity.

And so I think we'll see more and more of that. And I think Ratings, as you described, is a good indicator of that across the franchise and one that we're working towards as we think about planning each year. Right now, we're starting to plan for 2027, right? We're thinking about all the areas of top line opportunity as well as all the areas of productivity and that's -- and thinking about it now so that we can plan, put in place programs and actually get the outcomes that we'd like.

Got it. Okay. We have about 6 minutes left. So maybe some rapid fire into the 2 other segments. So talking about high-margin businesses, Indices, I mean, can those margins go higher? Or is it a case of reinvesting into what's pretty impressive growth in there?

I think it's both, again, right? Ratings, Indices, they are great franchises given the revenue dynamic, the secular expansion of those kind of ecosystems. And we continue to do work in Indices, for example, work around DeFi crypto indices, a recent partnership with Kaiko, who's a particularly strong player in that whole ecosystem with infrastructure data and indices where we're partnering with them on.

And then we can build packages and products for -- of indices for asset managers who want to create products around those as an example. And that just follows around the innovation indices that we've done around fixed income, around multi-asset, around some of the sustainability indices when that was a particularly strong market and one where we'll continue because what we want to do is build that industry and that business for the coming years as well as deliver on the current margin. So we'll be able to do both.

Got it. All right. Thank you, you addressed my revenue question there. So maybe let's just touch on Energy real quick. Because of all the geopolitical issues, I think you've lowered the guidance there. Unfortunately, it's continuing. Can you remind us kind of what you had assumed in that guide in terms of how long the conflict continues? And I think you had guided to a return to trend next year. So is that still kind of in line with what you're thinking?

Yes, that's what we're thinking. We started the year with somewhat more, somewhat higher guidance. Right now, we're about top line growth of 4.5% to 6%. First half of the year has come in just around 4%. And we said in our last earnings call that we thought that second quarter would be the low point, and we'd see some acceleration. So we'll see that both on a half-to-half as well as a quarter-to-quarter basis.

I think what we're seeing -- what we're assuming is some amount of stabilization in Energy markets. Now stabilization in Energy markets may be stalemates, right? So we're open to that environment. And we're seeing our Energy clients adapt. They're highly resilient. They are -- they've historically been very large, long-term thinkers because of the asset intensivity of their businesses. And -- but we see them adapting to this environment. What we've said is that next year, we expect to come back into our medium-term targets of 6% to 8% for the Energy division. And I think you'll see us build into that in the second half of the year. We also see that we won't be lapping some of the current sanctions, which are probably worth about 75 basis points about -- across the Energy division over the last couple of quarters. And that will also be a headwind we won't have to address.

Got it. And does the recent sale of the software assets to SLB, does that help the mix in terms of revenue growth and margins as well?

It does because it was just a software slice of the value chain that we're engaged in. It wasn't at the heart of what we did within the Platts benchmarks and then the data and research around that. And so it didn't have a very good growth dynamics. And so by exiting and at the same time, partnering in that area, we've got now a new partner by which -- through which we can actually distribute our proprietary data and actually makes it even more comfortable for us to sell our data across the ecosystem of other software providers and platforms. And it's also an area where we're building out our interface tools so that, that data can be distributed even more efficiently and effectively than it has more recently.

Got it. We only have 1 minute left, but I wanted to ask you a capital allocation question and then sort of maybe running through the priorities. Just curious since you've taken over, is there any nuance to that, that has changed even if it's just because of the environment out there in terms of what we should expect from S&P going forward?

I think we've been clear at S&P that we want to be stewards of our capital in a couple of ways, right? We want to continue to invest and reinvest in our businesses, primarily on an organic basis. And that means creating enough productivity so that investors get both revenue growth driven by investments as well as margin expansion. That's at the heart of capital allocation from an organic standpoint. We said that we're only interested in bolt-ons and smaller acquisitions and nothing transformational.

You saw us do a couple of those in just earlier this month, right? datacenterHawk, which is a data center power and forecasting area, a Ratings regional expansion in Africa. That's typical, but we're also prudent on the margin, right? And small subscale product lines, given our scale and heft, we want to invest in the bigger and more sustainable areas because they either give us top line growth or margin expansion capacity or both.

Got it. All right. We'll end it there. Thank you so much, Eric, for being here. Thank you, everybody as well, guys.

Thank you.

[Audio Gap] [Operator Instructions] So just to get us started, what are we talking about? And why are we talking about it now? We would be remiss if we didn't at least talk about the SpaceX IPO earlier this year, that brought a lot of fresh attention to the space technology market for a lot of different reasons.

It was a huge market event, catalyzing the overall IPO market in the U.S., a total of [ 146 billion ] of common stock was offered in U.S. IPO in the first 6 months of this year, dwarfing the 26.46 billion offered in the first half of 2025 and the $42.09 billion offered all of last year, according to S&P Global Market Intelligence data. Of the first half total this year, $86 billion was raised by the SpaceX IPO, accounting for more than half of the overall total. This webinar is by no means going to be all about SpaceX, but we just can't ignore the impact that, that company had on the space technology market and the interest around it.

That's also true of the M&A, not just the IPO market. The space technology market has seen 33 -- sorry, $338 billion of investment in the first half based on 193 transactions. This includes both M&A and fundraising. That's up from just under $22 billion from 133 transactions in the first half of 2025. Once again, SpaceX is playing a major role here with its $250 billion combination with Elon Musk X AI or now SpaceXAI and then some of its other follow-up transactions more recently.

But SpaceX or the space story goes so far behind SpaceX's Mega IPO and its mega-M&A deal. It's also about how competitors are turning to M&A to compete with SpaceX, which is the market leader in both satellite broadband and rocket launch capacity. Amazon is racing to catch up with the LEO constellation. And in mid-April, it bought the mobile satellite services provider, Globalstar, for over $11 billion. The deal, which can largely be viewed as a spectrum play, we'll integrate Globalstar's satellite operations, infrastructure and globally operated mobile satellite service spectrum licenses into Amazon satellite network, Amazon LEO, and enable the deployment of direct-to-device services, D2D services starting in 2028.

Then in June, Rocket Lab agreed to buy Iridium for $8 billion combining Rocket Labs launch business with the Iridium's mobile satellite network. And so we've got all of the deal activity that is really designed around these companies positioning themselves to better compete with SpaceX and getting their satellite networks up there, getting that launch capacity up and seeing if they can play catch up.

But before we get too deep into these different constellations and why each was attractive, I want to hand it over to my colleague, Eli, to walk us through some definitions of terminology. And then she'll hand it off to Johan and John to get us started.

thank you so much. Okay. So to dive into the space economy, we figured we should probably talk about kind of setting the scene for what we're actually looking at. So hopefully, you can see on the slide, we've got a bit of a diagram showcasing. Some of the key terminology and some of this might be familiar to our listeners and if not awesome, great, if it is a review, take it as such.

But we want to talk about in this webinar, mostly this focus on orbit. So you might hear some terms such as low earth orbit or LEO right? That is on the left of your diagram. And you can see that usually, that's consisting of satellites for communications, earth observation, scientific research as an orbital space, it's very full and very busy. So you'll hear the term LEO quite a bit. We also have some other orbits that we might be discussing. So we've got our Medium Earth Orbit, which usually consists of some navigation satellites such as those found in GPS.

And then we've also got geostationary orbits, so those would be communications, broadcasting, weather satellites and anything that you want good coverage within that orbital sphere. Some other terms that we want to bring up. We have this as a region between Earth and Lunar Orbits, as the new space economy kind of grows, this area is becoming more and more important. We're talking in transportation, communications, logistics, how do we interact within space as a whole, so not just terrestrially, as we go to the moon as we build out some of our capabilities there, right, how do we focus on lunar space and expand that?

And then, of course, on your far right, we've got Lunar Orbits. There's a couple that we're going to talk about. We've got low lunar orbit and there's near near-rectilinear halo orbits as well, as we develop the space economy and move towards the moon in a bigger way, lunar orbits are going to play just as big of a role as our earth orbits play for us today, right? We're going to need satellites, we're going to need communication. And so all of those are important to keep in mind.

We've also got the lunar service. While we aren't going to discuss it as much in this webinar, it's a key part of the eventual new space economy. So that would be lunar exploration, space mining, research stations even tourism. And along the bottom of the slide, you can see some of the reasons why each of these reasons -- regions matter, sorry. So we've got communications, navigation earth observation satellites, right? We talk about weather and monitoring it. That's what a lot of the satellites that we see today have been kind of working on.

We're going to see an expansion of that. We've got space transportation for that cislunar space area, the lunar economy, which fits into this new space economy, and of course, driving a lot of this, in addition to economics is science and exploration. We love exploring space. We're using it for science for exploration, but also to feed back into the existing terrestrial economy. So we've got this lovely give and take there. So any time you hear some of these terms, right, this is what we mean. This is kind of the scope of our new space economy, not comprehensive, but hopefully a good setting of the scene.

And I'm actually going to pass it back over to my colleague, Johan, who's going to talk about some of the differences between not just the new space economy, but how it compares to this older space economy that we might have seen previously. Johan?

Thank you, Eli, for setting the stage. As you mentioned, the new space economy. That's what we're talking about. And how is it different from the old. Looking at it, just a very brief historic overview. These are -- I think in my life and my parents life even, got you up in the middle of the night, the things that are landing on the moon. That's why you bought it television and watch these. Obviously, this early space rate was dominated by the U.S. and the USSR with national space programs, organizations like NASA, Roscosmos. And in Europe later, the European Space Agency, with the big defense primes as the primary contractors that could build like the space shuttle but they had very high launch cost, enormous, massive rockets, the space shuttle or whichever launch vehicle, bringing up huge satellites into geostationary orbits, primarily focused at weather information communication satellites for -- so in Europe, we could see like American television shows, but also like the navigation systems. Ellie just mentioned GPS, which is just the U.S. version, the type of satellite GNSS, global navigation system satellite.

GPS is the U.S. version GLONASS, the Russian version. And some of these Russian navigation satellites are already up to 50 years old and still operational, more or less. [ Baidu ] is the Chinese version. And then in Europe, we have the Galileo satellites but it was like primarily dominated by high launch cost and up to as much as 300 per kilogram. If we're talking about the new space economy, we see that emerge in the early 2000 as we begin to move towards more reusable rockets, the foundation of SpaceX.

First, private space, like missions, smaller satellites bring down the launch cost. So it opens up to new commercial opportunities. And generally speaking about the new space economy. I'm seeing 3 primary drivers, which I highlighted in 2019, 2022 and this year, the IoT satellites, the Russia, Ukraine war and this year, the Orbital data center push. As cost goes down and the use cases increased the number of satellites has increased significantly during the last decade. And I'll hand it over to John to look at the numbers in the next section.

My team is putting together a series of reports on satellite broadband next month. And so what I did is I went through those 3 reports that will be available to our subscribers and kind of plugged out some of the more interesting tables, I thought to kind of talk about what Johan as the new space economy.

So as we've mentioned, I'm going to be focused mostly on satellite broadband. We do have a report on DTD. And then another one on regulatory threats in addition to the opportunities. The TLDR with regulations is that compared to terrestrial broadband operators, satellite operators have very little red tick to get up and running nowadays, which is -- which is kind of interesting and gives them a little bit of a late-mover advantage in a way.

So Ellie LEO and GEO, I went on into the Kagan archive yesterday, and I was wondering when satellite broadband started. And our first numbers were in 1998. 23,000 satellite broadband customers at the time those services use geo, geostationary satellites, which are anchored to their position in the sky. So for example, just envision where you're sitting right now as you watch this webinar, there's a satellite above your head.

As the earth spins that satellite still above your head, morning and day. These satellites, they're 10,000 miles plus above the earth that impacts the speed you get in the broadband and also the latency. And the new version of satellite broadband launched around 2020, including these LEO satellites. And these things are only about 100 miles above the ground. It's very close to the earth, and not -- they're not -- they're not like anchored to the earth. They're flying at 18,000 miles an hour above us over our heads.

It's actually a pretty cool website called satellitemaps.space. You can kind of find where you live, zoom in and they track the StarLink satellite. You can see how fast 18,000 miles an hour is. It's pretty shocking to see that. But 100 miles above your heard, you can get a lot better speeds, a lot lower latency. So it kind of kind of change things for satellite broadband.

And Johan mentioned Sputnik. and sputnik until Y2K, we went from 1 to 700 satellites. And as the costs have come down and the new space economy has kind of emerged since 2000, we've added over -- I think, that number is just from orbitalradar.com. It's more like 17,000 satellites in space right now. So it's ramped up. I mean you talked about a hockey stick of growth. This is kind of quantifying how fast and how many more satellites there are now.

And about 2/3 of those satellites belong to Starlink alone. Digging in a little bit to the components of these LEO operators, the current constellation is -- or as of March across the big ones, there's about 10,000 here. and their total plan that they've got approval from to eventually put up in space. And that hockey stick is not stopping anytime soon basically is kind of the takeaway here. This also in the bar chart kind of underscores the scale at which Starlink and Amazon LEO are going to have when we just look at these LEO satellites orbiting currently and in the future.

So shifting gears a little bit, looking at back on earth, if we look at the broadband market in the U.S. in 4 different buckets: cable broadband, telco, which includes fiber and DSL, satellite, which is what we're talking about and fixed wireless. And Fixed wireless has been the major growth story in the United States since 2020. And I think in the last couple of years, satellite is not becoming another growth story. So again, back in '98, it started modest, and it never really cracked 2 million subscribers up until about 2020.

And now we have -- just in the last year, if you look at that market share table down there, satellite has gone from 2% share to over 3% share. in the United States just based on Starlinks growth alone. The next slide digs in a little bit more to the components in the U.S. for satellite broadband. You've got the 2 legacy operators. And then, of course, Starlink ramping up on the left is total subscribers on the right is net additions by quarter.

Starlink really ramped up recently compared to their competitors. Looking at the economics a little bit on this line chart on the left here, this is average revenue per user per month for broadband services. That blue line that starts out in '23 is the highest. That's just Starlinks ARPU, and you can kind of follow that line as it falls to the right and down through 2026. And you kind of envision, okay, they're competing for market share by holding down their price.

Now the other 4 lines are the other 4 broadband technologies, which have basically tracked inflation for the most part. I think things starting to soften up last year as the culmination of StarLink and fixed wireless, led to what I call the broadband price war last year. This is now no longer a low-hanging fruit market. It's pretty saturated. And leading up to the IPO, StarLink rates in the U.S. were as low as $30 a month, which is an incredible discount compared to what the competitors we're offering.

I think they still have some $30 a month service offerings, but on the table on the right is looking at the economics of the SpaceX connectivity division, which is basically Starlink. And they're getting a good profit margin already in terms of EBITDA and adjusted EBITDA in the 60% range in 2025. On the next slide, this kind of underscores -- these are the top 10 countries in the world by broadband penetration like satellite penetration.

And there's 2 takeaways here. Number one is it's not a primary connected connection method for broadband anywhere. I mean the biggest adoption rate is in [indiscernible]. And so it's not like the leading broadband method anywhere. The other takeaway here is, I think 8 of these top 10, if you look at the countries involved, U.S., Australia, Russia, Canada, these are geographically large countries with the population spread out, which really kind of hits home to what satellite broadband sweet spot was.

It's really good for rural area and rural connectivity. And the reason is because running wires, whether they be fiber or DSL or cable to remotely populated areas, the return on investment just isn't there for a lot of companies. I've heard some companies say it's as high as 100 years until they get that money back from digging a trench and running a line and connecting the home, whereas you put satellites up and you connected those homes automatically as long as they have a line of sight to the Sky, there's no trees or mountains in a way.

I did because I covered wireless for 15 years. I was curious about what the spectrum map looks like for the big 3 broadband operators in the U.S. And Starlink, ViaSat and Hughes, they have far more megahertz worth of spectrum than the terrestrial wireless operators. I think if you look at Starlink 15,000 total megahertz is about 15 x one of the big 3 wireless operators has in terms of low and mid-band spectrum. They have about 1,000 megahertz to run your smartphones and also this fixed wireless technology.

The biggest difference is these guys all share Ku-band spectrum. Now the wireless operators, they buy at auction and they pay a nice premium to have access to spectrum chunks that's just their they don't share it at all. We're looking for simple ratios to make at Kagan. And one of the things I kind of looked at here was, well, how many subscribers per satellite in orbit are these big 3 operators dealing with. And that's the graphic on the right there.

And I kind of went through for Starlink and tried to count the satellites in orbit above the Lower 48 in Hawaii and Alaska. And it was about 200. I saw yesterday, someone had estimated it was more like 500 satellites above those countries that could be in the range of your home connection. And so -- but anyway, using my more conservative 182 satellites, you divide that by 3 million subscribers, it's only 17,000 subscribers per satellite for Starlink, and that really kind of underscores a big difference between LEO and GEO just in terms of the volume of satellites we're talking about here, with LEO compared to the legacy satellite broadband services.

As Sarah mentioned earlier, there's been a couple of big satellite deals, again, thinking of the ratio to kind of compare these guys to looking at LEO and GEO. It's kind of a mixed bag right now in terms of Total deal value divided by its satellites acquired. We do this a lot for towers for wireless communication companies, but there's a big tower deal, we give an average of value per tower and it's more like $200,000 to $1 million per tower.

Compared to here, we have -- it's in the millions per satellite acquired and the 2 deals from this year so far are definitely ranking up at the top of this table. Just kind of underscoring just how popular this. It's a good story right now, and it's a hot space. So the deals are pretty expensive. And my final slide, this one is a little bit of a head scratcher for me. But so let's start with the bar chart on the right, that is the cost to build a terrestrial communications tower for smartphone connection and for fixed wireless, about $0.5 million. to build a tower in the United States, and that doesn't see -- and the red tape, the costs involved with -- and the time involved to get approval with local state county et cetera, et cetera, to build your tower, it can take many years to get approval and build these things.

And the accountants say, okay, we're going to amortize this asset at a 30-year cadence. I think that's -- a lot of us have 30-year mortgages. It's kind of a real estate business kind of makes sense. I think if you maintain your tower properly, that tower can last forever. I mean Eiffel Tower is over 120 years old. They maintain it. They make sure it's not rusting that thing will last forever. So shifting gears now and looking at satellite. Well, I was curious about -- for those satellites launched, on average, what does it cost? I'm looking at V3, which StarLink just launched last week, some test launches for this.

So looking forward a little bit for all those LEOs up there that Starlink, it's about $1.4 million to build and to launch and get these things in orbit per satellite. So it's a lot more than a terrestrial tower. But the thing that confuses me a little bit is that the accountants say the amortization schedule is just 5 years for these things. After 5 years, the life span of that LEO satellite has -- we can bring it back through the atmosphere and let it burn up, we don't need that satellite anymore.

The economics of that is a little bit confusing to me. And I think what Johan mentioned earlier about the cost. This $1.4 million per satellite is not set in stone. It's going to keep coming down, and that might make this make a little bit more sense. So -- but it is kind of interesting to think of none of these wireless operators are burning down a tower after 30 years of operation, they can use them a lot longer than that. And so there's an economic question here, but then there's also a little bit.

There's definitely an environmental concern with how many hundreds of satellites are going to start falling through the atmosphere and burning up and hitting birds and adding to pollution and things like that. So on that note, I'm going to switch gears and pass the microphone back to Johan.

Thank you, John, for that introduction. You primarily talked about communication satellites. In the introduction, I mentioned the IoT satellites as a push for the first wave of expansion. And roughly since 2019, we've seen dozens of new start-ups focusing on small satellites in low-earth orbit to serve those IoT use cases based on low-bandwidth communication protocols such as LoRa 1, NB-IoT and some proprietary protocols. What we've put on this slide is that we've been monitoring the adoption of some of these use cases in our 451 Research, voice of the enterprise, the OT perspective survey. We have monitored the adoption of satellite technology by enterprises. And especially in the oil and gas sector, already 67% of respondents indicate they leverage satellite connectivity.

And of these, like 2/3, monitoring remote assets is by far the most popular use case followed by several environmental use cases. And asset tracking is mentioned by 30% of oil and gas companies primarily focusing on locating like very expensive equipment that tends to get lost and someone can't find it. But if we talk about these IoT satellites, we've seen many startups come into play like 2019, 2021. The difference is compared to the old navigation satellites and communication satellites in geostationary orbit. These are operate in low earth orbit.

And they are a lot smaller and therefore, also a lot cheaper. But compared to the GLONASS satellite operating for 50 years. John just mentioned like the amortization 5 years life expectancy, in low earth orbit, the cube sats has become the standard. And Cube sat refers to cubes of 10 x 10 x 10 centimeters in different configurations. So you can have a 2U for you or a 6U satellite configuration totaling the number of 10 x 10 X 10 cubes.

But obviously, those are lot lighter than the old mega satellites that operate in geostationary orbit. But we've been tracking those companies, those IT startups for several years. And we saw a myriad of startups entering to different use cases. Each launching with an idea the specific use case that gained some traction, monitoring fishing boats in Indonesia or herd kettles on the Argentinian planes or pipelines in Siberia. And many of these start-ups stay launched their own proprietary constellation or at least they filed their plans with the FCC spectrum applications.

So earlier, John mentioned roughly 15,000 active satellites. But looking back at the forecast, we did in 2023, we saw that the total application for spectrum amounted to over 100,000 satellites by 2033. And since we're only 3 years into that decade forecast, the numbers are falling short of the FCC filings, particularly SpaceX aimed at [ 42,000 ] by 2030, still a little under 10,000. So they're falling short on their own ambitions. In many cases, the business case proved hard.

Some of the start-ups pivoted, abandoned their own constellation plans, piggybacking on other constellations or just refocus to the specific use case data collection. And since the starting of the war in Ukraine, we've seen next drive emerge. spy satellites, of course, have been the exclusive domain of national governments, departments of defense.

During the war in Ukraine that shifted. Military on both sides started using commercial observation satellites. So whether it's Hyperspectral imaging, synthetic aperture radar or just high-resolution optical satellites to just assess troop movements, even identified targets, Starlink became essential for drone navigation. And just the military use of commercial satellites, another trend emerged. Those private citizen started using Maxar planet ISI, satellite for open source intelligence to support Ukrainian army in identifying targets or simply to confirm Battlefield claims or investigate rocket damage on civilian targets. Currently, we're in 2026, and we're seeing a major push in FCC filings for orbital data centers.

And the primary post, I think, is the debate that's going on by the proliferation of AI and the power consumption of AI data centers and the availability of energy. So the immediate reflex is like, okay, we got space in space, and it's gold. So we don't have cooling issues. We don't have CO2 emissions. We can directly capture energy from the sun. So we solve the energy problem, but it's a little bit more complicated than that, and Ellie will go into that later.

But the FCC filings this year they've been accumulating to pretty much of a perfect galactic storm with, obviously, Starlink Space Act's being most ambitious, again, announcing plans for 1 million orbital data centers; Blue Origin, 51,000. And there's a couple in the bottom that are still in development, don't have finite numbers on the constellation plans. There is a very small red dot on the left-hand side, Kepler Communications, which should be even smaller, so small, you wouldn't see it.

So it's a bit larger than comparative, but Kepler Communications is an example of a start-up that has an orbital data center in space. But to put that into perspective, its first orbital data center has 44 GPUs and compare that to a hyperscale campus in context like the IT satellite ambitions, there is a difference between FCC spectrum applications and what will actually be built.

So are we chasing stellar mirages or dreams. We're seeing definite use cases for space edge computing. So some of the drivers that we're seeing, the energy constraints, cooling, CO2 emissions might look to be an answer. But Ellie will tell you that's more complicated. Because on the [ inhibitor ] side, we see the same things emerge as [indiscernible], the energy constraints, cooling, radiation shielding, orbital add to that. If we're looking at the trends and challenges, we see the vertical integration that Sarah mentioned, Amazon, Iridium, Rocket labs, it's not just satellite companies buying competitors operating in the same space.

But it's space companies buying capabilities in different orbital plane. So Starlink for instance, operating in low earth orbit, buying larger communication satellites in geospatial orbit or it's the vertical integration that concentrates the entire technology stack and not just the satellite capabilities, but also the launch capabilities, the rocket technology or robotic engineering companies for autonomous operations, for instance, for in-orbit servicing as these data centers could have a life span of 5 years, they would need servicing.

But one of the trends that we primarily see emerging space edge, compute, as all these earth observation satellites capture more and more images, high-resolution images of earth. It makes sense to do the first processing in space. So space edge compute before sending down the results to Earth to avoid downlink constraints rather than sending up AI inferencing workloads from earth up to space.

Space communication. As Ellie mentioned, we're moving on towards Lunar space operations. We need to establish that space communication infrastructure to enable asteroid and Lunar mining, but the business case remains a hard nut to crack. Then there's sustainability and sovereignty, which we'll touch upon later.

But as the example from the Ukraine, Russia war already also showed is that we have a governance issue to solve if military uses commercial satellites. How does that happen? How does that work? Who is responsible? And then there's a whole lot of other challenges that we will dive into.

All right. Perfect. I'm going to take over the screen a little bit and talk about some of those challenges that Johan had mentioned. So obviously, this slide says sustainability, but I would love it if we framed it more as practicality, right? We're talking about expanding the space economy and moving into these new levels of satellite launches, stuff in space. We need to think practically about what that actually means in terms of how do we make this happen and then also the impact if we make it happen.

We have a great opportunity here as we're scaling into space to move into this new frontier and to build it sustainably from the ground up. And that's not something that you always get the opportunity to do, right? A lot of times, you start with a project and you're already halfway though it and you look back and you say, "Oh, I would have done that differently, right? But as we're moving into these new frontiers, we have the chance to really start smart and build things in a way that will last in a way that is actually good long term and works well.

So that's kind of what we're going to talk about in the next couple of slides here. And so as we talk about sustainability within the space economy, the long-term growth of space economy depends on managing resources responsibly. And resources come in lots of different shapes and sizes. Obviously, you think environmental resources.

As we talked about, we have orbital resource constraints as well. And we'll dive in a little bit into that in a bit more detail. And we'd like to look at sustainability across an entire lifespan of an operation as we discuss the space economy, obviously, we've talked about satellites. We've talked a little bit about data centers in space, launch systems, right? All of that, plus the supply chain goes into these considerations along with end-of-life considerations and deorbiting procedures because as John had mentioned, we can't just leave stuff up there forever, right? It's not like building a tower, it's not going to work for 30, 100, 150 years.

There are other considerations that we need to Keep in mind, as we expand into space because the environment there is, frankly, very different than what we're used to on Earth. And each stage of this space life cycle includes different sustainability considerations that are going to be magnified as we try to hit these proposed expansions into the space ecosystem. So first, looking at supply chain, right? And when we're talking data centers in space when we're talking satellites, compute communication, rocket launch technology that stuff doesn't just magically materialize in space -- in earth, right? We need physical materials to make all of this happen.

So some of the same constraints in supply chains that we're used to dealing with on earth for compute construction, for communication, that all comes into play in the same way as we enter the space economy. So carbon fiber, aluminum, titanium, rare earth minerals, all of these have some sustainability implications from extraction and processing. They're well documented on earth. It kind of doesn't matter whether you're building a data center on earth or in space, you need those materials to do so. And we can get into asteroid mining later, but you need to get the material from somewhere, and that takes work, right? And that has add-on consequences.

So as we move along kind of the space story, we need to get stuff into space, right? That also takes work. And traditionally, we have rocket propellant and all of those from solid rocket fuels to refined kerosene, those release emissions into the atmosphere. So you can talk about emissions from terrestrial data centers.

But as we move into space, it's not emission free, it's just you change kind of where those emissions are released. And a lot of that is from the launch technology. And with traditional rocket propellants, most of the time, they've included large amounts of ozone-depleting chemicals, including black carbon, and we have nitrogen oxides. Part of the issue with rocket launches that isn't really factored in when we're talking terrestrial data is that you're actually launching into the atmosphere. So where are those emissions are released really changes the impact of those emissions. And so they can be a lot more destructive and harmful if they're released into the atmosphere as opposed to closer to Earth surface.

As rocket launches continue to scale, we talked about the cost of Rocket lunches going down, but we also need to think about the environmental cost of rocket launches. Yes, you can make it cheaper and cheaper to get into space. But if you're still being massively pollutant while you're doing it, we should consider that as well.

Fossil fuels burned by the space industry right now, only make up about 1% compared to those burned by conventional aviation. So obviously, the numbers are really, really small right now. But if we look at all of these FCC filings, as we look at how things have really scaled up in terms of what's going where, moving into space, the projections for where we want to go, that ratio is going to change, right? And we're lucky now because we have the opportunity to really target that and think about that from the ground up, no pun intended.

The pollution launches is definitely something that we need to keep in mind. Not only are we talking stratosphere and mesosphere and the atmosphere impact of all of these emissions, we also need to keep in mind, launch site ecology. And we've talked a lot -- there's been a lot of studies done around rocket launches, the impact on local plants, animals, the environment, right? We talked about well-executed rocket launches. You can do a pretty good job planning and saying, okay, if this launches successfully, this will be the impact on the local ecology.

Of course, anyone who has tracked anything with the space economy knows that not all rocket launches work successfully, right? You have a catastrophic failures, you have learning events. And I'm sure you're learning quite a bit. But when your rocket blows up on the pad, what does that mean for the local landscape through vegetation and for the animals, plenty of space agencies, including NASA monitor launch sites and try to minimize launch impacts. But that's not the case across the board. There are several launch sites around the world that have historically just kind of been used for rocket launches without much concern for the local environment, creating large zones of pollution caused by years of leaking and toxic rocket fuel, seeping into the soil.

So we can really cause a lot of problems if we aren't thoughtful about how we're launching stuff into space. Now when we move on to the third section of kind of this space life cycle, which is the actual in-orbit section. And we'll talk about -- I'll talk about it a little bit more in the next slide.

But we can get something called orbital congestion, right? So even though space is big and we have relatively few numbers of satellites now compared to what we want to put into space like we have limited orbital bandwidth for what can go where. And so on the next slide, I'll talk a little bit more about the congestion story. We also have this new kind of type of satellite that is being designed to specifically serve as orbital mirrors beaming some light on-demand to different places around the world. even nonorbital mirror satellites can reflect quite a bit of sunlight toward earth.

And so when you put satellites into orbit, they actually can be really detrimental especially to research and astronomy and physics as you're trying to look past our earth orbit and into the greater cosmos, and we need to keep mind this for us here on earth, but also as we try to continue our exploration further out, we need to make sure that we aren't blocking ourselves off intentionally or unintentionally.

And then finally, at the end of a satellite's life, we want to keep in mind some of the sustainability considerations there as well. So that would be disposal without causing massive problems. So one of these solutions to help prevent overcrowding orbits is this idea of deorbiting satellites. So there's a couple of ways to do that. And you can safely degrade an orbital satellite and let it burn up in the atmosphere on purpose. So this is controlled. This is meant to clear up overcrowded orbits instead of having a bunch of dead satellites orbiting around causing problems.

Deorbiting satellites is pretty standard practice anymore. In low earth orbit satellites are usually finished with their mission and they're mandated by the FCC and the European Space Agency orbit as soon as possible, and it's actually baked in that they aren't supposed to orbit any more than 5 years past their mission completion. So there is a plan already in place to try and help keep those orbital lanes as clear as possible. The problem, of course, with burning up satellites as they reenter the atmosphere is just like burning jump here on earth, they release additional pollution into the atmosphere.

So that adds to the emission problem, right? We aren't just meeting as we launch these satellites and those systems, they're also further emitting as they reenter the atmosphere. And some satellites, we don't deorbit at all. We actually move them into a graveyard or a junk orbit, which happens further up. So instead of burning up inside of earth's atmosphere, these satellites are moved into these kind of long-term storage orbits that are outside of our low earth orbit and our geostationary orbit and are meant to kind of be long-term holding cells, graveyards for these dead satellites.

And it does help clear operational orbits. But we have this nice beautiful, unpolluted, so to speak, space that we are now just dumping junk into. So it's worth keeping in mind that as we have graveyard orbits, they're going to stay there, these satellites for thousands or even millions of years. They don't break down in the same way that you have stuff weather here on earth, there's not air resistance, there's not weathering.

If you put something up there and you don't deal with it, it can stay up there for much longer than any of us are going to be around. So it's worth keeping in mind kind of our long-term impact as well. So those are some of the things to look at from a sustainability perspective. And just a little bit more on this congestion sort of story. So we've gone through a lot of numbers already on this webinar and talking about what is up in space, right? And it's interesting to think about because most of the time you look up at the night sky or even the sky in the a day, and you don't see much, right? You got your clear blue sky, you've got lots of stars, sometimes you'll see the fun SpaceX constellations going around in their little trains.

But there's actually a lot of space debris up in space, most of which we can't see with the naked eye. So with these numbers, we've got from the European Space Agency. And we've had, since 1957, more than 7,000 rocket launches total placing more than 26,000 satellites into orbit. Now these aren't satellites that are operational, right? These are just -- satellite that has ever been placed into orbit since 1957.

And the total mass of all of these space objects in orbit is more than 16,000 metric tons, okay? Now we talk about satellites as these nice little packages. But they don't always stay that way. I mentioned that things don't weather in space, you don't get degradation. Well, that happens as long as they don't run into other things. But if we have collisions in space, things are moving very, very quickly up there and that can cause debris fields that can really amplify the amount of stuff that we've got in orbit at any given time.

So on the right-hand side, we've got some estimated numbers of objects in orbit. There's no way to really count. All of these are based off of models, again, in this case, from the European Space Agency. So as far as objects go, those that are greater in size than 10 centimeters, we've got about 54,000 objects, right? That could be active satellites that could be and pieces of satellites anything that's 10 centimeters or bigger, we've got 54,000. But as we move into these smaller and smaller scales, we've got millions and millions of very small pieces of space junk that are just orbiting around.

And you can think oh, well, a small thing isn't a problem, but think about a bullet, right? A small thing moving very quickly can become very problematic very quickly. And one sort of term you might read about or come into contact with is this idea of the Kessler effect, which is that these small pieces of space junk can create these catastrophic chain effects where all of these interactions and collisions can lead to [ full orbital bands ] that can't launch satellites that they interfere with communications that we can't use an orbital band because it is so full of junk and it's just not safe.

And while that hasn't happened yet, it is something that really needs to be considered as we must avoid this scenario at all costs sort of thing. So having a proper plan in place to make sure we're deorbiting satellites in a safe, sustainable way that we're dealing with this space junk problem, right? We already have a lot of space junk that's out there. And if we could minimize the amount that is in our orbits that we want to use, that would be very important as well, especially as we're trying to expand and really regulate what's going on up in space.

And with that being the case, right, we really need to focus on international standards, space traffic management actively removing the debris that's there. And then, of course, as we've already started, we've got this reusable launch system already in place. We've got work being done for more efficient fuels and the work towards building a sustainable space economy is definitely actively happening right now, but there's certainly more to do and more to think about.

It's never just as easy as, well, let's just send the data center up to space, and we'll be done with it there. All right. One quick note that I wanted to make on sovereignty. I know we're getting close on time. We had a really great look forward journal article published by a bunch of 451 Research analysts come out recently. There's a lovely QR code in the bottom right corner of your screen, if you want to read the full report and discussing this idea of compute sovereignty and kind of what that means terrestrially. I did want to flag just really quickly this idea of sovereignty as a driving factor within the space ecosystem as well. So governments across the world are looking at sovereign cloud environments, domestic AI, high-performance computing, quantum computing skill and capacity and just to make sure that we've got secure data shortage, transmission that things are built in a safe sovereign way.

And as we look at space and space infrastructure, sovereignty as well is going to continue to come up as a key driver here. And because the same questions and the same discussions we're having here on earth are going to apply to space. And that includes with data sovereignty, application sovereignty, compute sovereignty as we look at data centers in space a little bit more. And so that's going to play a driving role in that.

So what's next? We've got all sorts of stuff coming up, space mining, infrastructure build-out, the new space race regulations. There's a lot that's going on, and we're excited to keep tracking what's going on within that. So I know we're close on time, I'm going to pass it back over to Sarah and she can manage any Q&A?

Thanks, Ellie.

Yes, we had a couple of questions come in, and I'm going to race through them so that we can cover as much ground as possible. We had a question come in about satellite life spans? Are they considered technically not useful anymore after the 5-year time frame we mentioned. That's a really interesting question. And honestly, it depends on the constellation we're talking about, right?

Now we're talking -- that 5-year time line has mostly to do with the Starlink LEO satellites that spend lot of the webinar talking about, some of the constellations that are -- have different constructions like Telesat. Their construction, although LEO, their satellites are going to be a little bit higher up, they're going to be a little bit bigger, they're going to -- they envision launching far fewer of them. And those satellites are expected to launch -- or expected to last. I think, closer to 15 to 20 years, if I remember correctly, as opposed to that much shorter life cycle for the lower earth orbit satellites that Starlink, but then also Amazon's LEO envisions using.

And so that is in terms of these different ways, these different constellations, that's definitely something to keep in mind. Ellie, we had a question come in about space radiation damage, data centers and how -- what are you hearing on that?

Yes, for sure. So Johan and I have actually been on some great briefings around that. And yes, long story short, radiation can cause problems in space. Obviously, when you're on earth, you have atmospheric protection from a lot of space radiation, that's not the case when you're up in orbit. And so there are a couple of ways to manage that. You can either help secure any of the chips behind different types of materials to block against radiation. There are radiation-hardened chips that are available. And I'm not sure, Johan, if you want to talk a little bit more about some of the radiation solutions that we've learned about in some of our briefings.

Well, looking at the traditional old space economy, you use like ruggedized chips, especially manufactured to withstand radiation tested, $200,000 a piece, life time [ 30th plus ] still operational in the international space station. But that's not keeping pace with commercial off-the-shelf capabilities. So yes, we see companies working on shielding technology, whether it's the chip itself in the semiconductor industry. We're seeing fully depleted silicon on isolated process technology, just to harden the chips or specialists working on more of the casing in various materials to withstand the radiation.

John, we had a quick question come in about your Slide 21, how many users per tower versus satellite, you brought up costs. And so just wanted to get a clarification on that one.

Yes. Is this the number of users per terrestrial tower.

Yes.

I ran some quick back-of-the-envelope numbers and including -- if you're a Tier 1 operator, you have 100 million subscribers, maybe most of those are human. Some of those are double count. There's some tablets. There's smart watches, there some cars included in there. Just a perfect human ratio, but assuming 50,000 pole towers, the number is about 26,000 people per tower. If we add in small cells and DAS networks, that number shrinks down to about 1,200 people served per tower, but there's a ton of caveats there, but I think generally speaking, the terrestrial networks serve a lot less people per tower than the satellite networks do. Good question.

Well, I know we are at time, and that you can continue to use the Q&A widget to submit your questions, and we will try and follow up with you. But I want to thank John, Ellie and Johan for their insightful presentations. We've covered a lot today. So if you have any follow-up questions, please use the contact with it, and we would be glad to assist. For those who want to review anything we cover, this session is recorded, and you'll receive a copy shortly, so you can access that on-demand at your own convenience. And when we close out of the webinar, you will be routed to our webinar survey form. We hope to see you at future events. Thank you all so much for your great time and questions.

Good morning, and welcome to S&P Global's Second Quarter 2026 Earnings Conference Call. I'd like to inform you that this call is being recorded for broadcast. [Operator Instructions] To access the webcast and slides, go to investor.spglobal.com. [Operator Instructions] I would now like to introduce Mr. Mark Grant, Senior Vice President of Investor Relations and Treasurer for S&P Global. Sir, you may begin.

Good morning, and thank you for joining today's S&P Global Second Quarter 2026 Earnings Call. Presenting on today's call are Martina Cheung, President and Chief Executive Officer; and Eric Aboaf, Chief Financial Officer. We issued a press release with our results earlier today. In addition, we have posted a supplemental slide deck with additional information on our results and guidance. If you need a copy of the release and financial schedules or the supplemental deck, they can be downloaded at investor.spglobal.com.

The matters discussed in today's conference call may contain forward-looking statements within the meaning of the Private Securities Litigation Reform Act of 1995, including projections, estimates and descriptions of future events. Any such statements are based on current expectations and current economic conditions and are subject to risks and uncertainties that may cause actual results to differ materially from results anticipated in these forward-looking statements. Additional information concerning these risks and uncertainties can be found in our Forms 10-K and 10-Q filed with the U.S. Securities and Exchange Commission.

In today's earnings release and during the conference call, we're providing non-GAAP adjusted financial information. This information is provided to enable investors to make meaningful comparisons of the company's operating performance between periods and to view the company's business from the same perspective as management. The earnings release contains financial measures calculated in accordance with GAAP that corresponds to the non-GAAP measures we are providing and the press release and the supplemental deck contain reconciliations of such GAAP and non-GAAP measures.

For today's discussion, references to revenue are to GAAP pro forma revenue on a consolidated basis, GAAP revenue for our Ratings and Indices segments and adjusted as recast revenue for our Energy and Market Intelligence segments. Other financial metrics discussed on today's call are presented on an adjusted basis and refer to pro forma non-GAAP adjusted measures.

In a press release dated July 6, 2026, the company provided recast financial information, excluding contributions from Mobility for the 4 quarters of 2025, full year 2025 and the first quarter of 2026. That release can also be found at investor.spglobal.com.

At this time, I would like to turn the call over to Martina Cheung. Martina?

Thank you, Mark, and thank you to everyone joining the call this morning. I'm excited to host our first earnings call since completing the Mobility spin, and I'm excited to be able to discuss the progress and the vision of our 4 divisions. We had very strong performance in the second quarter with 11% total revenue growth, outperforming our expectations on both the reported and an organic constant currency basis. Recurring revenue was up 8% year-over-year as well. The strength of our benchmark business has really shone through in the second quarter as well, with revenue increasing 15% year-over-year.

With high incremental margins in our benchmark products and disciplined expense management across the business, we were able to deliver 200 basis points of margin expansion, leading to EPS growth of 23%. On capital return, we have decided to increase our target share repurchase for 2026 by nearly $3 billion to more than $7 billion for the full year. As Eric will walk through shortly, our strong cash flow and healthy balance sheet will allow us to repurchase equivalent of more than 5% of our current market capitalization.

In the last few months, we've seen the end result of a great deal of exceptional work from teams across the entire organization. On July 1, we finalized the spin of our former Mobility division into an independent publicly traded company, which immediately creates meaningful shareholder value. We announced the consolidation of our supply chain efforts into our Energy division as well as new leadership and a new operating model for Market Intelligence.

We'll provide some additional insights on those points in a moment. We've also seen continued rapid adoption of our AI solutions, including our Kensho LLM ready APIs, and we've continued to explore different monetization methods with our large, sophisticated customers. We also announced an agreement to purchase datacenterHawk and the majority stake in Agusto & Company. datacenterHawk will combine with our 451 Research and energy forecasting assets to extend our leadership in the data center space.

Agusto & Company is a leading credit rating agency with operations in Nigeria, Kenya, Rwanda and Ghana. All of these milestones are evidence of the progress we are making in executing the strategy we announced at our Investor Day last year. With the completion of the Mobility spin and the division realignment, we are well positioned to deliver on the strategic objectives we have laid out. We will continue to invest to advance our market leadership and benchmarks across the debt, equity and commodity markets.

In Market Intelligence, we will make focused investments in the fastest growth areas while improving the profitability of more mature platforms. That will help us optimize the Market Intelligence business to meet the evolving data and AI needs of our customers. We are also integrating our data to create new opportunities and expand our addressable markets through Kensho data. Now that we have simplified the business down to 4 core divisions, it's more clear than ever how these divisions can create a powerful platform to help our customers navigate volatile markets and turbulent macroeconomic conditions.

As I've shared with you before, we are primarily a benchmark business. Benchmarks include our Ratings division, our Indices division, the Platts business within our Energy division and the distribution of our Ratings content through Market Intelligence. These benchmark businesses account for nearly 2/3 of our revenue and now comprise more than 80% of our operating profits.

Given this is the first earnings call since we completed the Mobility spin and realigned 2 of our 4 divisions, I wanted to discuss each division's growth drivers and strategic priorities before handing off to Eric to discuss financials and guidance. Beginning with Ratings, which is now our largest division by revenue. The market appears to be pricing in slightly higher rates than we expected at this point last year, though credit spreads remain very tight. Billed issuance increased 25% year-over-year in the second quarter, with strength across the risk spectrum. Investment-grade issuance was again bolstered by large issuance associated with AI infrastructure and data center CapEx as well as M&A.

We also continue to drive innovation in fast-growing areas of with DeFI. Issuance from the hyperscaler infrastructure companies slowed in the second quarter as we expected, but remains quite strong and is pacing well ahead of our initial expectations for the year. In the first half, we saw approximately $169 billion in billed issuance from the hyperscalers while our initial outlook for the year assumed approximately $200 billion for the full year. Our updated financial guidance assumes billed issuance growth in the mid- to high single-digit range.

We are now assuming $250 billion to $300 billion in hyperscaler issuance for the full year and double-digit growth in M&A related issuance. As we look at our midyear refinancing study, we continue to see robust maturity walls for several years, reinforcing our expectation for strong average annual growth. Over the last 12 months, we have seen billed issuance grow at an average of roughly 20%. And despite that very strong issuance and our outperformance in the first half of 2026, the near term and multiyear maturity walls remain quite strong. This is a powerful indicator that the strength we are seeing this year in Ratings is not coming at the expense of future refinancing activity.

In the next 4.5 years, we expect to see approximately $11 trillion in rated debt come up for refinancing, which bodes well for the multiyear growth opportunities in Ratings. Now turning to Indices. We continue to extend our leadership as the world's largest provider of indices by AUM. ETF AUM for S&P Dow Jones Indices ended the quarter at $6.35 trillion. We continue to see an even greater amount of AUM tied to our indices when we include mutual funds, OTC derivatives and insurance products.

We have built an incredible Index franchise founded on trust, transparency and disciplined methodology, while being responsive to an ever-evolving market environment. Our results demonstrate the strength of that franchise as S&P Dow Jones Indices was the #1 index provider yet again in terms of flow capture. Year-over-year, we have seen more than $600 billion in net inflows. June marked a significant milestone for the global markets as well as we saw the first ever ETF surpassed $1 trillion in AUM. We're incredibly proud to be part of that story as that ETF was based on the storied S&P 500.

We also continue to invest to drive new, innovative solutions in DeFi. Just last week, we launched the S&P Pantera Digital Asset Index, which uses a rules-based approach that focuses heavily on fundamentals versus focusing strictly on price momentum or market cap. That innovation is driving real economic value and competitive wins as well. In the second quarter, we saw multiple asset managers switch to S&P, bringing tens of billions of dollars in additional AUM, now benchmarked against S&P Dow Jones in Indices.

Now turning to our energy franchise. As we outlined back at Investor Day, we will be reporting Energy in 2 business lines going forward. The Platts benchmark business includes our price assessments, global trading services and other offers associated with our energy and commodity benchmarks. The CERA business line includes the proprietary data, content, research and events, including the holistic supply chain suite that previously was spread across energy and Market Intelligence.

When we think about the performance of the energy business, not just in the quarter but longer term, there are a number of factors impacting growth with long-term positive factors offset somewhat by near-term headwinds. We are confident that the secular tailwinds in this business remain intact. Energy expansion continues to be one of those tailwinds and informs much of our strategic focus. Our price benchmarks remain the gold standard across energy and commodities markets, and we will continue to invest to launch and scale new benchmarks.

As supply chains diversify and evolve, we continue to make investments in regions of the world like North Africa that are poised to play a more important role in global energy and commodity markets. We expect to see strong economic growth in these regions and look to work together with local partners to help deliver that growth. Global supply chains aren't just raw materials and manufacturing, they include technology supply chains involving data centers and power and represent a meaningful opportunity for our energy business.

That opportunity is exactly why you saw us acquire datacenterHawk. We're confident that as the demand for AI increases, the need for our data and insights will increase as well. We've also made great progress with CERA Titan and remain on track to officially launch our new AI native platform for upstream data later this year. Despite the many long-term tailwinds in energy, there are some factors that pressured results in the quarter, though not unexpectedly. Importantly, the Iran conflict has complicated contract renewals among some very large customers, and we have intentionally chosen to be flexible on price increases and other terms for affected customers during such a challenging time. Eric will walk through what that means for 2026 in a moment, but we remain confident that headwinds are cyclical while the tailwinds are secular.

Now turning to Market Intelligence. As we announced on July 6, we have created a new business structure for Market Intelligence with new leadership already on the ground running. We continue to see rapid changes in the technology landscape and in the ways our customers want to interact with our data. So we are refining our strategy and go-to-market motion to make sure we're best positioned for the future. Within Market Intelligence, we'll be reporting 2 business lines: Kensho Data and Platforms and Enterprise Solutions. Kensho Data consists of our data feeds, Kensho LLM APIs, RatingsXpress and our vast estate of proprietary data.

The Kensho data component is roughly half the size of platforms by revenue but is growing in the high single-digit to low double-digit range on an organic basis. The platform's component includes Cap IQ, Consulting, Issuer Solutions, RatingsDirect, Visible Alpha and With Intelligence. Platforms is the larger component of the business line and in aggregate is growing low single digits on an organic basis. Our strategic focus in Kensho data will be to deliver our differentiated and proprietary data in a channel agnostic way, accelerating revenue growth at strong incremental margins. Our focus in platforms will be to consolidate redundant platforms, leverage a more unified technology infrastructure across products and simplify operations while still growing revenue.

We will maintain a high standard for innovation and customer value to increase our efforts to leverage AI and traditional productivity measures to improve profitability. The other business line in With Intelligence is enterprise solutions. Enterprise Solutions includes our entire lending solution suite, ClearPar, Debtdomain, Pricing and Reference Data, Notice Manager and WFO. The Lending Solutions suite benefits from deeply connected data flows as well as strong network effects.

Enterprise solutions also includes iLEVEL, bookbuilding software for fixed income and equity origination and valuation services. These are important market-leading franchises that the markets depend on in order to function. In Market Intelligence, we have an incredible library of proprietary data and powerful workflow tools. We will emphasize those areas where S&P Global has a clear right to win. We are seeing customer buying behavior mature and evolve. Vendor consolidation continues to be a tailwind for our business, and we are beginning to see customers more rigorously evaluating AI budgets to prioritize those solutions that truly create positive ROI.

Across the board, we want to align our priorities with those of our customers. We will be focused on the highest quality assets in MI and on the highest growth opportunities. We will make more and more of our global data estate AI ready by scaling our enterprise data fabric. We will look to fund these investments primarily out of productivity and AI-driven cost savings to ensure meaningful margin expansion. From a capital standpoint, small carve-outs are possible in the near term, but there remains no real appetite for transformational M&A.

The simplified structure and clear objectives we've discussed today will better position Market Intelligence to serve customers in the future and drive long-term profitable growth. Now let me turn to the exciting progress we're making in artificial intelligence. As we shared with you last quarter, our customers leveraging our AI solutions are growing much faster than average. That [ gap remains ] in the second quarter for both Market Intelligence and Energy. ACV growth in MI is now 60% faster in MI for AI customers and is approximately 3x in energy.

The demand signal from customers is incredibly strong. We continue to rapidly add customers to our LLM ready APIs at MCP connected solutions, with that number now sitting above 500 and increasing more than 70% quarter-over-quarter. API call volume continues to grow rapidly as well, showing that our customers are finding real value in these powerful solutions.

Call volume for our LLM ready API in the second quarter was more than 5x the volume we saw in the first quarter. Internally, the EDO has achieved nearly 60% of its targeted $100 million in annualized cost savings through a combination of AI-driven efficiencies and traditional productivity initiatives. We are on track to deliver the full $100 million or roughly 20% of the EDO cost base before the end of 2027, even as our AI solutions are seeing great demand. We are hearing more and more from customers that they are paying more attention to token costs and the overall expense of their own AI investments. Customers are looking for ways to minimize or manage token expenses, including building solutions in-house.

Those customers want to build with S&P Global and with Kensho Labs. Over time, we believe that our AI offerings will create meaningful value to our customers without creating exorbitant costs. Overall, we are pleased with the performance of the business in the second quarter. We once again demonstrated the power and resilience of our benchmarks businesses while making meaningful progress on strategic growth initiatives across the board. We are energized by the opportunities and new leadership in Market Intelligence, and look forward to delivering a strong second half.

With that, I'll hand it over to Eric to walk through the quarter's financial results and the guidance.

Thank you, Martina, and good morning, everyone. Starting with Slide 15, we delivered another quarter of strong financial results, including 11% revenue growth and 23% growth in adjusted diluted EPS. Our second quarter performance underscores the power of our benchmark businesses, which grew revenues 15% year-over-year on back of excellent performance in Ratings and Indices. Revenue grew 11% in both in organic constant currency and all-in basis as M&A and FX had only modest net impacts. .

Adjusted expenses increased 6%. We tightened our spending with the start of the Iran conflict amid heightened volatility and macroeconomic risk. This discipline, along with our ongoing productivity savings carried through into the second quarter enabled us to deliver 200 basis points of year-on-year margin expansion to 54.3% and a 15% growth in adjusted operating profit.

Excluding OSTTRA from the prior year period, our second quarter 2026 margin expansion would have been 270 basis points. Finally, adjusted operating profit was up 15%, and our robust return of capital to shareholders through buybacks helped drive EPS further up 23%. Turning to our divisions with Slide 16.

This quarter, Ratings reported a record quarter by revenue, which increased 17% year-over-year. We exceeded our internal expectations for both the quarter and for the first half of the year. Issuance in the quarter benefited from tighter spreads and favorable market conditions, though growth was also elevated due to a fairly soft compare in the year ago period, driven by last year's tariff uncertainty.

Transaction revenue increased 25%, partly driven by high 20% growth in investment grade supported by tech infrastructure and hyperscale issuance and M&A transactions in the second quarter. We also benefited from double-digit revenue growth in bank loans, high-yield and structured finance. Private Markets Ratings revenue increased 60% year-over-year. Nontransaction revenue grew 8% driven primarily by higher annual fee revenue, very strong growth in Ratings Evaluation Services or RES and CRISIL revenue.

Adjusted expenses increased by 6% reflecting higher compensation costs and continued strategic investments in our people, technology and product development, partially offset by productivity. With a high fixed cost, low variable cost model that we have in Ratings top line outperformance continues to benefit margins, evidenced by the division's 310 basis points of expansion to 68.5%.

Now turning to S&P Dow Jones Indices on Slide 17. The Indices reported its 13th consecutive record quarter for revenue and the division surpassed $2 billion of revenue on a trailing 12-month basis. Revenue in the quarter grew 20% with excellent growth in both asset-linked fees and exchange traded derivatives. Revenues associated with asset-linked fees had their fourth consecutive record quarter.

We delivered 22% growth year-over-year driven by equity market appreciation and net inflows into products based on S&P Dow Jones indices. Notably, we have our best quarter of net inflows on record. S&P Dow Jones Indices operates the world's largest index business by AUM. And as Martina mentioned, we have built a franchise on trust and discipline. That reputation was recognized again this quarter, and we're pleased to see that 4 of the 5 ETFs selected by the U.S. Treasury for inclusion in Trump accounts were linked to S&P Dow Jones Indices.

Exchange-traded derivatives revenue grew 22%, driven by strong volumes, particularly in SPX. Data & custom subscriptions increased 9%, primarily driven by new business growth in end-of-day contracts. Adjusted expenses were up 16% year-over-year, driven by investments in growth initiatives and higher compensation costs. Indices operating profit grew 21% and operating margin expanded 90 basis points to 71.5%.

Now turning to S&P Global Energy on Slide 18. Energy revenue grew 3% amid pressure from the challenging environment as well as the sanctions we have called out in recent quarters. The conflict in the Middle East led to continued volatility and uncertainty in the quarter. While the business remains resilient, the Iran conflict, tariffs and extreme volatility have put some strain on energy subscription renewals, onetime sales and Global Trading Services or GTS, as Martina mentioned.

We believe these headwinds are transitory, however, and we expect growth to normalize after this year, back to the 6% to 8% average range we outlined at our Investor Day. As we discussed last quarter, we continue to see our customers turn to S&P Global for the data and insights that only we can provide, with our best-in-class data and the recent consolidation of our supply chain assets into energy, we are in an excellent position to equip our customers with the data and intelligence they need to adjust and remap their supply chains.

CERA grew 1% due to strong growth in Market Insights and Analytics, largely offset by declines in upstream and conference and training revenue. Conference revenue was pressured by headwinds from the lower event attendance due to the Middle East conflict. We are pleased by continued progress in the various aspects of our upstream data transformation. Platts revenue grew 4% in the quarter, driven by strong growth in price assessments as demand for our benchmarks remain resilient. This was partially offset by declines in GTS. While higher volatility is usually a positive for GTS revenue growth, extreme energy volatility like we saw in the second quarter, can actually have a dampening effect on the market.

We saw this dynamic in the second quarter. The sanctions we discussed last year had 120 basis points negative impact to Platts and a 30 basis point negative impact to CERA growth in the second quarter. Adjusted expenses grew by only 1%. Our teams remain disciplined through the quarter to support profitable growth during a volatile time period. The 1% expense growth we realized was driven by higher compensation costs and ongoing investments in growth initiatives, almost fully offset by productivity programs and careful expense management.

Second quarter margins still expanded by 70 basis points to 47.5% even in this environment. Turning to Market Intelligence on Slide 19. On both the reported and organic constant currency basis, revenue grew 6% in the second quarter. We continue to deliver solid growth in Market Intelligence, supported by the ongoing vendor consolidation trend, momentum in key strategic areas, particularly our AI solutions and Kensho LLM APIs and improving capital markets activity.

As Martina noted, this has been partially offset by some softness in pockets of Market Intelligence as well as longer renewal cycles with some of our larger, more sophisticated clients. In Market Intelligence, we have some mature platforms that have a strong customer base with stable growth and potential for meaningful margin expansion. We also have high-growth products like Visible Alpha and our Data Feeds business, that continue to benefit from favorable market positions and their proprietary nature.

We've also identified a few smaller products that are facing headwinds and negatively impacting the growth of the division. As Martina mentioned, we will be prioritizing our investments going forward in favor of our highest growth opportunities, ultimately striving to maximize long-term shareholder value. In the second quarter, subscription revenue increased a solid 6% on both a reported and organic basis, benefiting from growth across the subscription franchises and benefiting from some upfront revenue from a 10-year renewal in the quarter.

Volume-driven revenue increased by 9% with growth in market linked revenue and corporate actions and the primary markets group as well as usage-based revenue in ClearPar. Onetime revenue declined 2% in the quarter, primarily due to declines in the consulting and Sustainable1 revenue. Kensho Data and Platform revenue increased by 8%, driven by Kensho Data and the With Intelligence acquisition as well as 4% organic growth driven by data management solutions, RatingsExpress, Capital IQ Pro and Visible Alpha. Enterprise Solutions revenue grew 3%, reflecting the divestiture of EDM and thinkFolio. The business grew 10% organically, driven by data valuations and risk analytics, including financial risk analytics, lending solutions and the primary markets group.

Market Intelligence's adjusted expenses increased 4% year-over-year, driven by expenses from the With Intelligence acquisition as well as compensation expense and long-term strategic investments, partially offset by the impact from recent divestures and productivity programs. More Intelligence delivered 120 basis points of operating margin expansion to 36% in the quarter.

Now shifting to our outlook starting with Slide 20. With our spin of Mobility Global completed on July 1, we are introducing our guidance for GAAP results. As a reminder, when we report third quarter as well as the fourth quarter and full year, mobility will have moved to discontinued operations. As such, our full year guidance on both GAAP and adjusted basis now excludes the contributions from Mobility for the whole year.

Slide 20 outlines our GAAP guidance. Slide 21 shows our adjusted guidance. For the reasons I just mentioned, the consolidated guidance we are giving today is not directly comparable to the adjusted guidance we had issued previously, which assumed a full year contribution from Mobility. For all material purposes, however, our division guidance is comparable to prior guidance. On a consolidated basis, we expect organic constant currency revenue growth in the range of 6% to 8%. And our prior guidance, including Mobility, also called for 6% to 8% growth, but we have offsetting items.

As you will recall, our Mobility business has historically had a higher revenue growth than the business overall, but with modestly lower margins. As such, excluding that revenue causes the overall revenue growth of the business to come down slightly, all else equal, but margins to improve. The outperformance Of Ratings and indices this year is enough to offset that impact, so we expect our overall growth to be in the same range. Ratings and Indices also have the highest incremental margin across our 4 divisions. We are reinvesting some of that upside in the second half, but we do expect margins to expand more than we had originally anticipated this year.

We now expect consolidated margin ex OSTTRA to expand 75 to 100 basis points this year. Strong revenue growth, additional margin expansion and the additional buybacks I'll discuss in a moment, allow us to deliver faster EPS growth as well. We expect adjusted EPS in the range of $17.50 to $17.75 representing double-digit growth across the entire guidance range. For adjusted free cash flow, the Mobility Spin creates some nuance.

In the first half of the year, including Mobility, the company generated $2.4 billion in adjusted free cash flow. In the second half of the year, excluding Mobility, we expect to generate adjusted free cash flow in the range of $2.9 billion to $3.1 billion. Seasonality typically drives higher free cash flow in the second half of the year.

Now turning to our division guidance on Slide 22. Guidance is based on recast financials, which reflect a movement of 451 Research in Maritime and Trade from Market Intelligence to Energy in all periods. These products are fairly small in aggregate, so our division revenue growth guidance is comparable to prior guidance for all material purposes. For Ratings, we now expect revenue growth in the range of 5% to 8%, up 1 percentage point from the prior guide.

Indices is expected to grow revenue in the range of 12% to 14%, up 2 percentage points from the prior guide. Our guidance for Market Intelligence and Energy is unchanged from the prior guidance with Market Intelligence expected to grow in the range of 5.5% to 7% and Energy in the range of 4.5% to 6%. Lastly, as Martina mentioned, we are once again increasing the expected share repurchase for the year. As you may have seen, we received approximately $2 billion in a dividend from Mobility Global upon the completion of the spin. These proceeds will be used primarily for the purchase of shares with about $500 million for some debt retirement.

In the second half, we expect to issue approximately $2 billion in additional debt to fund further buybacks with timing dependent on market conditions. We expect to end 2026 with gross leverage of approximately 2.7x to 2.8x EBITDA modestly above our target leverage range of 2.0x to 2.5x. We expect natural deleveraging over the course of 2027 as our EBITDA continues to grow and would expect to be back in the target leverage range by the end of next year.

In aggregate, this means we expect to repurchase over $7 billion in shares this year, representing more than 5% of our total market capitalization at the current share price. With that, let me turn the call back over to Mark for the questions.

[Operator Instructions] Operator, we will now take the first question. .

Our first question comes from Faiza Alwy with Deutsche Bank.

I wanted to ask about the Kensho data and platforms business. I guess, as you focus more on the Kensho data side of the business, and maybe lose the distribution and interface layer in some cases. Give us some context on how your thoughts have evolved around future pricing and AI monetization, especially if your clients are able to approach data acquisition in a more modular way and kind of limit some of the data source of.

Faiza, it's Martina here. Thanks much for the question. Maybe I would start with just one thing that didn't change about our organization announcement and that is that we maintain the direct relationships with the customers. So our contracts are directly with customers. And then consistent with our flexible delivery strategy, we will continue to distribute our content, whether it is through our own platforms through third parties and through our traditional feeds distribution channels.

Maybe 1 point I would make about the role of Kensho coming into Market Intelligence is that it is an acceleration and an amplification of what Kensho has been doing so brilliantly when it wasn't aligned with Mark Intelligence. So for example, the team will continue to work with the MI team even more closely on development of very innovative capabilities. We have great building blocks here. We started with the LLM ready APIs. We moved on to the adaptive retrieval that you saw us announce this week, and we are making great progress with MCP applications.

And so we'll continue that. The team will work closely as well with the platform team to continue to implement those great capabilities on the desktop as well. And I would say that the other thing that's really great about having the teams together is that Kensho Labs, which we launched last year has really gotten tremendous momentum and traction and has been a true differentiator for us as we've been having these AI use case conversations and bringing that really close together with the business being very close to the MI commercial team, these are ways in which we think we can really scale the impact of Kensho Labs. Eric, do you want to talk about monetization?

The monetization approach is multifaceted. First, what you what we'll continue to see is just a dramatic uptick in data usage by our clients through their AI calls. The MCP connectors are up to 500 clients. Data usage is up 5x relative to the prior quarter and the prior quarter was up 5x prior to that. And so there's a series of ongoing discussions that we have with clients to how do we economically share in that. They get enormous benefits. And really, it's a mix of some consumption pricing, some additional data set pricing. And we feel quite comfortable that the revenues are beginning to come through and with -- along with higher retention, higher sales and so forth, bode well for our businesses.

Our next question comes from Manav Patnaik with Barclays.

Martina, thank you for rehashing kind of the strategy upfront in the call. Clearly, it sounds like, especially in MI and energy, you're still refining the strategy in kind of how you want the segments to look. So I'm just curious, usually, in that situation, we get more disclosure by segment as opposed to kind of consolidating some of the stuff that you did. So does that imply that you're still trying to reevaluate exactly how those businesses might look with all the different components or just give you some of your thoughts there.

Manav, thanks for the question. I would say that what we're aiming for here is simplification in MI and in Energy, the strategies for both divisions have not changed. This is really about how I think about it as basically wrapping ourselves more closely around our customers as well as getting the teams who are operating very similar platforms, for example, in MI, an opportunity to move more quickly and grow more profitably by being able to sort of develop the capability once and use it many times.

And so this is really about stronger and more efficient execution against the strategy. In energy, for example, look, we just see such a tremendous opportunity in Energy in the trillions of dollars that are being spent in AI infrastructure, in the power grids that are required to support that AI infrastructure. And we are executing the changes that we have to enable our clients to get more clarity on the supply chains, they need to develop that infrastructure as well as the forecasting models whether it's supply chains or even with data centers that we'll be able to offer. And so no change in strategy, but I would say more closely wrapping ourselves around the clients as we move forward. Thanks for the question.

Our next question comes from Surinder Thind with Jefferies.

Eric, I guess when we think about the margin expansion that we're seeing at this point, how are you thinking about balancing that against the opportunity to maybe accelerate investment and the trade-off? Like can you do a lot more? Or are you kind of at the level that you see reasonable for what you can kind of, I guess, absorb what clients can obsorb in the current environment.

Surinder, it's Eric. We see quite a bit of opportunity with our clients. We have our core clients in the financial institutions area. We continue to expand to across corporate clients, part of the alignment of our supply chain businesses are for that effect to kind of widen the base of clients that we serve and continue to develop new and refreshed and updated in some cases, leading-edge products for them. .

All that is consistently and relatively easily funded by productivity. You've seen us describe productivity in the EDO. We've got productivity programs that I referenced in MI, in Energy and Ratings and Indices. And every one of those frees up resources, whether they're people or technology or other or otherwise to reinvest and build those new products and services. And so it's quite a virtuous circle and cycle and allows us to continue to grow as we'd like to do.

Our next question comes from Toni Kaplan with Morgan Stanley.

I wanted to go back to MI to talk about a little more about the reorganization. Should we expect any disruption from the realignment? And you talked about some parts of the portfolio facing headwinds. Are you able to cumulatively size them? And would we expect that you look to sell those or divest those? Or are you going to try to fix those areas?

Toni, it's Martina. Thanks for the question. From an MI perspective, I don't expect disruption, if anything, I expect greater simplicity and continuity in how we're doing things. So I'll give you a couple of examples. We moved the Pricing and Reference Data into Enterprise Solutions, and that really simplifies our go-to-market around private markets. The Pricing and Reference Data is very closely aligned with the lending suite that we have there as is the valuation service that we offer.

Another example would be the great progress that we've made with Kensho Labs that was really in partnership with the CCO, and we see such an opportunity here to extend that to more of the clients. And so that's one major part of the rationale for bringing the Kensho team that we've selected into the Martin division and having the Kensho data vertical stood up essentially. And that really brings that innovation from the Kensho team very, very close, in fact, much closer to customers also.

So I think I would look at this as coming from a position of strength and allowing ourselves to really unlock the full value of our products and our data. The other point to make here is with respect to the [ software ] products. These are smaller products, subscale, some consulting services, for example, some of the sustainability products. We're not talking about our strategic products like WSO or ClearPar for example and where there are cases where we may see cyclical impacts and growth could come back in those products, we're going to watch that very closely, and there may be opportunities otherwise if we don't see growth coming back, and we may think that we have to invest a little bit more, we may make some strategic choices there. But overall, this is coming from a position of strength and in a way that allows us to operate much more effectively around the customer.

Our next question comes from Curt Nagle with Bank of America.

Great. Just 1 quick 1 for me. I think, Martina, you mentioned that you're seeing some long-dated sales cycles, some of your largest -- for your clients. Maybe just unpack that, what's driving it? Maybe what changed? Is it environment? Or just what's behind that comment?

Thanks much for the question. Look, we view it actually as a positive because it means that our clients want to do more with us. And as we've been going through these renewal cycles, we're having quite substantial conversations around use of AI and use of our IP and data for AI. And the conversations are getting a little bit complex in some cases, and that's because we are absolutely intent and focused on protecting our IP over the long term.

And so we've seen some elongation as a result of that. I look at it as more of a sort of a baselining with our customers around the terms and conditions that we're putting forward. And this is something that's more of a sort of a near-term impact, not something that's going to impact us over the medium or long term. Thanks for the question.

Our next question comes from Alex Kramm with UBS.

I actually want to ask about the Index business and just maybe a little bit in the weeds [ in detail ], so bear with me. But you have that licensing relationship with CBOE. And by my numbers, this is definitely more than $200 million a year. And there's been more investor concerns around, more from their side about that renewal that's coming up in a few years.

Now just wondering what your latest thoughts are on this because, again, if you look at the relationship, some people would suggest that you can probably double those fees. So that could be nicely material and accretive to your business. So just wondering, how do you think about that relationship other exchanges have actually wondered about getting that license from you. So maybe talk about it, if you could give it to multiple exchanges or maybe shop it around because again, it could actually be nicely accretive to your bottom line.

Alex, it's Martina. Thanks for the question. Look, we don't comment on our partners or the conversations that we would have with any of our partners. But thank you for the question.

Our next question comes from Scott Wurtzel with Wolfe Research.

Just wondering if you can talk about just the overall ACV bookings growth within Market Intelligence during the quarter and then building off of that, how you feel about the trajectory of those [indiscernible] heading into the back half of the year.

Scott, it's Eric. We feel like we delivered solid revenue growth in MI this quarter, 6% OCC revenue growth, 6% subscription revenue growth. ACV was also in that 6% range. And so we continue to do well. We had a good first quarter, a good second quarter, we have every intention delivering on our guide for the full year and continue to build from there.

Our next question comes from George Tong with Goldman Sachs.

Can you elaborate on trends that you're seeing in private markets across the company? And how much private markets contributed to revenue growth in both Ratings and Market Intelligence?

George, it's Eric. We've had quite a bit of success in private markets as you've seen in the underlying numbers in our prepared remarks. In Ratings, we described it as 60% up, which is quite strong and continues an area of strength and something that we expect to continue in the coming quarters and coming years. And then in MI, we're particularly well positioned as we integrate With Intelligence. We've seen very strong growth across the board, both in the acquisition and in our core business and expect that to continue. And so this is really an area that we've built around, and we expect to continue to grow organically and really lead the industry in.

And George, I would just add 2 points to that. The first is that we still see really good momentum in AUM inflows into private market funds. And that demonstrates a continued appetite from investors [ for closure ] to the asset class. And then maybe the second point that I would make is that notwithstanding all of the noise that we've heard in the media and otherwise around private markets, our view and in fact, our experience and what we're seeing is that this actually increases the demand for transparency, whether it's through benchmarks or data and analytics.

Our next question comes from Ashish Sabadra with RBC Capital Markets.

I was just wondering if you could talk about the puts and takes on issuances in the back half of the year? Any thoughts around how you think about issuance in 3Q versus 4Q and the same thing on your Rating revenues?

Ashish, it's Eric. It's really a continuation of what we've seen in the first half of the year. We've seen M&A activity pick up, and that's been tailwind. We've seen hyperscaler issuance. You've seen us book a very significant billed issuance in the first half. We expect a good amount in the second half. We've seen some refinancings come through, notwithstanding the change in the rate environment, and we expect that to continue. All that said, we just see very strong refinancing walls in the coming years. And we see a strong trajectory in the business. The one thing I will note is that the year-on-year compares in the individual quarters in the second half of this year will be lower just because last year started low and ended high. So you'll just have a patterning there, but the sheer volume of issuances and revenues on a per quarter basis continue to move along strongly during the year.

Our next question comes from Jeffrey Silber with BMO Capital Markets.

Just to continue the thought from the last question, let me just play devil's advocate here. The market seems to be pushing back on some of the hyperscalers in terms of the amount of cap spending that they might be doing, are you expecting any potential slowdown from debt issuance because of that? And also, if we do see interest rates going up, would you be expecting the same thing?

Jeff, it's Martina. Let me take that question. So maybe a couple of things. The first is when we came to you earlier this year with the full year assessment, we said, look, we look at the announced CapEx, and we discount that for what we think will get debt financed and then we make assumptions around that as well. And so we're already tracking well ahead of where we thought we would be for the full year through the first half.

But we've also said to you that our range is about [ $250 million to $300 million ] for the full year, which basically says not too much more hyperscale issuance relative to the first half and the back half of the year. Now that being said, we are always prudent and thoughtful about how we think about the issuance in areas like this. And from our perspective, we've seen that the market continues to absorb these types of deals, and we've also seen the hyperscalers do many different types of structures, including issuing outside of the U.S. as well where there may be additional appetite.

So all in all, I would say we have taken a very prudent look at the rest of the year for hyperscale issuance.

Jeff, it's Eric. I'd just add that we obviously have a guidance range for the full year, and it's got some width to it, and that's because of some of the factors you mentioned, the global economy, the conflicts in the Middle East, interest rate levels may move credit spreads may widen or stay where they are. And so there's a range there, and I just want to absolutely be conscious of that. Notwithstanding that, we continue to focus on execution and managing and working on what we can control.

Our next question comes from Craig Huber with Huber Research Partners.

I just wanted to focus, if you could, please, on how AI is benefiting you on the efficiency side of the cost side of your business within Market Intelligence. Can you quantify a little bit further within that division, how much it might be helping on an annualized basis and how that may help you long term to increase margins in that division.

Craig, it's Eric. There's actually a wide range of positive productivity effects and programs that we've had in MI. But we've also had them in -- across the various divisions. I think the earliest one was around our EDO, our enterprise data office, which is primary provider of data through MI in there. We're on track to deliver 20% productivity gains on a base of $0.5 billion. So you can just see the kind of scale at which we operate. More recently, we've begun to roll out programs around software development life cycles, moving into product development life cycles that we see as quite an opportunity in energy, we've focused on researchers and the researching process.

And we've actually found that, that actually has parallel benefits in MI and then actually in Ratings with the analytical groups. And so there's quite a bit of areas and tooling that we've been able to put in place. And that's why we see the margin guidance being as it is why we expanded it, to be honest, this year because we've accelerated some of those efforts, and we expect that productivity gain from AI and more broadly from our other programs. We'll continue to build in the coming years, lead to more reinvestment and thus deliver on the growth that we'd like to deliver on.

our next question comes from Andrew Steinerman with JPMorgan.

On GTS and Energy, I feel like we don't hear that much about it. You obviously mentioned it today because of end market volatility. So just tell us a little bit more about how GTS revenues are impacted by volatility. And then this is a very small technical point. I thought I heard you say that again, within Energy, the [ upstream ] software business, the divestiture is now in your guide. Is that the case? And is that new?

Andrew, it's Eric. Thanks for the questions. On GTS, GTS, Global Transaction Services business is really one that monetizes revenues as energy prices and trading activity accelerates or decelerates as we find what you typically see as volatility increases, you get more trading. And then at some point, if there's heightened volatility, folks pull back and still on the sidelines and tend to not trade as much. And that's what -- how that plays out.

In terms of upstream, we now have we can see the likely close of the Upstream software division in the -- during the third quarter. And so at this point, we've tried to give you the -- we've updated the guide on an OCC basis with that in mind, just that you could track our performance and allow us at the same time to focus on organic constant currency growth, which really is what -- which really is our focus.

Our next question comes from David Motemaden with Evercore ISI.

Just had a question on the Market Intelligence subscription revenue growth. Eric, I believe you called out some upfront revenue from a 10-year renewal that benefited this quarter. I was wondering if you could size how much that helped the MI subscription revenue growth. And then just how you're feeling on that building from that level throughout the rest of the year.

Subscription revenue growth. And saw a good performance in the 6% range, the first 2 quarters in a row in MI, and obviously, we track that in our other divisions as well, with growth would have been slightly lower had not been for that software renewal. But if you remember, there's always going to be lumpiness in software renewals. And what's particularly striking in this case, we have a client who wanted to have a 10-year contract, right, not a 3-year, not a 5-year, but a 10-year contract.

And it gives you a sense of how valuable and institutionally important our software products are for our clients and bodes well for our progress. And then in terms of the full year, I think our guide is in a good place. We feel comfortable with it. We felt comfortable with it at the beginning of the year. We're now midyear we feel comfortable with it, and we continue to plan on executing against that.

Our next question comes from Jeff Meuler with Baird.

I'd be curious on your views on how MCP adoption will impact the trend toward vendor consolidation, you're describing it as an ongoing trend. I think you're well positioned with proprietary content either way. But I would think clients having an AI interface on their end may make it easier to leverage data feeds for multiple vendors. So just if you could help me with that.

Jeff, it's Martina. Maybe just to start on this one. Look, I would say this is very much for us, one of the reasons why we laid out our strategy as being one of flexible distribution. Firstly, we benefit tremendously from the demand for our proprietary content and our data, which, in aggregate, is quite unique relative to any other player in the market. And for that reason, we are in a great position to take advantage of better consolidation opportunities.

Maybe a couple of deals that I would highlight in the quarter. One was a very large strategic deal where we did a renewal for desktop feeds, Visible Alpha and AI-ready data and that actually resulted in an over 20% uptick over several years. And so we were incredibly pleased with that because the positioning of our products was really alongside that large firms own internal AI systems that they had developed as well as third parties that they are using.

So that's one example. I would say also, look, the MCP applications, the MCP servers, these are all building blocks that help us with additional opportunities for increasing revenues in our data area. So think about the building block starting with LLM ready AI that allows our customers to do more structured Q&A or prompting against our data, one data set at a time. The latest adaptive retrieval product that we launched was previously known as Kensho Grounding, and that allows our customers to really ask very complex questions and set multistep tasks with the grounding agent and allows our customers to do a whole lot more across a multitude of our data sets.

And then with our MCP applications, we decompose parts of our desktop and allow our clients to basically render those capabilities within their own systems or third-party systems. And we're getting incredible feedback on all of these. I think what's really encouraging with us is that we're seeing net new licensing opportunities with our existing clients. But we're also seeing new clients come to us. So about 15% of the clients that are licensed for our LLM ready APIs, for example, are actually net new clients or clients that are returning to S&P that had previously been clients with us.

So we see this as an incredible opportunity across the board, whether it's clients who want us to invest further in our traditional areas or want to do more business with us and buy more data sets with us through NCPs and other new distribution channels.

Our next question comes from Christian Bolu with Autonomous Research.

I had a question really on AI infrastructure. It's clearly a major theme across capital markets. So can you talk through long-term strategy for compute and data center infrastructure as an asset class. And as you think about commercializing compute benchmarks, how are you thinking through building that through the S&P Dow Jones JV, where you already have CME as a partner in compute futures?

Christian, it's Martin. Thanks much for the question. I think part of this, we addressed a little earlier in the call with the questions around hyperscale issuance, for example, with data centers and AI infrastructure as an asset class in Ratings. And there, as we've said, we don't have heroic assumptions for the balance of the year around that.

And you're right, there probably are some really interesting opportunities, for us in aggregate with compute and data center from an index or a benchmark perspective. This indeed is one of the reasons why we announced the acquisition of datacenterHawk today, for example, that combines on the datacenterHawk side, a very specific proprietary data center intelligence, including pricing, supply chain, site selection and details like that with the world-leading forecasting models that we have in 451 Research. And so look, we will be paying attention to how demand is evolving for benchmarks in this area, it's very nascent, and it's something that we feel we can add some value to for investors.

Thanks for the question.

Our next question comes from Jason Haas with Wells Fargo.

On the 1Q call, you said that you were expecting an acceleration in MI subscription growth. And it doesn't like it showed up this quarter. So I'm just curious, what was the reason why? And are you expecting that MI subscription growth to accelerate in future quarters?

Jason, it's Eric. As we covered in some of our prepared remarks, we've had solid performance in MI. We did have a couple of small products that are lagging consulting, sustainability that we called out. And so those tend to have some impact on results. I think in general, we're pleased with what we've seen in terms of execution, whether it's OCC. Revenue growth in MI was at 6%. Subscription was at 6%, net retention rates are -- continue to tick up.

And then with all that, we've seen very good expense discipline and productivity programs, which has helped us deliver double-digit earnings growth through the first half of the year, and so we just see the strong execution performance delivering. And then as we continue to refine with Kensho data and platforms and so forth, that over time will help support and deliver on the growth.

But for now, we're comfortable with our guide for the year that we started with and are on track to deliver on that.

And Jason, maybe just a final point for me on that. Look, you've seen us be very disciplined stewards of the portfolio in the past in MI, and we're going to continue to do that going forward as well. This is going to be something that we'll consider if we see opportunities where subscale products will create greater value outside of our portfolio. Thanks for the question.

Our next question comes from Sean Kennedy with Mizuho.

So in Ratings, for your M&A related issuance outlook, I believe you said up double digits for the year. I was wondering how M&A-related issuance have progressed so far this year and how you're thinking about growth in the second half and any visibility there?

Sean, thanks for the question. We've seen quite a healthy pipeline from an M&A perspective. And obviously, there have been some very large deals announced in the market. But the M&A we've seen actually really spans across multiple sectors. It's not necessarily focused in one sector, and we think thematically that continues through the year which is why we have mentioned double-digit growth expectation for the full year. Thanks for the question.

We will now take our final question from Owen Lau with Clear Street.

I want to go back to private market. Could you please add more color on like new products and potential capitalists in this area. I mean if you look at company valuation, it's not low. And you also mentioned AUM flowing into private markets also go up, it doesn't look like the activity actually slowed down there, but it just appears that it's hard to find a good way to monetize it or expand the revenue contribution more. What does it take to change that trajectory?

Owen, it's Martina. Thanks for the question. We mentioned that last year we saw a base of about $600 million in private markets revenues across the organization. So for us, it's a quite healthy base. And we've seen very strong growth across the organization in private markets driven by Ratings. And so maybe a couple of points I would make. First, in addition to the influence, what that essentially does is create a greater appetite for transparency for information, for benchmarks.

So we've seen lots of product launches within Index, for example, the team has launched with Lincoln, some private credit indices as well as broader private markets indices covering the S&P top 50 private stocks, for example. We've also seen incredible innovation across the Market Intelligence team, including the partnership that we have with Cambridge Associates and Mercer, where the teams have launched several data sets into the market map to the new taxonomy as well as map to our market-leading LoanX IDs. And so these are just some examples of how we're monetizing and growing in this space, and we continue to be very constructive about private markets opportunities going forward.

Thanks for the question.

Well, in closing, we've had a strong second quarter with record level performance in 2 of our benchmark businesses, the launch of Mobility Global and really growing traction in our AI-enabled client solutions. None of this will be possible, of course, without the talent and dedication of our people. Our mission of advancing Essential Intelligence continues to be highly relevant for our clients, and I'm confident we remain well positioned to deliver long-term value. Thank you for joining the call today.

That concludes this morning's call. A PDF version of the presenter slides is available for downloading from investor.spglobal.com. The replays of the entire call will be available in about 2 hours. The webcast with audio and slides will be maintained on S&P Global's website for 1 year. The audio-only telephone replay will be maintained for 1 month. On behalf of S&P Global, we thank you for participating and wish you a good day.

Hello, everyone, and welcome to today's webinar. My name is Sarah James, and I lead the Tech, Media & Telecoms News team at S&P Global Market Intelligence. I'm thrilled to be your moderator for today's session titled GenAI Fundraising From Private Rounds to Public Markets.

Today, we are going to talk about both the record amount of fundraising we saw in the first half of 2026 and why GenAI companies are now turning their eyes to public markets. Before we dive in, I have a few housekeeping reminders. All engagement tools are resizable and movable, so feel free to adjust them for optimal viewing on your monitor. We want this to be an interactive session. While we may not be in the same room, your participation is key to making this experience engaging.

We encourage you to submit your questions throughout the presentation. [Operator Instructions]

If you're joining us for the replay, please use the request demo link found under the related content widget to reach out to us. This widget also includes links to our thought leadership resources. You can also access our webinar replay portal to revisit the session and others on demand.

This webinar features close captioning in English. To activate it, simply click the CC icon in the media player. And at the conclusion of the session, a brief survey will appear. Completing it takes less than a minute and your feedback is invaluable to us. It helps us understand what aspects of the webinar you found engaging, identify areas for improvement and gather suggestions for topics we'd like to cover in future sessions.

Now please note that the activities of S&P Global Market Intelligence are independent and separate from S&P Global Ratings. S&P Global Ratings maintains a separation of analytical and commercial activities. Thank you for joining us today.

So this webinar will begin with a brief presentation from my colleague, luri Struta, who covers capital markets and M&A in the tech space here at S&P Global Market Intelligence. He'll be walking us through his research into the funding we have seen thus far this year for GenAI. After his presentation, we'll hear from Melissa Otto, Head of Visible Alpha Research at S&P Global Market Intelligence, about the financial metrics that are supporting these funding trends and why these funding trends are or are not likely to continue.

Then, we'll move straight into a panel discussion with our guest speaker, Shari Mager, National Capital Markets Leader & Partner at KPMG. And she will also be taking your questions. So without further ado, Iuri, can you get us started?

Actually, before we begin, let me ask -- we're going to start off with a brief poll. How do you expect your organization's budget for AI initiatives to change over the next 12 months? Do you expect them to significantly increase, remain about the same, decrease or significantly decrease? And just take a second to answer the poll. And then we will begin with our presentation with Iuri, giving us his overview. And just waiting for some answers to come in, usually takes about 15 seconds.

Interesting. So we've got -- it looks like everybody is expecting their organization's AI budget to either increase or significantly increase and then about 1/3 or a little less than 1/3 to remain about the same. All right. Iuri, do you want to take it away?

Thanks, Sarah. And great to see that AI spending is growing. So yes, I'm going to -- we have a dense presentation and I'd like to go through it quickly, and then I'll hand it over to my colleague, Melissa. So here is a quick rundown of the entire AI value chain of basically how we see it and what we consider to be an AI company from chip makers to the application layer.

And broadly, we have AI applications, which include foundational models and end user application and then AI infrastructure, which includes the chip makers, cloud infrastructure like neoclouds and the software tools to build, implement, test secure AI and so on. So if we are going to the next slide. So we can see funding for GenAI companies has already shattered last year's record. Q1 was the strongest ever with more than $140 billion raised from private markets. And Q2 was the second best ever quarter.

And these numbers, they are largely due to a massive concentration of funding into top-tier foundation model providers like those provided by OpenAI and Anthropic. But we believe this is very likely to be the peak in transaction value for GenAI in private markets at least for a period because we think a lot of these companies -- a lot of these companies have already put to test private markets in terms of how much they can raise and now are increasingly seeking to move their fundraising activity to public markets, which we're going to discuss in more details in the panel.

And why we believe that? Also, if we are looking at the GenAI infrastructure, AI infrastructure, which just as a reminder, includes the chip makers, includes cloud infrastructure, the neoclouds and software tools like Databricks, those provided by Databricks, for example, Snowflake. So if you're looking at GenAI infrastructure, a good chunk of this company, especially the larger ones, have already moved to public markets in recent years. And this includes companies like CoreWeave, Cerebras Systems more recently. Another chip maker, Grok was acquired by NVIDIA.

And from our numbers, we can see fundraising has been relatively strong for AI infrastructure, but it's probably -- I wouldn't be surprised if it goes down this year. And this is primarily because a few of the companies that can raise big private rounds have already moved to public markets.

If we're moving to our next slide, we do this research where we exclude foundational model providers because they sort of skew the numbers upwards and just look at the GenAI companies that they don't own a frontier foundational model. They use a third party where they have their own, which is fine-tuned or they make their own, but is more specialized. And we see -- so for GenAI, excluding foundational models, we see a sequential increase in funding in Q2, but an annual decline.

So annually, we see a decline. And we think some of these declines can be attributed to factors like the largest foundational models have increasingly moved into different verticals like enterprise, legal coding and so on. And this does make some VC investors avoid or at least pause funding for AI companies that are not at the frontier. And within this environment, when a foundation model like we saw with Anthropic launching Cowork, they could just come and crush it by attacking the specific verticals like coding and legal. And as a result, we think investors are looking elsewhere, pausing a little bit, looking more into what there is in the infrastructure layer.

And on the other hand, I think also a lot of the capital is being sucked by -- in private markets by top foundation model players. They are growing at a speed that has never seen before -- never seen before speed in private markets. And as a result, I think investors are sort of pausing. They're not thinking to stop their investing activities in non-frontier foundational models, but they're definitely looking for a pause and trying to understand where this is leading before putting more money to work.

And if we are going further down into the GenAI application layer, we divided by sort of the use case, audio code, image, multimodal, synthetic data, text, video, we can see text and code remains one of the top funded verticals. Synthetic data a little bit more, but the most interesting that we see is audio actually. And audio has seen an increase basically -- has seen sequential increase over the past 4 quarters. And it is becoming a use case that is more and more important. And if we're going to the last slide, and we've seen -- I want to talk a little bit about the token-maxxing trend, and we saw news that some of the companies burned through their entire annual budgets in just a few months.

So we look at the data from the fintech company ramp, they have about 70,000 business customers, which most of them are so-called AI field. They are investing a lot in AI. And the data shows that the token-maxxing trend is essentially limited to a few power users rather than being broad-based. So this shows -- this chart shows that the average company still spends just $11 per month per user on AI tools, which basically this equates to a Netflix subscription. And this does show the potential for growth and for AI demand to continue to grow exponentially from these levels.

So with this, I finish my presentation, and I will hand over to Melissa.

Thanks, Iuri. It's great to hear all the different things happening on the VC side. Good morning, everyone. Thanks for having me today. Can we go to the next slide. So one of the things that I wanted to kick off with for my presentation -- my part of the presentation was to just highlight in the public markets, what has been happening in terms of CapEx spending. And it is absolutely staggering to look at these numbers.

If we look at the major tech companies, so Alphabet, Microsoft, Amazon, Meta, and Apple, back in 2019, they were all kind of similar parameters for CapEx in total, about $80 billion. And then let's just fast forward to this year. We're looking at close to $700 billion. And next year, based on Visible Alpha consensus, that number is projected to go to $850 billion. And so when we put those together, between this year and next year, the major hyperscalers are expected to spend $1.5 trillion, very substantial amount of money coming into the market to be spent.

And normally, the next question that I get asked is, are we in a bubble? And where is that going? And why isn't Apple participating? So let's go to the next slide and take a look at this. If we look at the balance sheets of these hyperscalers, they are very strong. So Google, Microsoft, Amazon, and Meta, you can see very clearly, as we look out to 2026, 2027, all of the debt-to-equity ratios for those companies are expected to be well below 1, which is, I think, a fairly -- is a decent rule of thumb around health of the balance sheet.

Whereas we do look at Apple and Oracle, for example, these are much higher. And Oracle, I think, by definition, is the levered play in the space. And you can see very clearly that Oracle's debt-to-equity ratio is expected to be over 3. So I think one of the questions -- like to go back to that initial question around the bubble, the reality is that the hyperscalers have a lot of cash that they can spend and have had a lot of cash that they can spend.

So if they start to leverage up their businesses, the amount of capacity is very significant. This could -- like imagine if Amazon or Alphabet took their debt-to-equity ratio up to the same levels as Oracle. I mean this would be very significant. So that's actually how I'm looking at it and how I'm watching it. And I'm also using a total debt, which is incorporating different facets of their liabilities on their balance sheet, not just simply long-term debt, but to really look and see where the leverage may come from.

So let's go to the next slide. One area that we are seeing all of this money being spent is around Memory. Memory was essentially left for dead. It's an area that is very important to the applications, as Iuri alluded to, as an application leverages AI and gets to know you, it remembers you. And in order to do that, it requires Memory and quite a lot of it. And so that has taken the expectations for Memory absolutely through the roof. And I mean, these were doing very little in revenues. And you can see very clearly Samsung, SK Hynix, and Micron all seeing their expectations for the next couple of years really skyrocketing.

And that is really driven by price increases due to this enormous demand coming from the hyperscalers. And there is really not much that's going to slow that down. It's really very much intact. We don't see anything that would say that we're going to stop buying Memory. I think the question is, is how it's managed, how it's navigated and how much new supply will come on to the market over the next couple of years. So I mean, this is one area that we're watching very closely, and it's continuing to defy gravity.

Can we go to the next slide, please? Another area that is worth highlighting around this are power consumption trends. This is a study that was done by Columbia Business School. Columbia showed how the major 4 hyperscalers are really using a lot of power in the U.S. for their data centers. It went from fairly low levels back in 2018 to now it's about 5% of total U.S. annual consumption. And it's -- they're projecting it to go closer to 20% by 2030. So I think there's different views around this. I've seen other studies that are looking at more like 14%, 15%.

But the reality is that it's probably somewhere in that range given the amount of investment that's coming in. So what does that mean when we say there's more power consumption that's coming through. Let's go to the next slide. This is, I think, really where it gets interesting.

So in order to facilitate all of this fantastic growth and infrastructure and to ensure that the compute happens, it requires a lot of electricity. In order to pipe that electricity into the data center, it requires a lot of copper. Copper is the backbone of the data center. It delivers the power, the grid connections. It's -- there's no way that a data center can deliver enhanced compute power for AI without copper wiring. And I think there's a potential here for it to drive significant volume. I mean silver as well. Silver also has high-performance uses around its chip packaging, connectors and switches within the actual rack and within the data center itself.

But I think copper here from a volume standpoint and where we are in terms of timing and how energy is such a critical focus is an area that we're watching very closely. So let's go to the next slide and take a look at copper pricing.

And here, just taking a look at Anglo American, copper expectations have been on the rise this year. And I wonder if there's more revisions that are coming into the pipeline as we look out to 2027, 2028, I think the Street is probably trying to get their head around what the direction of travel is going to be, how sales volume and production are going to shake out as these new data centers come online. And I think you can see it pretty clearly from 2025 to 2026, 2026 to 2027. And it will be interesting to see what ratchets it up further and where we could continue to see maybe outsized expectations starting to hit.

And then if you could go to the next slide. I'm going to move it forward and pass it over to Shari, our guest speaker, to take us into a broader look at how the capital markets are experiencing this.

Yes. Thanks so much. And yes, Shari, we wanted to start with you and get a sense for -- Iuri mentioned that a lot of the GenAI companies are buying IPOs later this year. The SpaceX IPO obviously generated a lot of hype and Anthropic has started setting up meetings with Wall Street bankers ahead of the possible October IPO. We've got OpenAI in the wings. How are you thinking about these mega IPOs and what they say about the health of the IPO market?

Yes. Thanks for the question, Sarah, and thank you all for having me today. So I think one thing that's really important to understand is these mega IPOs, they are important signals, but I don't think they're perfect proxies for the entire market. They do act as market bellwethers, right? They are providing very valuable data points. So think investor appetite, valuation discipline and risk tolerance.

And so companies like SpaceX and leading AI firms, they do attract outsized attention, but their scale and their market position make them unique. So I think it's important for companies to view them as indicators of sentiment rather than direct templates for the broader IPO market. And in terms of the health of the market, we're definitely seeing a healthy market, but it is still extremely selective.

So there's clearly been a recovery in IPO activity, but it's still nothing like what we saw in 2021. Investors are really rewarding quality, profitability pathways and really operational maturity rather than just simply growth at any cost. And so I think the thing that companies in the space need to remember is there is extremely strong demand, but it's concentrated around AI, digital infrastructure, certain health care sectors and fintech with other areas we're seeing secular growth drivers.

So I guess what I would say is the mega IPOs are definitely telling us the market is open, but it's not open for everyone because investors are being highly selective. And so they're rewarding companies that can combine scale, strong fundamentals and really a compelling long-term growth story.

Interesting. And just to follow up on that. Some of these GenAI companies have been raising huge thumbs, just huge thumbs as private companies. As they make the switch to publicly traded companies, do you foresee any new challenges as they become accountable to shareholders or changes that they have to make?

Yes, definitely. I mean I would say the level of scrutiny changes overnight once you go from private to public. And so private companies, they generally have much greater flexibility and how they communicate performance and strategy. But once they're public, management teams are often facing quarter-by-quarter accountability from the shareholders, the analysts, the regulators, the media, right, there are so many stakeholders that are going to be focused on them. And it really just requires a much higher level of operational rigor.

So if you think about expectations around forecasting and execution, they become much more demanding. There's definitely going to be heightened pressure for AI companies to prove the ROI. I think governance becomes a very strategic differentiator. And honestly, maintaining growth while they're public is probably going to be one of the more difficult asks, right, of a newly public company compared to when it was private.

And I would say what they need to remember is going public is not the finish line. It's really the beginning of a new level of accountability. And so the ones that are going to be successful are the ones that compare their innovation and growth with strong governance, transparency and frankly, consistent execution.

Interesting, right. So kind of stability as opposed to burst of innovation are interesting. Iuri, what are the risks to growth and innovation in the global economy? Has overinvestment in AI left little fundraising for other software equipment or biotech markets?

Yes. Thanks, Sarah. I'm not sure if the question is -- so I would say -- I would not say there is little funding left for other endeavors. I think -- and there is always money to fund something. I would say the willingness to fund software, I'm not sure -- I'm not an expert on biotech. I don't know much what's happening in biotech. Maybe Shari knows more in the IPO market, I think it's becoming pretty exciting there.

But I would say the willingness to fund software and also, for example, fintech and other areas like that are non-AI is very low now. This is happening in private markets, but private markets often take choose from public markets. And we've seen that a lot of the software companies in public markets are not trading at valuations that would make private investors salivate for take -- to eventually take these companies public. Maybe a lot of the software companies in public markets, they can be a good value investment -- a value investment that's certainly not a growth investor -- certainly not a growth investment for VCs for venture capitalists, which they're looking for -- mostly for new technologies that can grow a lot.

So if you look at public markets, there is definitely a rotation that has taken place. Money has been moving into AI names, the infrastructure, I think Melissa can talk more about this in Memory. That is for sure. And software has suffered, but my view is that probably it will continue to suffer because there is this -- it's not only the low growth that we've published some articles that we showcased the data from Capital IQ that growth, while it has not suffered in software, it's not accelerating. So it stays sort of locked into the 10%, 13% range.

And that's definitely for a lot of growth investors, that's definitely not something that you want fund. You don't want to fund now like 10%, 13%. You want to fund something that can grow like 50%, 60%. So you have -- and the low growth, you also have -- in addition to low growth, you also have this narrative that is going to be disrupted by AI. And unfortunately, you don't have the growth rate kind of disputing that fact, at least for now. You don't have it sort of proving it that AI is disruptive but you also don't have it that it's -- confirming that it's not a disruptor for us. So this double whammy keeping these areas.

And I'm not sure all software is up for disruption, system software like Microsoft, SAP, Salesforce, these are hard to rip out from your system. So they basically become embedded in your system, it's very hard to rip them out. So probably you're going to build on top of them rather than taking them out completely. And in private markets, the blood bath in software that has happened in public markets. In private markets, it is the same thing and probably even worse. And in VC, VC investors, they're looking at they want to fund the future. And as we can see, there are very few people thinking software is the future now. And a lot of money is being funded into AI, AI hardware and space.

Right. So it's not -- the way to think about it, it's not that AI is kind of stopping up all of the money available. It's more that it's providing that different options for that selectivity that Shari mentioned where investors are choosing what they're betting on growth.

Yes, exactly.

Perfect. We had a question come in from the audience. Iuri, I think you would be able to answer it based on some of your discussions with investment bankers. But we had a question about these companies require -- the audience number is mentioning the hyperscalers. These companies require subcontractors to put in the investment, but they don't have the same credit quality of the hyperscalers. How do these hyperscalers expect the downstream supply chain to fund these projects?

Yes, a very good question. And I think I'm not an expert in that, but basically based from my discussions with a lot of the investment bankers, especially in the data centers space. So even if you are downstream and/or don't have like any quality or credit quality, if you have a contract that is coming from the hyperscalers or it's coming from someone that has good credit quality and they say, look, we are going to be your client and you can show that to the bank or to the lender, then you can borrow money to finance that project. You are basically a good credit.

But if you don't have the hyperscalers as a customer or your potential customers are not good credit, then this becomes a little bit more difficult downstream. And I'd say the financeability of project -- of these projects downstream of AI and subcontracting very much depends on who your clients are and whether your clients are good credit and they can vouch for you with actual contracts that they say, if you deliver this, you're going to get this amount.

Shari, many AI and high-growth companies have been able to stay private longer than ever before. What are the factors that ultimately push a company to transition from private capital to public markets?

Yes, that's a great question, Sarah. And I think what we're seeing is that access to capital is not really the primary reason for going public because as we just heard, right, today's leading private companies, they have access to unprecedented levels of private funding, whether it's from venture capital, private equity, sovereign wealth funds, right, and crossover investors. So what I'm seeing is that the decision to go public, it's more driven by strategic considerations, really more so than just raising cash. And so I think companies are asking whether the public markets are going to help them accelerate growth, enhance their credibility, right, and provide them to maybe broader access to capital over the long term.

So I think what's really important is the scale and maturity of these companies. Certainly, that's going to require potentially a different capital structure, right? So even in today's environment, there does come a point where a company needs whether it's liquidity or currency or just that visibility that the public markets can provide. And so we definitely see IPOs creating these opportunities for companies. And frankly, many large state companies -- private companies are choosing to go public because it's really like the next logical phase of their growth.

And so I think the thing to maybe keep in mind is that the question isn't really, can the company stay private longer because I think it often can given the funding that's available to them. But really, the real question that they're asking themselves is when do the benefits of going public start to outweigh the flexibility that they have if they remain private. I think those are the ones that we're seeing starting to get ready like well long before they need to make that decision because they're taking advantage of the optionality that the private markets give them today while evaluating the benefits of entering into the public markets.

Right. And we are seeing the SEC try and push through some changes that would lower the reporting burdens or make it easier to raise money once you're a publicly traded company without having to wait that first year period and kind of make it easier for companies to go public and encourage that -- make IPOs great again.

Great. Well, Melissa, I think you are on the line. We can't see you right now, but I think we can hear you. How should public market investors evaluate GenAI companies with significant capital needs, especially when private valuations remain high?

[Technical Difficulty] Great. Okay. I think valuations are really going to be, I think, a function of how the company is growing and what sort of total addressable market scalability options they have. So I think investors will probably want to weigh valuation versus growth. And I think if we're in a hyper growth scenario where we're seeing an entire build-out of a new infrastructure and capability within the technology sector, it will be important to understand what those fundamental drivers are.

So at the moment, the way that my team and I, we've been thinking about it is very much not necessarily like what the hyperscalers are spending, where those companies are growing, but where their CapEx is going and how that's accelerating the companies that are receiving that CapEx because it's something that they haven't received before.

And I think that also will play out in the private markets. It's not simply isolated to the public markets. In fact, one of the -- one interesting thing that we have seen is that small companies, whether it be small cap public companies or small companies in general have been enjoying the fruits of all this CapEx that's getting injected into the market. So I think it's just going to be about really understanding the drivers of the company and how they're accelerating.

That's a good point. I think so many of us think, oh, all of that CapEx is just getting sucked up by NVIDIA, but that money is actually creating an economy for these different players in the market.

Indeed. And I think there's different phases of that. You could argue that NVIDIA was Phase 1. It was about transitioning from CPU to GPU. And now we're bringing online Memory so that the transformers can actually remember who you are and what you're doing. And then it will be interesting to see how the rest of it shakes out, what other chips and other capabilities, connectors. As I mentioned, copper could be an interesting area within the data center that prompts that growth.

It's funny because I come from a -- covering a telecom background. And so for so long, copper has been like almost a bad word. Everybody is ripping the copper out and replacing it with fiber. So that's funny to hear. Iuri, we had a question coming from the audience with foundation model companies pulling in $100 billion-plus rounds, is there still a path to profitability for GenAI application start-ups? Or are we heading toward a few winners and a long tail of acqui-hires? You have focused a lot on the application layer.

Yes, I think that's a very good question. And it's probably we're going to have a mix of both. And this is what I've been discussing with VC investors, what they think and what they are looking at when they want to invest in GenAI applications. They're looking for technology that is unique and cannot be replicated easily. This is increasingly harder and harder to do, but still can be done, especially if your focus is small enough that it doesn't become an interest or a larger company or a large premier foundation model is not interested in it. And we've seen, for example, in the legal space, we do have 2 companies that are sort of 1 in Europe and 1 in America that they are sort of the first 2 leaders in legal AI.

And -- then we also saw Anthropic moving into legal with -- they kind of moved into a lot of vertical markets, including sort of legal with the Cowork product. So this is definitely becoming a risk for those investors. But I would say it also becomes this very old debate of best-of-breed or best-of-suite. So if you are a client and you need the best legal AI, then you're probably going to go to a specialized model. If you are sort of happy with one that maybe it's not the best, but it's okay for you because it's also cheaper, then you're probably going to use sort of a model that's not specialized.

And we've seen this happening over the years, like if you remember, Microsoft Office and Lotus, nobody remembers about Lotus, but they were the first one to produce like this Office suite and they're basically killed by Microsoft. And then the same thing happened with Internet Explorer and Mosaic. Mosaic was also like lost in the end and Internet Explorer won and there was -- more recently, we see this, for example, Microsoft Teams having competing with Zoom and Zoom is still here. And if you need -- Zoom is more expensive, but probably as a customer, if you need better features, then you choose Zoom. If you're happy with like best-of-suite, then you choose -- if you don't need to make presentations all the time, then probably fine with Microsoft Teams or you don't do presentations to very large audiences, then you can be happy with the best-of-suite product.

And I think the same we're going to have in the GenAI space. And it's now for companies like or for VC investors is a matter of skill and talent to choose which ones are going to -- are going to win in this market, what are use cases that are going to win where people will choose fewer or the market for those that choose best-of-breed versus best-of-suite is big enough that it makes sense to invest and you can have sort of a business model with that.

And we are already seeing a lot of application layer companies that are very successful despite what a lot of people can say that, oh, premier foundation models are going to come and that is going to -- are going to kill everyone in the market. And can name here in Europe, Synthesia focused on AI video for enterprise, they're very successful, and it doesn't seem that they're going to be disrupted anytime soon, especially by larger companies. And you have the legal AI, I mean, they're not -- they haven't been disrupted. We still -- Lovable Labs, for example, focused on coding. They have a viable business model.

But we kind of have to see how this all goes. It's just still at the beginning. But I would say to answer this audience question, we're going to have a mix of both. It's not going to be, I think, either black or white. It's going to be something in the mix. Some use cases are going to be very successful within their own like sort of niche or vertical markets.

Yes. And I mean we even see that in the financial market where you don't necessarily want to use the large foundation models that are public and you need to keep kind of a closed gate around your data or around your information and making sure that all of that's protected. We are about 15 minutes away from the end. And so I did want to ask the audience if they would like to be contacted in the future for more information. But I did want to go back to Shari. A follow-up, if we can, when we were talking about IPOs. Do you see a difference in how private companies should prepare for their IPOs in this cycle with AI and space tech at the forefront versus previous cycles? Are there lessons learned from the past?

Yes. Well, I think definitely, there are lessons learned. But maybe foundationally, I would say that the preparation requirements, they haven't really changed, right? Investors still want a lot of the same things that they've always wanted, and that's predictable financial reporting, strong governance, right, operations that can scale, a compelling growth story and really that credible path to long-term value creation. But what I would say maybe has changed is just the level of scrutiny around the business fundamentals.

So in sectors like AI and space technology, right, investors are evaluating companies that have very ambitious growth plans, right? And as we heard earlier, very significant capital requirements and frankly, very evolving business models as well. So I would say, as a result of that, investors are spending much more time assessing how the management teams are planning to convert their innovation into more sustainable financial performance.

So I think the companies that benefit, right, we can learn from the past, have to be exceptionally clear about their economics, right? The investors are going to want to understand, well, what are those capital requirements, talk about customer adoption trends, right, revenue quality, cash flow expectations. So there's some very key metrics that investors are going to want to hear about and be able really to measure progress of the management team.

And I think for AI companies, in particular, the increased focus on whether the growth is being driven by like real durable customer demand versus experimentation. And then maybe for space and other emerging technologies, I would say investors are looking very closely at commercialization, scalability and what type of execution risk there is. So although these technologies might be different, I still think the fundamentals of a successful IPO remain the same, right? Investors are looking for -- you've heard me say it, high-quality companies, right, with strong governance, reliable reporting and a very credible path to creating long-term shareholder value. So those elements haven't changed.

Got it. Melissa, we had a question coming from the audience about, are there any analogies or lessons that can be drawn from the recently previous era of cloud CapEx spending?

Well, I guess the one that's often referred to is around the Internet. When the Internet came out, and it just -- everything just went hog wild and we ended up in a pretty significant bubble during the late '90s, early 2000 before it all meaningfully slowed down. I think there's some clear differences there compared to now. One is that we have Reg FD now. So there is a clear wall between investment banking and research analysts, which did not use to exist before that. And so I think companies that are coming to market as Shari said, there is a discipline around them that is, I think, a bit higher quality than we did see in that previous era.

And the second thing is that there is a whole infrastructure that is hardware around this, whereas Internet was more of a software capability, building things like websites and apps and a whole structure around that, whereas this is about building data centers to enhance compute. So we're talking about things like real estate and putting all of that into a model that is energy efficient and sustainable and clean. And then maybe that goes to space. There's a very good argument to be made that space is probably one of the best places for those. We've seen that with satellites. So that would be one area that I would point to.

I think a second analogy that I would look at would be how the smartphone exploded in -- right after the financial crisis. We had -- like really, it started around like 2010, 2011, when we started to really see broad adoption of the iPhone and really start to transform mobile technology. And it became this very transformative technology that enabled the quality of many people's lives to be enhanced. And I think that's what we're really looking for with AI is to Shari's point around ROI is to see broad adoption in a way that translates into enhancements to growth and fundamentals. And we certainly saw that with Apple and with many of the applications that are in the iPhone ecosystem.

And so that would be one area that I think we're watching very closely to try to understand. We haven't really seen anything hit the ground running yet, but that doesn't mean that it's not going to. It's just a matter of, okay, we're building out the infrastructure. We're getting the compute power enhanced. We're going to try to get the cost down so that we're not racking up these huge bills of tokens and then kind of see where it starts to gain traction. I think these are like a couple of areas like milestones that I'm watching.

Great. And Orbital data centers have been kind of gently referenced a couple of times. Just a shameless plug, we will be having a webinar next week that is totally dedicated to SpaceX and Orbital data centers and their feasibility. So do check that out. It's from the S&P Global Energy team and our 451 research colleagues. I'm very excited about it.

Iuri, I think we've got time for another audience question. In the EU, AI is rather heavily regulated. How do you think this would impact AI markets globally and especially in the EU? I know this is something you have talked about with me at least very frequently.

Yes. Thanks. This is good and definitely an important question, even though it is -- for me, I think it's sort of hard to -- hard to say exactly how all this is going to pan out, especially from a regulatory perspective. But what I can say is that there is, in Europe, a regulatory fatigue, so to speak, European AI companies from what I'm hearing also in the legal side as well, they're pushing back against excessive regulation. And there are some efforts to streamline some regulations, remove some, make it easier to make -- not only like to open not only tech business, but general to make business in Europe.

And I think Europe has learned a hard lesson that too much regulation impedes business creation and there are increasingly a lot of like more louder voices that are calling for a regulatory landscape that is less excessive. And a lot of the regulation in Europe, this is from what I've been speaking, the tech business on the ground, a lot of the regulation has good intentions. And -- you look at the regulation, and it seems like good -- with good intentions basically, but ends up with bad outcomes for European technology and European business.

And I think you probably can include here the sovereignty issue and Europe wants to be more tech sovereign, not depend too much on U.S. technology and dependent on energy, dependent on tech. But if you want to do that and they want to do that, I think there has -- the realization may be coming slower, but it is coming that if you want to be sovereign, then you probably need to have a much more constructive regulatory environment and probably also like less [ lineage ].

Well, it does not escape my attention that this question is coming, what, just days, a couple of weeks before the deadline for implementing the EU AI Act and some of the disclosure requirements around that, which we are all dealing with. And it does seem like in terms of as AI increasingly gets integrated into workflow tools, does then everything gets some kind of AI disclosure around it so that then the disclosure then becomes almost meaningless or not as helpful. So it's a very timely question. Thank you.

I think we have -- I think we have time for one last thing. Shari, are you hearing about conversation happening as companies prepare to go public? Is that reach out to public markets already happening? Or is that a trend expected in the near future? How significant are you expecting the IPO outlook to be or fundraising to be at this point?

Yes. No, that's a great question. And we are definitely seeing companies access both public and private capital markets really to support their large-scale AI investments and infrastructure build-outs. So I definitely think that the scale of investment that's required to support AI growth is significant. And so the capital markets are playing an increasingly important role in funding that expansion. We're also seeing quite a bit of AI-related debt issuances. So that's accelerating as companies are really seeking diversified funding sources, right? We've heard how capital-intensive it is and the access to capital is there, whether it's through private markets, capital or debt as well as public markets.

And I don't think it's a question of whether the capital is available. I think we've all seen that it is, and companies are definitely accessing it. And so I think the most important thing maybe for companies to be thinking about is how prepared are they to access it? And can they clearly demonstrate why they deserve it. So it's definitely a very prevalent phenomenon. And I think companies need to differentiate themselves as they're seeking access to various sources of capital.

Absolutely. Well, we covered a lot today, and we are about at time. So if you have any follow-up questions, please use the Q&A widget, and we'll get back to you. For those watching the replay, feel free to reach out via the request demo link in the related content widget. You can revisit today's material as we recorded the session. Tomorrow, you'll receive an e-mail with a link to access the replay at your convenience and the slides will also be available in the related content widget.

We would also like to remind you that we recently acquired Visible Alpha, which provides sell-side models and granular consensus estimates. Please click the link in our related content widget to learn more. Notably, Visible Alpha and Melissa will soon be publishing their AI monitor of publicly listed AI companies. So do be on the lookout for that.

When we close out this webinar, you'll be routed to our survey. We'd love to hear your feedback. So please take a few moments to complete it. And in closing, a big thank you to Iuri, Shari, and Melissa for sharing their insights, and thank you all for joining us today. We look forward to seeing you again soon. Thanks so much.

Thank you very much.

Okay. Welcome, everyone. So having the pleasure of hosting Mark Grant, SVP, Investor Relations and Treasurer at S&P Global. Mark, thanks for coming today.

Thank you for having me, Sean. It's great to be here.

So I'm going to kick things off. I'm going to dive into Market Intelligence and GenAI, which is the vast majority of the questions I get on S&P these days because the rest of the business is sort of resilient and strong. So my first question is, so how do you distinguish between cyclical headwinds, like end market softness in the financial sector? And any structural AI substitution risk to CapIQ and all the similar workflow tools within Market Intelligence.

Yes. I think this is a really important question. And to your point, we get this a lot on our side as well, right? I'm glad that you started with how resilient the rest of the business is, right? As most folks understand, we're primarily a benchmarks business, right? 2/3 of our revenue, roughly 3/4 of our profit comes from benchmarks, right?

The Ratings, the Index, the Platts commodities prices. These are fantastic, very resilient businesses, where we are the only source on planet earth for that information, right? And so we do get a lot of questions around, well, what's this small pocket in Market Intelligence that could potentially be at risk here? And how do we assess that, right? So when we look at the Market Intelligence performance, most of the questions we get are specifically around Cap IQ, right? Cap IQ is the product that most of our investors are most familiar with because they either use it or they use one of the competitor solutions almost every day, right?

Cap IQ is less than 6% of our total revenue and even smaller percentage of our profits, right? So when we look at this, it's -- they are very important questions about a very, very small part of our business. And so when we look at the Market Intelligence business broadly, you've got incredible data sets in there like Compustat and SNL that's the distribution platform for much of our ratings content through RatingsDirect and RatingsXpress. We've got these incredible workflow tools that are highly moated and have great network externalities that create a great deal of value for our customers.

And we have a lot of data that gets distributed through these platforms that customers consume in various ways, whether that's through a desktop or through data feeds or through Databricks and Snowflake or more recently through MCP connectors, which I'm sure we'll get into as well. When we look at the performance of that business, it's actually fairly easy to differentiate between what are cyclical tailwinds, what are secular tailwinds, what are the themes that we're seeing in the market that really drive performance there.

And one of the themes that we've seen is vendor consolidation. More and more of the customers that we talk to, primarily through our Chief Client Office, our large sophisticated strategic customers, they want fewer vendors in their ecosystem. They know that there are huge swaths of information and value that they can only get from S&P Global. And so they come to us very regularly and say, all right, what else could we be getting from you and how can we eliminate some point solutions in our ecosystem.

So that's something that we would consider as a secular tailwind theme, right? The cyclicality piece impacts us a little bit less than you would expect in some -- for some other folks in the space because we haven't had seat-based pricing in 5, 6 years, right, longer than that. So having the enterprise contracts that we do allows us to look through a lot of the cyclical stuff without it actually impacting the financial performance of Market Intelligence materially at all.

Got it. And then I guess from a high level, like what are you hearing from your customers for demand for S&P's data?

Look, I think the general theme is your data is great. For most of what we're consuming, you're the only source we have, and all of the tools that we're looking at using or starting to deploy now require us to consume more data at higher volumes at higher velocity. So our customers are telling us we need to do more. We want to consolidate more. We view S&P Global as a very powerful strategic partner for us and an incredibly important vendor.

And so how can we structure things such that we can consume this data and make sure that there's the value recognition on the economics, right? So when we look at the deployment of MCP connections, right? We've talked about this a little bit in our most recent earnings call, we've seen volumes of API calls through those MCP connections increase 500% quarter-over-quarter, 100% month-over-month, right? And so the value that our customers are getting from S&P Global data through all of these platforms is only increasing, right? And I think over time, you see that show up in the economics as well.

Yes. That was my next question was about just demand for data within this GenAI world, right? So yes, it was 5x quarter-over-quarter, right, for the API call volumes. And I think there was renewal uplifts as well as like 35% to 45%. I think maybe a few clients, but very promising. So I guess, taking a step back, can you help us like frame that I guess the revenue opportunity there from AI over the next 2 or 3 years?

Yes, I think this is another important point because the reality is nobody knows exactly how this is going to play out, right? When we look at the financial services end market, the energy end market or nonfinancial corporates, whatever customer base that we're serving, you have to start with the realization that customers don't have infinite budget. And so the value that we are creating for customers, we have to also help them understand not just how we're creating more value, but we can also help facilitate freeing up budget for them, right?

And that goes back to the point on vendor consolidation. If you can eliminate point solutions in your ecosystem and do more through S&P Global, yes, your contract value with us is going to go up, but your total cost of ownership across that portfolio of products actually goes down. And so when we look at customers who are looking to invest more in their AI solutions, looking to invest more in data, looking to really scale out some of these strategic initiatives, S&P Global is probably as well positioned as any company in the world to facilitate that, right?

And so I think as we look at revenue growth over time, you do see that show up in customer retention. You see it show up in wallet retention. You see it show up in sales cycles. You see it show up in competitive win rates, right? And ultimately, you see it show up in pricing power, too, as we increase the value we're creating for our customers, we ask them, of course, to share the economics of some of that value with us, right, through price.

Yes. And I was just going to touch on, I guess, the competitive environment with AI. Market Intelligence growth, I think you said last quarter is running 30% higher for AI customers versus non-AI customers? And then you touched on it that the net renewal rates increased 100 basis points last quarter, which is great to see. So are you seeing any share gains from competitors like Bloomberg or FactSet specifically because of these AI features that you're rolling out? Or is this primarily just wallet share expansion within existing clients?

Yes. It's a fair question. This is a space that's been competitive for a very long time. We have scaled competitors in Market Intelligence. We've got a great deal of respect for our competitors in that space. I think when we look at the investments that we've made over time in adding AI functionality to our products so if you look at features like ChatIQ, Chart Explainer, Document Intelligence, all sit within CapIQ Pro, it increases the functionality of that platform for the people that are using that as their daily tool, right?

So that absolutely creates value. That shows up in renewal rates, and it certainly shows up in competitive win rates, right? But it's a much broader conversation with most of our larger customers. It's not just about what are you doing with Cap IQ. It's about what are you doing with MCP? What are you doing with the Kensho Grounding Agent? What are you doing with the Kensho LLM ready APIs? And how are you looking at making the full data estate available, right? And so these are initiatives that we have internally as well about how we can meet the evolving needs of our customers faster than anyone else and delivering value, frankly, that they could only get from us anyway, right?

So I do think this shows up in competitive win rates, but look, our competitors aren't standing still either, right? We've got -- like I said, we've got a great deal of respect for the competitors that we have in the space. It goes back to the iron sharpens iron analogy. But look, I think we -- if you go back to what we said at Investor Day, the financial targets that we put out, we admitted on stage. That's going to require us to take market share because the end market is not growing 6% to 8% on an organic constant currency basis. We're confident we'll be able to do that.

And when -- I guess, when you look across your competitors, right, whether it be Bloomberg, FactSet, Thomson Reuters, like, how is the -- how do you feel like company is positioned versus those competitors? And then also, like, what specific advantages does S&P have versus them?

The single greatest advantage that S&P Global has is that we are the single source for the vast majority of what we do, right? Look across the entire ecosystem and we do have conversations where folks want to focus just on Market Intelligence, but our customers don't, right? Our customers come to us for a broad array of products across all of our divisions, right?

The Ratings division sits a bit siloed just from a regulatory standpoint. We don't really package Ratings with anything else, right? But when you look at customers, a large global investment bank is likely buying data through the Index business. They may very well have portfolios on the asset management side that are benchmarked against our indices. They are likely buying pricing data from our energy business because their energy traders would have a really hard time actually managing their workflows without knowing Dated Brent crude prices, right?

You've got all the content that we distribute through Market Intelligence. And so the single greatest advantage that I think we have is just this massive holistic set of solutions that power the entire global market, whether that's the equity markets, the fixed income markets or the commodities markets. And so as we can demonstrate to our customers across that swath of products, we are adding more value for you. Every year, every quarter, we're launching new products. We're launching new features. We're launching new data sets, making more of our data available through LLMs, through the Kensho LLM ready APIs, right? All of that makes this conversation with customers about so much more than just the desktop.

And the Chief Client office is a huge part of it...

It is.

Right. And it's been up and running for probably a little over a year now.

Yes.

Can you just talk about, I guess, what the over the course of the last year? Like, I guess, what learnings you have kind of like where is it on its kind of maturation curve?

Yes. I think we're in very, very good shape. So Sally Moore is our Chief Client Officer. I think she's one of the most brilliant commercial minds I've ever seen in my career, having her in that position really does solidify that customer focus across the entire organization. And she's done a phenomenal job and the team that works for her has done a phenomenal job orchestrating our commercial initiatives, right?

So if you go back a few years, you may have had a team from Market Intelligence to come and visit you as a customer. And the next week, somebody from Energy may have come and visited you. And they might not even have known that the other team was there, right? Because that coordinated effort wasn't necessarily as robust as it is now under the Chief Client Officer and with Sally in there, in particular, we've really created this ecosystem where the divisions focus on serving clients holistically, particularly those large strategic customers.

We're talking about 150 of our largest customers or so in the Chief Client Office. And it really does allow those customers to have a greater sense of the value we create for them holistically, but it's also been a huge driver of just product awareness, like, so many times we've gone into a customer who's bought 1 or 2 products from us for years and years and didn't even realize that we did so many other things.

So when we go back to that point on vendor consolidation, the Chief Client Office facilitates that as well, elevating those conversations up into the C-suite and making more strategic decisions around just how much value we can create for a customer across the entire organization that's been a huge driver for us, not just in Market Intelligence but everywhere.

And you mentioned, I think it was a few quarters ago, but just about sales incentives and kind of restructuring them and maybe consolidating them from -- and I think that tears down silos just internally. But can you just talk about how the sales incentives, you don't have to be specific, but just how you kind of thought about them and changed them over the past year or so.

Yes. So this was -- I will probably forever be grateful to Saugata Saha for the transformation that he helped orchestrate inside of Market Intelligence, the simplification of the commercial teams and what we call publicly the revenue transformation in Market Intelligence was a big part of what Saugata was able to deliver in his first year there as the President of Market Intelligence, simplifying the incentive structure, making sure that it aligns with the best possible economic outcome for not just our customers but for us as a company and ultimately, for our shareholders as well.

Going from 60-plus different commission plans in Market Intelligence down to 10 and making sure that it was very clear to our commercial teams, how their incentives aligned with the incentives of the broader enterprise, our customers and our shareholders. That was a very, very heavy lift. And so when we have this leadership transition in Market Intelligence now whoever comes in and runs that Market Intelligence business will be in a very, very good position to execute and to deliver results because of what Saugata was able to do in his 1.5 years there.

Got it. And then maybe just touch on the leadership transition a little bit more and also the Data Office because Saugata was the head of that as well. Could you just touch a little bit more about like kind of what's happening and how you guys are thinking internally?

Yes. So I think for those that may not know, Saugata Saha was the President, still is the President of Market Intelligence and our Chief Enterprise Data Officer. So when Martina established the EDO or the Enterprise Data Office, Saugata was put in place as the head of that when that was created. So he wore 2 hats simultaneously. They weren't necessarily one because of the other, right? He was just the best person to wear both of those hats.

When he announced that he'd be leaving to go take a CEO role at a tech company, one of the things that Martina did immediately was take that Enterprise Data Office and roll that up under our Chief Technology and Transformation Officer, Firdaus, who is a phenomenal leader, right? And I think if we had somebody like Firdaus 1.5 years ago, we may very well have structured this differently from the beginning. I don't know. But Firdaus joined just a few weeks ago, brilliant technologist, successful entrepreneur in his own right, he knows how to manage businesses, deeply steeped in the technology. And so it makes perfect sense for us to have the individual leading our technology and transformation, be also the same person who's leading our Enterprise Data Office.

And so this is one that we just made perfect sense immediately to Martina and to everybody else. When we look at the Market Intelligence transformation there on that transition from a leadership standpoint, all we've really said at this point is that we're going to move quickly and thoughtfully, right? So we want to make sure that we're able to execute that we're able to deliver the results that we've talked about for this year and for the forecast from our Investor Day. But we'll have more to say about that at the appropriate time.

Great. Makes sense. And then we touched -- I mean we talked a lot about, I guess, GenAI from the revenue side, but just from the running an information data analytics business, just I guess, from the internal cost workflow side on S&P, what has GenAI -- I guess one for Market Intelligence, what kind of learnings there have you had about cost takeout and efficiency.

Then also maybe about like Ratings, and I know it's a little bit different in terms of the regulatory environment, you move a little bit slower, more pragmatically. Could you also touch on Ratings and the other businesses as well.

Yes. So I'll start with Ratings. I think this is -- there's a great opportunity for technology deployment inside the Ratings Agency. That's been true for a long time. So we've gone through multiple generations of deploying technology inside the Ratings business, whether that was traditional machine learning and deep learning to multiple rounds of deploying robotic process automation and RPA, right?

So that is an organization that is very used to adopting and moving quickly as technology has evolved, GenAI is no different, right? So we've created specific tools that sit inside of the Ratings agency that are actually separate from the rest of S&P Global just because we have to manage data silos, and there's information barriers that can't be crossed. So Spark Assist is our internal kind of copilot tool that we've built.

Most of the organization gets access to that. There's a separate version of it that is just for the Ratings agency, right, so that they can leverage data that only they have access to, there's no commingling of that. I think when we look at AI and its potential to drive further growth and opportunities in the Ratings Agency, we have to be cognizant of the fact that there is a significant degree of human judgment that is required to create a Rating, right? And that's not just true from a practical standpoint, but it's true from a regulatory standpoint, right?

The credit analysts that publish these ratings are taking personal liability, right? Similar to when you publish a note, you've got a Reg AC certification at the bottom of it, certifying that it matches your personal views, right? And you're taking personal liability by publishing that note, our ratings analysts are the same, and AI can't do that, can't comply with that regulation, right?

So we want to make sure that, that degree of human judgment and expertise stays there, stays robust and stays celebrated. What we can do is leverage new technologies and tools to make those people more productive. And in fact, we can hire more credit analysts at the covering level and give them the support that they need through staff and through technology augmentation to make sure that they can provide the attestations that they have to, that they have the bandwidth to surveil all of the ratings that they've published that they can effectively manage the workload.

And so you've seen that show up in our margins in the Ratings business for several years, right? If you go back to our margin targets from the 2022 Investor Day, our 2025 margins in Ratings were well above the high end of what we thought they would be in 2022, right, part of that is through technology, part of that is through cross training and making sure that we've got the scale and scope in our population of analysts who are, in my opinion, the best in the world, right?

And so outside of Ratings, I think there are huge opportunities because you don't have the same regulatory constraints or attestations and requirements that you have in Ratings. But we said at our Investor Day, we actually think the greatest opportunity for margin expansion in any of our divisions sits within Market Intelligence, right? Roughly half of our global headcount sits within Market Intelligence. And I think there are huge opportunities there to help make those people more productive and help them dedicate more of their time to more fulfilling work. And I think arguably continue to scale that business on the top line much, much faster than we'll have to scale it at the head count level.

Got it. And I want to touch on Kensho for a little bit, which I think is like a great asset within S&P. So I think last quarter, you said there was like 300-plus customers under contract or trial for the Kensho LLM-ready API. So can you walk us through the product road map from here? And specifically, how you plan to evolve from API delivery to agentic workflows and what that means for the pricing architecture?

Yes. I think this is one that we very closely watch. This ecosystem is evolving very, very quickly. And when we first started talking about the Kensho Grounding Agent, the number of times that I had to explain and frankly, the number of times they had to explain to me, if I'm honest, just what a Grounding Agent is. And we were so early in MCP so early with getting Grounding Agents out there, data retrieval agents.

So this is an ecosystem where we've been comfortably working for quite some time. And when we look at how that ecosystem evolves from our customer perspective, our partners' perspective, right, there's -- there are a lot of moving pieces. We've seen significant evolution just in the last 7 months since we had our Investor Day with the launch of new products, new platforms, new models. I think when we look at agentic workflows, I think most people would look at that and say, all right, truly automated, agentic workflows, straight-through processing either moving from human-in-the-loop to human on the loop or from no human involvement whatsoever, right?

People are exploring conceptually what that might look like. We have to make sure that we're moving quickly enough to facilitate that where our customers want it. So making more and more of our data available through LLM-ready APIs, which means attaching machine-readable metadata and contextualizing that data so that it can be consumed and used in an LLM ecosystem, right? We've been very early to that. We continue to scale out.

Every quarter, we introduce new data sets available through those LLM-ready APIs. But we're also seeing the evolution of things like skills and applications where we can actually create something like a skill that sits almost like if you look at the software space years ago, the phenomenon of containerization, right? Skills kind of serve that same purpose, where we can build skills which function like a collection of prompts, right, or prewritten instructions, and you can put these skills together in stacks that can create truly value-driven workflows, leveraging S&P Global data through an MCP connector in an ecosystem like Claude or ChatGPT, right? So more and more, we're leaning on these not just the Kensho engineers, but other engineers and technologists like Firdaus and the people in his organization to really scale out these initiatives and make sure that by the time our customers really want to be there, we're already comfortable operating.

Got it. And then just moving on to Ratings. We're just talking before that it seems like there's so many kind of structural tailwinds to the business right now. And 1Q billed issuance rose 14% year-over-year. And you're citing hyperscaler IG bond issuance for AI infrastructure is a primary driver there. So just how large is this AI-driven issuance opportunity? You see all these $7 trillion stats and huge demand there. And are you seeing outside the hyperscalers and other areas like energy or industrial end markets that are supporting the AI build out across the world?

Yes. I think this is a phenomenon that impacts a lot of industries, right? People don't realize just how much energy consumption goes into something like a data center. They also don't fully appreciate how much concrete goes into that, right? There are so many different industries that are impacted by this level of CapEx investment. But at the end of the day, it's funded, right? And predominantly, thus far, it's been funded by debt. When we look at our issuance forecast for 2026, we've said publicly, our issuance forecast really only assumes that less than half of the announced CapEx from the hyperscalers actually comes to the market funded by debt, right?

So we've seen a mix of funding this year between -- predominantly, it's been debt, but there's been significant slugs of equity announced as well, right? So our guidance and our billed issuance forecast does not assume that even half of what's been announced actually comes and is funded by debt, if it were to come that meaning half of it were to come, that would be a point or 2 of upside to our billed issuance forecast.

But I think that's an important distinction as well because we get this question a lot, right? The hyperscalers are not in our frequent issuer program, right? Otherwise, they couldn't impact the billed issuance at all. Billed issuances -- or frequent issuer program is excluded from our billed issuance calculation. So when they come to the market and we're rating that debt, that isn't something where they've paid us a flat rate, and we're just going to rate whatever they do, they're paying us every time they come to the market and we rate that debt.

So that's been an important driver of results for us, as you saw in the first quarter, right? I think if we were to see the pace of debt issuance in the first quarter continue through the rest of the year, that's more than we're assuming in our forecast, for sure, right? But I think we do stand to benefit from that very well. Like we know that through all the data that we have internally and the expertise that we've built out over years, we have a fantastic offering for rating the data center debt. And I think market participants understand and appreciate that as well. So we are frequently tapped to do those deals.

Could that change over time if one of the hyperscaler just has some road map when they're going to forecast that they're going to tap the debt markets over the next 5 years continuously. Could they come to you guys and say, hey, can you work with us or with a frequent issuer program or things like that or not really?

I mean, it's always possible. But at the end of the day, that's really not what the frequent issuer program is designed to do, right? It's not for customers that come to the market with big slugs of debt every once in a while, right? It's for market participants that are very frequently in the market all throughout the year in generally very predictable ways, right? So -- and that program has been structured to facilitate that part of the market. The hyperscalers, really, don't fall into that bucket for us.

Got it. And then what -- I guess, what other kind of deep funding currents are out there over the next year but also in the next few years? I know that's mature -- the large maturity walls and things like that.

That's exactly where I was going, Sean. When we look at the maturity walls over the next few years, they're very, very strong, up -- I mean the 3-year forward cumulative maturity wall is still up double digits from where it was last year. And when we look at particularly the '27 and '28 maturity walls, a lot of this is debt that was issued in 2020 or 2021 at very low rates.

So we don't necessarily think there's a lot of incentive for those issuers to pull forward the refinancing of that. That's why we don't include any kind of material impact from pull forward out of those maturity walls in 2026 guidance. But eventually, that debt comes, right? And what we've seen historically is that, that tends to get refinanced. We typically don't see large corporates paying off debt at scale. So we would expect those to benefit from those maturity walls as they come through. It's just very difficult for us to predict what quarter or even what year sometimes that issuance will come through. We know that if you've got a 3-year kind of horizon, you'll capture all of it.

And then moving on to private markets revenue and S&P is focused there. It ended '25, north of $600 million at the enterprise level. And then I believe in the first quarter, private credit was up 25% for Ratings year-over-year. So like how would you think about, like, S&P's like penetration today, I guess, in Ratings, but then, I guess, overall? And what are the biggest challenges looking forward, keeping that competitive edge? Is it like data sourcing, client adoption, competition to sustaining kind of this growth rate, high level?

Yes. So it's -- so you're right. Our total private markets initiative across the entire organization was north of $600 million last year. We've said just within the Ratings business, it's hundreds of millions. And to your point, growing 25% in the first quarter. So it's been a very strong growth driver for us off of a decent base, right?

So this is not a subscale business for us by any means. Certainly, smaller than the public markets, of course, but a meaningful growth driver. I think as we've seen the evolution of that private market space really over the last 4 or 5 years, we've seen more debt that could be done in the public markets, actually getting done in the private markets. And for the most part, we rate that, right? So if it is debt that could be in the public markets, I think we've got a great chance at rating that debt.

As more focus has been spent on the potential risk in private markets. I think that actually generates more demand for Ratings generally, but it also generates more demand for our Ratings specifically because we're a large global institution. The brand recognition is very strong. Our methodologies are exactly the same in the public markets and the private markets.

So there's no differentiation there. If you are used to trading public market bonds and you're used to seeing an S&P Global Rating saying it's investment grade, it's that exact same methodology that gets deployed in the private markets that instills a great deal of confidence in the investment community because they know exactly how to interpret an S&P Global Rating. Importantly, that also means that our rating travels.

So if debt that's issued in the private markets and that issuer wants to refinance that in the public markets, they don't have to worry about a degradation in their rating, all else equal, right, because our methodologies, the risk factors, the criteria, they're all the same. And our pricing is the same, right? So for us, I think over the long run, we're largely ambivalent over whether the debt gets issued in the private markets or the public markets, we think our opportunity to rate that debt and create value in the ecosystem is the same and our economics are the same.

And then I've gotten questions. It's just about kind of the private credit headwinds that have been all over the headlines last few months. Are you seeing any of those headwinds in your more, I guess, the Ratings private credit business versus this time a year ago?

I think if you go back to some of the numbers that you pointed to, billed issuance in the first quarter grew 14% overall. Private markets grew 25%. So it's still a much faster growing piece of our business. And so I do think, to the point that I was making earlier, as we've seen the ecosystem evolve and as we've seen the risk environment evolve a little bit, there is more demand for Ratings generally, more demand for our ratings specifically.

I think that likely continues, right? I don't know that there's necessarily anything that I would point to and say, "Hey, this is something that's structural that we're paying attention to, right?" Like I mentioned before, I think in the long run, we're going to be fairly ambivalent whether it's public or private.

And then moving on to Indices business, maybe -- some would argue the crown jewel of S&P...

It is a beautiful business.

Around 74% operating margin. I believe last quarter, revenue was up 17%, mostly because of the asset-linked fee business. So what do you -- when you look at the business, what are the most exciting investment opportunities in the Indices today? And then how should we think about margins over the next few years?

Yes. So one of the reasons that I love the Index business so much is not only does it create a great deal of shareholder value, but it's also perfectly aligned with our customer interests. When you think about the way we've structured that business, to your point, the majority of the revenue is asset-linked fees, which means when our customers thrive, we thrive with them.

When the markets go up, we grow all else equal, when fund flows benefit our customers, they benefit us as well, right? The flip side of that is also true, right? When our customers feel pain, we share it with them, right? We're directly tied to the interest of those customers, which makes that a very resilient business model for us that grows quite well.

As you know, markets tend to go up over time, right? And so that business tends to grow automatically. When we look at the investment opportunities, we've talked about some really exciting opportunities in digital wealth, in direct indexing, right, on the custom index and data subscription side, which has been growing double digits for us for the last several quarters, like these are all great opportunities for us to grow that business.

But there is a bit of a double-edged sword there because you've got the S&P 500 and that's a phenomenal product. It's an incredibly powerful ecosystem built around that, these liquid ecosystems. And so that piece of the business will continue to grow for a very long time, right? That's our view. And so for a new product to come in and potentially accelerate the growth when you've got a big product like the S&P 500 ecosystem that has $15 trillion, $20 trillion of AUM behind it, you've got to launch a lot of new products in order to dramatically move the needle, but there are some really exciting opportunities.

Got it. And then the Energy division has some strategic repositioning that was announced last quarter. So just looking at that, what is the ideal revenue mix look like for this division over the next few years? And maybe some of the motivations behind the repositioning you did last quarter?

Yes. So the Energy division is predominantly subscription. As you know, price assessments, energy and resources, data and insights, upstream, the vast majority of that is going to be subscription revenue for us. I think that's always going to be the case. There are pockets of that business that are event-driven. And so as you know, the first quarter of every year, we host CERAWeek, which is the world's premier energy conference.

When the world wants to talk about energy, they do it at CERAWeek. And so you see that every first quarter in the Advisory & Transactional Services revenue, right? You also have this great business around Global Trading Services, which is somewhat event-driven. That's the derivative instruments against our Platts benchmark prices, right? So that can fluctuate from quarter to quarter based on what we're seeing in the markets, but it's a great business.

So I think over time, that business will continue to be predominantly subscription, continue to have a really great market position. When we talk about upstream specifically, the divestiture that we announced of the upstream software business that software piece is really something that's better owned by somebody like SLB who's buying that, right, where they're scaling out an offering. That wasn't necessarily an area where we wanted to go in and say, we're going to make a big investment to scale this out and make it a globally competitive software business. Really the value that we see for our customers across the entire estate is in the truly proprietary data, that's in the 3/4 of upstream that we're keeping.

And then, I guess, the larger kind of strategic action that you've been taking and planning for the last year or so, with the Mobility spin effective July 1 and the $2 billion of debt placed at Mobility Global. So I was just wondering, how should investors think about the capital strategy at S&P? And how -- does the bias shift towards buybacks with the stock price at these levels? More tuck-in M&A, maybe I was thinking like kind of unique data sets and things like that or deleveraging at these levels?

Yes. So with the completion of the mobility spin, which we expect to take place on July 1, you're right, we raised $2 billion of debt financing that gets dividends out to S&P Global. We've said publicly the intended use of proceeds there, share repurchases and some debt reduction as well. We want to make sure that the spin is leverage-neutral for us, but we're very comfortable with where we are in the balance sheet.

We've managed that very well over time. So I think from a capital allocation standpoint, we have a publicly stated target of returning at least 85% of free cash flow every year to shareholders through dividends and buybacks, with the proceeds from Mobility, we're raising that for 2026 to 100%, right? So that's going to be roughly $4.5 billion of share repurchases this year. And so that's -- that's really the focus, particularly given where the valuation is right now, the return that we get on buying back stock, I think, is very high, and that increases or elevates rather the bar that we would need to clear even for something like tuck-in M&A. So we've said publicly, there's no appetite for anything transformational. And even the appetite for tuck-ins has diminished a little bit just given the bar that they'd have to clear given where the share price is.

And then at your Investor Day, the medium-term targets, 7% to 9% organic constant currency growth, annual margin expansion of 75 bps. And given the strong 1Q, right, 9% organic growth and then 100 bps of margin expansion. And looking at this year, I guess, what would need to go wrong to track towards the low end of those ranges? And I guess where do you see the most upside in the business this year, but also over the next like 2 to 3 years?

Yes. I mean this is the kind of question that we typically get at the end of almost every meeting we have, right? Like what's going to drive upside, what's going to drive potential downside. For us, the answer is always going to be the market-driven businesses because they're the hardest to predict, and they're the ones where you can see fluctuation and have seen that historically, right? So that's Ratings and Indices primarily. So in periods where we see very strong issuance, you're going to see potential upside even to the targets we gave out at Investor Day, in periods where you see dramatic outperformance in an index like the S&P 500, that will benefit us as well. And the flip side to that is also true.

I think that's it. Thanks, Mark. Really appreciate it.

Thank you, Sean.

All right. We'll get started here. So thanks, everyone, for the session. I'm pleased to have -- welcome back, Martina Cheung, President and CEO of S&P Global for a second time. So thanks for making it back. We didn't scare you after the first time last year. As always, on this, if you have a question, you can send it through Pigeonhole or you can do it through the scan the QR code, I believe, on your screen somewhere.

Okay. So with that, I'll get started with questions for Martina. So Martina, let's just start on growth at the company. At Investor Day, you laid out three strategic pillars for the company: advancing market leadership, expanding into high-growth adjacencies and amplifying enterprise capabilities through AI. You are guiding to 6% to 8%-ish type top line growth, some amount of margin expansion over time. At a high level, which of those three pillars is most likely to surprise you think, over the next 12 months -- 12 to 18 months? And is there a scenario where you think growth could be better than what you laid out at Investor Day?

Yes. Thanks, Christian, and it's great to be here again with you. I would say if you think about the combination of our businesses, we are really predominantly a benchmarks business. So that's 2/3 of our revenue, 3/4 of our profit. And our benchmarks span, as you know, Ratings, Index and our Price Assessments in the Energy division. And Ratings and Index, in particular, will be highly sensitive to the market.

So over time, particularly if we think about the next 12- to 18-month time horizon, it will probably be those market-driven businesses that to the extent there's an opportunity to surprise to the upside, for example, if issuance were much higher than we imagined or if the U.S. equity markets were much stronger than we imagined as well.

And I think maybe the only other point I would raise across the three pillars is that third pillar really is around amplifying our enterprise capabilities and AI. And so there, we have a lot of work happening to transform parts of the business in S&P Global. We talked a little bit about this at the IR Day as well with some of the big efforts we have going on within our engineering teams, our enterprise data office and otherwise.

And so as we look to accelerate some of that transformational work, there may be potential opportunities there on the productivity front or the speed to market front as well over the next 12 to 18 months. But I would highlight really more the market-sensitive businesses on that time frame.

Okay. Let's start with one of those businesses, Ratings. The backdrop seems incredibly strong for Ratings. When I think about things like hyperscaler issuance, obviously, strong economic growth, we have some of the COVID era low bonds coming up for refinancing. Even your results were very strong in the first quarter, double-digit billed issuance. Yet the guidance seems somewhat conservative when I think through the guidance for the year.

So can you just help us understand structurally maybe the framework you think about in terms of a longer-term sustainable growth in the Ratings business?

Yes. So the Ratings business, we came into the year and certainly, when we talk about our medium-term plan, we highlighted what we view as strong tailwinds for the Ratings business over the next 3 to 5 years, including a very strong maturity wall, for example, through 2028 of about $8 trillion, and that is historically high. And so we have, I think, a good position and starting point around the Ratings business as we think about the outlook.

I think for this year, in particular, we came in thinking, obviously, 12-month maturities. We did not make very strong assumptions around pull forward from '27 onwards as part of what we were looking at. And I think importantly, we also made some assumptions around hyperscaler issuance, which has obviously been a key factor this year.

We were assuming around half of the announced CapEx would be financed through debt. And when we look at Q1, we assume that there was pull forward in Q1 of what we were anticipating throughout the year. And so you think about that, we've seen -- obviously, we've seen very strong overall IG issuance even without the hyperscale activity and some strong M&A as well that came through in Q1.

The balance is really between that, the assumptions around the pull forward and then also that little bit of additional uncertainty that we're seeing, whether it is the rate environment such as it is with inflation as well as the geopolitical environment. If we didn't see a major deterioration in the rate environment, the geopolitical environment, there is a possibility that we could see some outperformance on the outlook for this year in Ratings.

Let's switch over to private credit. That has obviously had a lot of noise in recent months. I guess a couple of questions. What are you hearing from LPs, GPs and regulators right now about the state of private credit rating? And more importantly, how do we think about demand for what you offer in private credit, given all the turbulence we've seen so far in that market?

Yes. I think the way to think about this is that additional scrutiny is really increasing the demand for high-quality independent opinions, whether it be ratings, assessments, valuations or otherwise. And so within the Ratings business, in particular, as you know, we've invested over many years in private credit. We have been very engaged across the market.

The asset class in and of itself has become more of a sort of a catch-all for credit that is private as opposed to direct lending. And so we've seen infrastructure, data centers. We've seen asset-backed finance, corporate investment grade across the full spectrum really within the set of issuances that we see coming driven by the GPs and otherwise.

And so the demand for an S&P opinion is high, and we see that in the growth that we've seen over the course of the last 4 years or so. It's growing off a base now that is in the hundreds of millions of dollars. And we will continue to provide our very strong independent assessments. And we think that, that is appreciated and really needed by the investors who use those ratings, whether they be insurance companies, sovereign wealth funds and others.

Okay. How do you think about the competitive landscape in private credit? Obviously, it's a new asset class, deal structures are newer. My sense is issuers are willing to try some nontraditional rating agencies. So maybe just talk through how you view the competitive landscape, what's S&P's differentiation, either product-wise or expertise-wise?

Yes. Well, I think maybe 4-plus years ago, it was actually us being asked to come into a market that had previously perhaps relied on smaller niche providers. And that request from LPs and from GPs was to have a very high-quality S&P Global independent rating. And I think there, the ways in which we think about the value that we provide is, first of all, we have invested in making sure we have the capacity and the expertise, which is incredibly important, particularly given the expansion into so many sub-asset classes within sort of this overall private umbrella.

And the second thing I would say is a consistent methodology. It's credit that is public or private. And we have a methodology that spans, is consistent between both. It's not a different methodology for private. I think that is increasingly important, not just because we've seen issuers take advantage of opportunities to refinance into public markets or otherwise, but also because LPs need to be able to actually track their exposures using a consistent methodology. And that has been, I think, appreciated even more in the past 12 months or so.

And so we're going to continue to provide that consistent view with the investments that we've already made in the capacity and the expertise and continue to engage very heavily, including not just within the U.S., but also in the EU and in Asia, where we've seen increased interest over the past 12 to 18 months from LPs in the asset class also.

Okay. Good. Let's switch over to Market Intelligence. Actually, I think yesterday, you just announced that there's some leadership changes within Market Intelligence. Maybe just talk through what investors should think about that or understand about that.

Yes. Well, it's a large company, S&P, you can expect from time to time that we can have these types of things. I've worked with Saugata for a very long time, and we have a wonderful relationship, and I'm very pleased for his next opportunity. He left a fantastic -- in fact, he's not left yet. He's given us a transition through the end of July.

But I think the work that he's done in the past 1.5 years plus has been phenomenal in really setting up Market Intelligence for success. As you know, the first thing that we announced yesterday is actually the transition of the Enterprise Data Office over to Firdaus Bhathena, who has just joined us as the Chief Technology and Transformation Officer.

And maybe just to highlight that for one second, this is really a great opportunity for us to marry the data organization with the technology organization in the sense that it's the technology that is going to help us unlock the additional value that we see across our very vast data estate across the enterprise. And so that was a very easy decision to make as we examined the implications of Saugata leaving.

I would say if you look at Market Intelligence now compared to where we were 1.5 years ago, we have done with Saugata's team and support from -- across the broader enterprise, we've been able to do a tremendous amount of productivity work, whether it is delayering, whether it is consolidation of incentive compensation programs within the sales organization and the real transformation of the overall sales and revenue organization.

We've also been able to see productivity flowing through from some of the initiatives that we have in technology and in data as well. And so the organization now is set up with durable overarching strategy around developing continued flexibility in our distribution channels and taking advantage of the AI opportunity. And I think, overall, I think a good starting point for what comes next.

Now look, in the past 6 months, I don't think any of us could sit here and say that the technology landscape hasn't evolved massively again in that time horizon. And it's a good opportunity for us to really examine and make sure that we have a prioritization of the investment that we're making in MI that, that is something that we still feel good about. And that if there are opportunities there to advance the integration of AI, for example, in certain areas to really think about how we can accelerate the value we provide for customers, how we can think about accelerating the productivity opportunities that we have, now is the time to do that.

And we're going to take that opportunity to do that as we examine the leadership and structure for the business. It's something that we will do thoughtfully and very quickly. It's not something that we're going to kind of trail out over a long period of time. I think we can -- with the shift of EDO under Firdaus, that's the first very quick step that we made, and we'll move quickly with the rest of this as well. But overall, I think the business is performing well. We affirmed obviously our guidance as part of the announcement that we made yesterday, and I'm excited about the next steps there.

Okay. Let's drill a little bit more into that business and the guidance. And you're right, the business has picked up in terms of growth over the last year or so. But when I just step back and think about the backdrop for, let's say, financial intelligence, data intelligence, it seems pretty robust.

There's AI tailwinds. People are spending more on AI. There's a big capital market cycle. So you would imagine there's a lot more demand for the data and the people that use your data. But growth still roughly is in that 6% type range, which is somewhat at the lower end of kind of a longer-term guidance range. So just help us understand the disconnect between what seems like a very strong macro backdrop for the business versus what we're actually seeing.

Yes. So maybe just to start with contextualizing the medium-term guidance for Market Intelligence as with the rest of the divisions as we issued at IR Day is really an average over a 3- to 5-year time horizon. And so we may see over that or kind of under that over that time period. And so that's a bit of context for where we see today, 2026 and the guidance that we provided.

We've got a couple of factors in here. The first is the end market in and of itself, and we said this at IR Day, is actually growing a little bit more slowly. And so we have to make sure that we are positioned to grow faster than that whether it's taking share or expanding the opportunities and getting into tapping into additional wallets, whether it is in the CIO's wallet or the AI -- Chief AI Officer's wallet. And that's where we're seeing quite a bit of opportunity as we go forward.

I would say the other things to think about here are, look, there's not a single customer that I talk to who doesn't look to us and say, we need you even more now in a time when we have to be able to make sure that we can trust what is coming out of these models. And we've had conversations recently with a very large bank that had used one of the frontier models in a sandbox environment and thought that it was working great and then they put it into deployment and had to shut it down very, very quickly because they couldn't trust what was coming out of it.

And they came to us and said, you must keep investing in your products. We need you guys. Let's talk about an extension of what we're doing with you. And so I think there's -- it's important to understand that the vendor consolidation opportunity is very, very strong. The opportunity for us to partner with our clients as a way to make sure that they're simplifying their vendor stack and getting the most out of our content is really important as well. And as we do that, we take more share and we increase the addressable market within those clients for ourselves as well.

I think some of the other sort of puts and takes on MI in general, I mean obviously, we had and we disclosed we had a revenue recognition impact in Q1 was about 50 basis points and we expect that to reverse throughout the course of the year. And so that gives us good confidence in the guide for the year, including the fact that we're seeing the pipeline building as we continue to go on. So ongoing strength in execution, continued engagement, both with the Chief Client Office as well as through the strengthened and transformed revenue team and just a real focus on delivery for the year.

Okay. Let's unpack that near-term growth. I think you've talked about growth accelerating through the year. Any more specifics as to what drives that?

Yes. I think maybe it was at the risk of repeating myself, I apologize. We've had the revenue recognition piece that I talked about. The pipeline build is incredibly important. I would say, in addition to the pipeline build, we've seen very strong results around retention, and we track that very, very closely.

So we look at retention, we look at cancels, we look at the sales pipeline build, the conversion of that. We've seen a compression of the sales timelines or the sales cycles, which we're tracking very closely as well with the MI commercial organization and with Chief Client Office. And so these are the things that we continue to examine and that inform our view in the full year.

Can we just talk through in an AI world, how you monetize this -- the MI business? I think in the world of MCPs, if we think about -- if we imagine your business being more the back end to an LLM front end, how do you think about pricing the business and monetization in a world where maybe the desktop and things like Cap IQ Pro are not as relevant anymore or not the primary interface into tapping into your data?

Yes. Look, I would maybe lay out a couple of starting principles around how we think about this. And I'll answer this specifically in the context of MI, but I think it's fair to say that we would -- we use the same principles across the organization where we're selling data. So the first thing is that we will retain and we do retain the relationship with the customers, the end customer. The second is that the end customer is looking for S&P Global's answer. They're not necessarily looking for Provider X's answer. And it's real key, particularly with that investment bank client that I mentioned was like we do not trust the answers that we were getting. We need you. You must keep investing in your products. We want to make sure that we're getting like -- we need to continue our day-to-day, and we can't be distracted by answers that we don't trust, right? So that's incredibly important.

I think the other thing that we would talk about or that I would sort of set the stage on here is it is not a new thing that we are distributing through a third party. We've distributed through third parties for a long time. Most recently, we saw this big shift about 5 or so years ago with Databricks and Snowflake with -- and I remember at the time, I guess it was a little bit longer than 5 years ago, being nervous when I was part of MI that Databricks and Snowflake would disintermediate us in some way. And actually, if anything, they actually gave us a pretty big uplift in terms of growth around the data. And so I think that these are all things to take into consideration as part of this.

And then I suppose the other point that I would make is, for us, as we work with our customers, there are a lot of customers who are going to continue using the desktop and expect us to build an AI native experience in the desktop, which we're doing. And then there are very sophisticated clients, particularly those who we work with through the CCO, who will have their own internal AI interfaces. And they still want to see the S&P Global answer. And more now, I think as we're seeing how they're developing, they're also interested in actually the skills that will teach their agents to get the S&P Global answer that is grounded in S&P Global standards, S&P Global metadata, the linkages between data sets. They don't want to get into the data management business themselves.

And so I consider it as a different way of experiencing the desktop interaction. And honestly, in that environment, trust is paramount. I think the value of our IP is even higher. And so these are the ways that we're working with our customers, and I think we're getting very, very good, very solid results out of those conversations.

Okay. Let's talk through enterprise pricing. You guys are famous for doing enterprise pricing. You're not very seat-based. Your competitors have copied that model. But how do you think about an agentic world, agents running around doing tasks? How does that impact the way you price? Are you beginning to think about that this year?

Yes. I'll answer this question more broadly also, again, sort of a philosophical response, whether it's MI or otherwise. For us, whether it's an agent or a human being, the value that we provide is in the use case that's being used for the access channels, right? So number of channels, the types of functions that are being used, whether it's agentic or otherwise. And there are many more inputs that go into determining the price, right? So we can tell with the increase in API calls, for example, which clients have already started deploying agents against our data.

But for us, it's very much a case of, look, it doesn't matter if it's an agent or a person. The value that we deliver is continuous, if you like, regardless of how many people are actually using it, right? And in many ways, I think it's even higher for the reasons that I mentioned around needing to have that ground trust and the response that you're getting out of it. And so that's how we think about the value proposition for customers and with all the other pieces that I mentioned around the philosophy of ensuring that we retain the ownership with the customer, the direct customer as well.

I think you talked about you are seeing some good AI usage. I think on the last call, you talked about a 5x increase in API calls. How do we think about that flowing through if you're in this enterprise model, enterprise pricing, is that a 2026, 2027 renewal discussion? Or are you thinking about more usage-based type pricing that should allow some of your value pass through to the P&L?

Yes. So that's going to be with the enterprise model, that's going to basically come through the renewal cycle, right? So there are opportunities that we're seeing right now to actually have an upcharge to the renewal cycle already with turning on AI-ready data for clients. It's very early days. We did give some examples in our Q1 earnings call with clients willing to pay anywhere from 35% to 45% more to get the AI-ready version of a data set at the renewal.

I would say that we've got some really interesting conversations going. I mean, one very fascinating example is a large global bank that we worked with in Q1. And this is a very sophisticated institution that did two things with us, which we think are emblematic of the direction that we'll see the vast majority of our larger clients going. The first is that they actually renewed Cap IQ, but also expanded the use cases for Cap IQ. And that is because they very much like the native AI capabilities that have been built in there. but they also subscribed to AI-ready data and made our AI-ready data their data standard for their internal AI platform.

And so these are the types of things that we're seeing with even the most sophisticated of our clients, which I think is a very important signal around the value that they get from S&P Global, whether it is through the AI data or the actual web-based solutions as well.

Okay. I got a couple of more AI questions, but I think I'll -- let me move on to something else. Let's move on to energy and your commodities business. Obviously, a lot going on generally in energy markets here and also in your business, some near-term headwinds from the Iran conflict, et cetera. Maybe just step back and help us think through what sort of normalized growth for that business looks like? Are there any drivers that could -- that excites you over the next couple of years?

Yes. So I look at that business, and it's an incredibly, I would say, strategic and resilient business in the sense that we are the sole provider of Brent crude essentially across the markets. And I actually, a couple of weeks back, visited with our Market-On-Close team in London, who've been, as you can imagine, working very, very hard to take in all of the volatility in the markets and manage that price.

We do 15,000 price assessments a day. The uptick that we have seen in Q1 on the consumption of our data, our research, et cetera, has been quite significant because we are the only provider of these insights in many cases. We have also seen some challenges in the end market, particularly in areas where there was a huge dependency on oil and gas through the Strait of Hormuz, whether it's in Asia and other regions. And so that's reflected a little bit in some of the comments that we provided in the first quarter earnings call.

I think over time, the business itself is just very, very strong, particularly on benchmarks research and the unique IP that we have. And as we also talked about, we've divested the Upstream software portfolio, which was a portfolio of very niche and specialized software applications to Schlumberger. And with that, the Upstream turnaround is now connected to our new product, Titan, which has gotten really, I would say, very positive reception from our client base in Energy, and we'll expect the benefits of having launched Titan to show up over the next several quarters as we continue the transformation of Upstream. So overall, I think the energy business is very, very well positioned going forward, notwithstanding some of the near-term headwinds.

Okay. Perfect. Move over to Index. That's been a very fast-growing business for you, very high-margin business and really centered around your flagship sort of S&P products. Over time, how do you think about sort of the long-term product roadmap to help you diversify with maybe other asset classes like fixed income and private markets and just be less reliant on the core equities business?

Yes. The team has been very successful at innovation, particularly over the last several years, and I'm very excited about Cathy Clay and what she's doing with the team as well going forward. I've seen incredible opportunities and growth in fixed income with the iBoxx franchise, multi-asset class as well as in the liquid derivative ecosystem as well. And so the team is really going to continue to execute. You've seen them do that with strong growth as well as very strong margins.

And I think just a couple of things that got me quite excited in the first quarter there. One was the first digital native U.S. treasuries index that we launched. And we also launched in partnership with Lincoln, a first-of-its-kind private loan series, index series as well covering the U.S. and Europe. And so lots of incredible innovation there, and I think the team is going to continue to go from strength to strength on that. Those areas can be areas that grow very fast, obviously, off a smaller base. And so we continue to see really good signals in the business.

Perfect. Mobility and the spin. So I think that goes live July 1. Beyond the financial cleanup, how do you think about the RemainCo going forward, the identity and competitive position of RemainCo? So for an investor who's seen the company or talking about -- look at the company for the first time, how would you describe the difference in the company post RemainCo -- with RemainCo versus what it is today?

Yes. Well, obviously, with Mobility, I mean, we're excited -- I'm excited for that team, and they had their Investor Day recently. So I don't need to mention anything else about the Mobility business. RemainCo is the strategy that we presented at our IR Day. And so think about advancing Essential Intelligence, our market leadership in our core markets like Index and Ratings and Energy and in the vast amount of work that we do across the entire credit ecosystem in our Enterprise Solutions business, for example.

And then we've also talked about high-growth adjacencies like private markets and the work that we're doing there, whether it's in Ratings, in Index with the example that I just provided and also in being able to really harness the full power of AI. Perhaps maybe some of the comments I would make here, that guidance that we provided for the medium term includes ways in which we continue to prioritize shareholder value, whether it's distributing 85% or more of our adjusted free cash flow through dividends or buybacks, ongoing focus really on margin growth and margin acceleration as well as the revenue side.

And maybe one thing I would say is that when we provided that medium-term guidance, it was provided not assuming that we would do heavy transformation with AI. And with our new Chief Technology and Transformation Officer, heavy transformation is on the agenda. And so I think there are opportunities for us over that 3- to 5-year time horizon to do more around growth and productivity as we unlock the full potential of AI as well.

Okay. And when you say transformation, you mean revenue benefits or more margin?

It can be both. So if you look on the one hand, we have our Enterprise Data Organization by the end of this year, we'll have really added quite a lot of our data to our data fabric. Maybe just to give you some context, the AI-ready data that we have out in the market right now is what I would characterize as a handful of data sets in the context of the broader data estate that we have. We chose those data sets because they have the highest sort of use case application, if you like. As we get to our higher value and even more unique data sets in our data fabric, linked, connected, AI-ready, the possibility of unleashing AI on that is interesting. And so we'll work through those opportunities.

And then on the productivity side, we have the ability now to take some of the work that we talked about at our IR Day, whether it's across our research teams, whether it's taking a deeper look at the Enterprise Data Office and the productivity initiatives we have there, agentic SDLC, for example, in our engineering teams, there are opportunities really to go further with our workforce transformation there as well.

And just a quick follow-up on the RemainCo and post Mobility spin. What does it mean practically for you as CEO? Is it you have more time? Do you have more capacity? How does it -- how does spinoff a big division sort of impact your ability to manage the business?

I would say that I have been very focused in ensuring that we have -- we've got the right strategy for RemainCo and very focused on engaging clients, partners, stakeholders and otherwise around S&P Global and the 4 core divisions. We had a very senior and very competent SpinCo management team that included folks from our finance team as well as obviously Bill and his team. They have that well in hand. And I've been very focused on S&P Global and the growth trajectory for S&P Global.

You touched on this a little bit, but let's go back to your sort of expenses and your margin framework and how you think about that going forward. The company moved from sort of setting margins at a segment level to an overall 50 to 75 basis points annual expansion. And obviously, the folks talk about that to be market-driven, et cetera. Maybe talk through why you've changed the framework to go to an overall margin framework versus segment and any advantages that gives you going forward?

Yes. Look, it's intended to allow us to actually report the business the way we manage the business. And we have moved, I think, as is pretty clear at this point to a more enterprise model. And that enterprise model has EDO running across all of the divisions, technology now under Firdaus running across all of the divisions, CCO running across all of the divisions, et cetera. And so this gives us the opportunity to really put on an accelerated path those enterprise capabilities as part of that third pillar of our strategy around amplifying enterprise capabilities, including AI and to deploy those in ways that benefit all of the divisions. And that allows us then to make the proper targeted investments where they have the best return for the business, for shareholders and for our customers.

And so we're going to do what makes sense there. I would say that, that flexibility at the enterprise level makes it actually a little more simplified in terms of how we're going to operate the business going forward. So instead of having 4 versions of a technology strategy, there's one technology strategy, one set of capabilities, et cetera, the same thing with the Enterprise Data Office. And so those are good ways to be able to actually affect and manage the businesses because in some ways, we have more than half our employees, for example, in those 2 functions alone and being able to actually make decisions there that can flow through and benefit the divisions like Market Intelligence where we can actually really bend the curve on margins, I think that's very important.

Okay. Switch over to M&A. How do you think about using M&A to grow the business? You've done a couple of tuck-ins as CEO right here. But where do you see the most opportunities and which businesses would benefit most from inorganic growth?

Yes. I mean, look, to put a fine point on it, at this point, with the valuation the way it is, any deal, even a tuck-in size deal, quite frankly, would have to hit a really high bar for it to be a better outcome for shareholders than returning to shareholders. And so that's where we sit right now. We've also said no transformational M&A. And generally speaking, tuck-ins that are aligned either with the core areas where we have market leadership or in the transformational or the high-growth adjacencies.

But I come back to where we are right now, and we're always going to be very thoughtful about uses of capital and what is best for shareholders and the business. And so right now, it's with a fine -- a very fine assessment of where we are in valuation.

Okay. Good stuff. I've got a few audience questions, so I'll just try and summarize them. A couple of them seem to just talk through, again, AI and risk of AI. So something along the lines of as LLMs get more sophisticated, they can maybe do a lot of the data cleaning, a lot of the data work or data management work that you've talked about has been somewhat of a competitive advantage for you. So over the long term, as that happens, how do you think about sort of pricing power for your business in a world as LLMs get better and better?

Yes. Look, the vast majority of our IP, whether it is data, research, et cetera, is actually not available publicly. And so for there to be a thesis that the value that we provide through the IP is lowered because an LLM can sift through data more quickly, you'd have to assume that the LLM has open and free access to all of that data, and that's just simply not the case, right? So I think for us, it is to continue to make sure that the unique content and IP that we have is front and center that we are protecting and continuing to grow that IP so that we can actually realize the value of that, whether it is through our own channels or through some of these LLM channels as well.

And look, I go back to the example of the investment bank who said like, listen, we can't -- trust is paramount, right? And it may be one thing to say, give me an answer on a financial, et cetera. But if you can't put that into the context of your entire book of business or your portfolio or you can't link it, et cetera, it's not going to be useful for you in your day-to-day.

Another one more on the Ratings business, just around the rates environment as we see rates tick higher here, how do you think that impacts your Ratings business?

Look, I think this is one of the reasons why we're being thoughtful about Ratings and the outlook for the full year. It includes how we think about the rate environment as well as how we think about the geopolitical environment.

Okay. And then last one, kind of focused on M&A, but thinking through to the extent you want to get bigger in things like risk intelligence, RegTech, maybe more of a focus on data and network businesses versus workflow. But yes, I don't know if there's any thoughts.

Yes. Look, I would say that the bar is very, very high. And I would be -- again, I won't go back to the sort of the valuation piece of it, right? If you set that aside, I would say the bar is extremely high. It has got to be something that is very unique, not available elsewhere. It's got to fit the profile of our own unique IP. And we will be very, very thoughtful about where we add. I will certainly say that we're going to be extremely thoughtful about not adding in areas where we have, let's say, higher concentrations of undifferentiated content like MI, for example. And so again, we'll be very, very thoughtful, but it's going to be things that reinforce the network and the moats that we have today.

Okay. Maybe just lastly for me to wrap it up. I mean you've mentioned stock value here. And obviously, we can see the prices. It sounds like there's a lot of momentum in the business on the Ratings side. Even MI, we're seeing nice momentum. There's a lot of scope for margin improvement, as you've talked about. What do you think investors are missing?

Yes. Look, I -- it's a benchmarks business predominantly. It's 2/3 of our revenue, 3/4 of our profit. And as much as we get so many questions on Cap IQ Pro, it's less than 6% of our revenue and even lesser than that of our operating margin. And I think that's a really important point. It's also important that in this moment that we have an opportunity to think a little bit about our investment priorities within Market Intelligence and make sure that those priorities are aligned with direction of travel of our customers and that we can accelerate the integration of AI.

People will often say to me, "Oh, it's hard to disprove a negative." I want to focus on the positive, which is that we have an incredible business. We are the only providers of the S&P Global Ratings, the only providers of the S&P 500, the only providers of the Platts Brent crude benchmark. And that is something that is unique to S&P Global and will continue, is deeply moated, deeply entrenched in the global macro environment and will continue to be so. And so that is the last message, if I could, that I would leave you with.

Fantastic. On that upbeat note, we'll end it. Thank you very much, Martina.

Great. Thank you.

Good morning, and welcome to S&P Global's 2026 Annual Shareholders' Meeting. I'd like to inform you that this meeting is being webcast. [Operator Instructions] The meeting is being recorded. I'd now like to introduce Judah Bareli, Corporate Secretary of S&P Global. Mr. Bareli, you may begin.

Good morning. My name is Judah Bareli, and I am the Corporate Secretary of S&P Global. It is my pleasure to welcome you to our 2026 Annual Meeting of Shareholders. Before passing the meeting over to our President and Chief Executive Officer, Martina Cheung, who will provide an update on the company, I'm going to briefly address some of the virtual meeting logistics and provide some introductory remarks regarding the information presented during today's meeting. You will be able to submit written questions through the virtual meeting website. On the site, click the Q&A icon, type your questions in the field provided and hit the send button to submit your question. Shareholders may submit questions online at any time.

In the interest of a productive and orderly meeting, please consult the 2026 Annual Meeting Rules of Conduct available under the Documents section of the virtual meeting center screen for guidelines and additional information regarding the process for submitting questions online. We appreciate your participation and courtesy in observing these rules of conduct.

After the formal portion of the meeting is adjourned, we will have a brief Q&A session. We will answer as many questions that comply with the posted rules of conduct as time permits.

With that, let me turn the meeting over to our President and Chief Executive Officer, Martina Cheung.

Good morning, everyone. Thank you for joining our Annual Meeting. 2025 was a year of strong execution for S&P Global. We delivered excellent results and advanced our strategic priorities. We launched our medium-term strategy centered on 3 objectives: advance our market leadership, expand into high-growth adjacencies, and amplify our enterprise capabilities and AI. We are delivering on our strategy under our mission of advancing essential intelligence.

On a year-over-year basis, revenue increased 8% and adjusted operating margin expanded 140 basis points, while adjusted diluted EPS grew 14%. This performance reflects robust demand for our benchmarks, data and analytics. We remained highly disciplined in capital allocation, returning 113% of our adjusted free cash flow to shareholders through dividends and share buybacks. We are a trusted partner to our customers, and that trust underpins the demand we see across our businesses. Our benchmarks and proprietary data enable our customers to make critical decisions every day and bring transparency to opaque markets. The message is clear and consistent. S&P Global is uniquely positioned to help our customers to be successful and solve their most complex challenges.

For example, we strengthened our position in private markets, one of our high-growth adjacencies. We completed the acquisition of With Intelligence, expanding our private markets data and workflow capabilities, significantly enhanced our iLEVEL platform with new AI features, and launched new private equity benchmarks and indices. We also partnered with Cambridge Associates and Mercer and saw continued growth in private credit ratings. Together, these actions put us well on our way to building the most comprehensive solution set in the world for private markets.

At the same time, we invested in enterprise capabilities to drive innovation and efficiencies. 2025 was the first full year for our Enterprise Data Organization and Chief Client Office, and we've already realized material benefits from these initiatives. We unified our data operations within the Enterprise Data Organization to better meet customer needs for flexible delivery and AI-ready data, while increasing productivity. The Chief Client Office enabled us to bring the full enterprise value proposition to our clients. It also elevated our engagement beyond business leaders to include their heads of technology, AI and data science, giving us earlier insight into customers' needs and challenges and enabling us to co-develop new solutions, including through Kensho Labs.

As I look back over 2025, we had an excellent year, and we're very pleased with the results we delivered. We delivered strong financial performance and bolstered our capabilities for future growth. We have a clearly defined strategy, an incredible team, and deeper customer partnerships than ever, all of which give us confidence in S&P Global's long-term success.

On behalf of the more than 40,000 colleagues at S&P Global, thank you for your support and partnership. We are confident that the steps we took in 2025 have positioned us well to continue creating value for our customers and shareholders with momentum in how our people are innovating in our customer engagement and in our collaborations with technology partners.

Before I conclude, I would like to acknowledge Bill Green, who is retiring from our Board today. Bill, thank you for your amazing leadership and 15 years of service to S&P Global.

I will now turn it back over to our Corporate Secretary. Judah, please proceed with the meeting.

Thanks, Martina. We will now begin the business portion of today's annual meeting. Please be advised that we have certified lists of the shareholders of record as of the close of business on March 23, 2026, who are entitled to vote at this Annual Shareholders' Meeting. Such lists are available for inspection by any shareholder using the link at the bottom of the virtual meeting center screen. Copies of the Notice of Meeting, Proxy Statement, Annual Report, Rules of Conduct, and Affidavit of Mailing relating to this annual meeting are available in the Documents section of the virtual meeting center screen. The affidavit will also be filed with the records of the annual meeting.

The Board of Directors has designated a representative of Computershare Trust Company to act as Inspector of Election for the annual meeting. Harold Murphy, a representative of Computershare Trust Company, is available in virtual attendance today. Harold Murphy has been duly sworn in, and his oath will also be filed with the records of the annual meeting. In addition, the holders of a majority of the shares of common stock entitled to vote at this annual meeting are represented either in person or by proxy. Mr. Chairman, the annual meeting has been duly convened, a quorum is present, and the business of the annual meeting may proceed.

Ladies and gentlemen, I'll now pass the business portion of today's meeting over to our Chairman, Lord Ian Livingston.

Thank you, Judah, and good morning. My name is Ian Livingston, Chairman of S&P Global. With a quorum present, I call the meeting to order. Before we begin the formal part of today's meeting, I would like to introduce our Directors, all of whom are present and in virtual attendance today. In addition to myself and Martina Cheung, who opened the meeting and is a Director as well as President and CEO, I would like to introduce the rest of the Directors, all of whom are Independent, who will stand for election today, along with Martina and myself; Marco Alverà, Jacques Esculier, Stephanie Hill, Rebecca Jacoby, Hubert Joly, Robert Moritz, Maria Morris, Gregory Washington.

It is clear we have a world-class Board. All of our directors have broad experience, excellent judgment and take their fiduciary responsibilities very seriously. At this time, I would like to echo Martina's remarks about Bill Green, who is retiring from the Board today. On behalf of the entire Board, I want to thank him for his distinguished service and contribution to the company. He has served the company and our shareholders with integrity and commitment. Bill, thank you.

We will now proceed to the formal business of our annual meeting, the purpose of which is to: one, elect 10 Directors; two, approve, on an advisory basis, the executive compensation program for the company's named executive officers as described in the proxy statement; three, ratify the appointment of Ernst & Young LLP as the company's independent registered public accounting firm for 2026; four, vote on a shareholder proposal to reduce the stock ownership threshold for calling a special shareholder meeting; five, vote on a shareholder proposal to issue a report on the company's charitable support; and six, consider any other business, if properly raised.

It is now 8:39 a.m. Eastern Daylight Time on May 20, 2026, and the polls have been opened for voting on all matters. If you have already voted, your vote has been tabulated, and there is no need to vote again. If you have not voted or if you want to change your previously cast vote, please do so by clicking on the Vote tab on the virtual meeting website. The vote link will be available until we announce the closing of the polls after the presentation of all matters for shareholder consideration.

Please remember that if you have already sent in a proxy or voted by telephone or over the Internet, it is not necessary to vote again. Once the polls close, the inspector of elections will provide his preliminary report. As a reminder, please note that time will be provided to shareholders wishing to ask questions during a general question-and-answer session at the end of the formal portion of today's meeting.

The first item to be voted upon is the election of 10 Directors, whose names are listed in the proxy statement. The second item to be voted upon is the proposal to approve, on an advisory basis, the executive compensation program for the company's named executive officers as described in our proxy statement. The third item to be voted upon is the ratification of the appointment of Ernst & Young LLP as the company's independent registered public accounting firm for 2026. Dan Kilduff, the Ernst & Young partner responsible for S&P Global, is in virtual attendance at today's meeting and is available for questions.

The fourth item to be voted upon is the shareholder proposal to reduce the stock ownership threshold for calling a special shareholder meeting. Mr. Chevedden, we will now open the line for you to present the shareholder proposal. In accordance with the annual meeting rules of conduct, 2 minutes have been allocated for you to present your statement. Mr. Chevedden, you may begin your remarks.

Hello. This is John Chevedden. Proposal 4 gives shareholders a reasonable ability to call for a special shareholder meeting. Shareholders request the Board of Directors take the necessary steps to permit written consent by the shareholders entitled to cast the minimum number of votes that would be necessary to authorize an action at a meeting at which all shareholders entitled to vote thereon were present and voting. This includes shareholder ability to initiate any appropriate topic for written consent. S&P Global shareholders have a particular need for the right of 10% of shares to call for a special shareholder meeting because they have no right to act by written consent. According to state law, S&P Global shareholders can have a right to act by written consent and the right to call for a special shareholder meeting. Both rights allow shareholders to take action between annual meetings.

It is especially important for S&P Global shareholders to have the right for 10% of shares to call for a special shareholder meeting, because S&P Global requires a backing of 25% of all shares outstanding to call for a special shareholder meeting. The reason that a 25% figure is too high is that shareholders at more than 100 companies have had an opportunity to vote on the special shareholder meeting topic, and there has never been even one example produced of a special shareholder meeting ever taking place at any company whatsoever that required 25% of shares to call for a special shareholder meeting. Companies like the 25% figure because they know the 25% figure is more like an insurance policy that a special shareholder meeting will never take place.

It is important to adopt a shareholder right, because the current S&P Global right to call for a special shareholder meeting is unattainable and S&P Global shareholders have no right to act by written consent. Also, this is a black mark on Computershare for this meeting. The online platform went dead and the telephone line went dead. So another black mark for Computershare in running annual meetings. Thank you.

Mr. Chevedden, thank you for your remarks. The Board of Directors unanimously recommends that you vote against the proposal based on the reasons set forth in the proxy statement.

The fifth item to be voted upon is the shareholder proposal to issue a report on the company's charitable support. Prerecorded remarks have been provided to the company from Boyer Research to present the shareholder proposal from the Heritage Foundation. In accordance with the annual meeting rules of conduct, 2 minutes have been allocated for the statement presentation. The presentation of the prerecorded remarks may begin.

My name is Stefan Padfield, and I'm a Principal at the Free Enterprise Initiative, which is part of the Heritage Foundation. The Heritage Foundation is the proponent of Item 5, which requests a report on risks associated with S&P Global's charitable support. The company's statement and opposition can be boiled down to urging shareholders to trust the status quo. But how can shareholders trust the status quo when that is precisely what has led to the company scoring 100 on the Human Rights Campaign's Corporate Equality Index, which our proposal makes clear constitutes a red flag that the company is risking material reputational and other harms by promoting transgenderism.

Notably, the company's opposition statement does not even mention the human rights campaign, nor does it mention that the 1792 Exchange rates S&P Global a high risk on its corporate bias ratings for reasons including the HRC score in addition to concerns related to using Benevity for charitable donation screening purposes, which potentially implicates S&P Global in discriminating against mainstream advocacy organizations through the recently indicted SPLC's overly broad hate list.

Another red flag calling into question the company's status quo is a recent letter from a coalition of 23 states questioning the lawfulness of the ESG policies of S&P Global Ratings. This letter was led in part by Nebraska Attorney General, Mike Hilgers, and raises the specter of undisclosed and unlawful material conflicts of interest as well as concerns related to antitrust violations and deceptive trade practices, all connected to the company's embrace of politically charged ESG. The foregoing list of red flags suggesting biased decision-making at S&P Global should make it difficult for shareholders to trust the status quo, and shareholders could further be forgiven for wondering whether such bias may explain the company's poor performance, which apparently includes underperforming the S&P 500 in the past 5 years to the point of roughly 60 percentage points. A second look at S&P Global's charitable support in light of all the foregoing should be a part of ordinary oversight.

The prerecorded remarks have now concluded. The Board of Directors unanimously recommends that you vote against the proposal based on the reasons as set forth in the proxy statement. The polls are about to close, so if you've not yet voted, please do so now.

[Voting]

It is now 8:47 a.m. Eastern Daylight Time, and the polls are closed effective immediately. This concludes the voting on all formal business items.

The preliminary tally of votes by the Inspector of Elections shows that: one, the 10 persons nominated as Directors of S&P Global have all been elected; two, the proposal to approve, on an advisory basis, the executive compensation program for the company's named executive officers has been approved; three, the ratification of the appointment of Ernst & Young LLP as the company's independent registered public accounting firm for 2026 has been approved; four, the shareholder proposal to reduce the stock ownership threshold for calling a special shareholder meeting has not been approved; and five, the shareholder proposal to issue a report on the company's charitable support has not been approved.

The certificate of the Inspector of Elections will be filed with the records of the meeting, and the final results will be available on or before the 26th of May 2026 in a Form 8-K filing. There being no further business, the formal part of our annual meeting is concluded. I now declare the meeting adjourned.

Before passing the meeting over to Martina Cheung, let me take a moment to thank our shareholders for their continued support. The number of shares voted and the support demonstrated is very much appreciated. Martina Cheung will now lead a general question-and-answer session. Martina?

Thank you, Ian. We will now open the meeting to questions. Judah?

With no further -- there are no questions at this time.

Since there are no comments or questions, we will conclude the annual meeting. We thank all of our shareholders for being part of this meeting and for your support of S&P Global. Thank you again very much for tuning in.

That concludes this morning's call. A replay will be available within 6 hours from investor.spglobal.com and will be maintained for 12 months from today. On behalf of S&P Global, we thank you for participating.

Well, good morning, everyone, and welcome to Mobility Global's 2026 Inaugural Investor Day. My name is Tejal Engman, and I lead Investor Relations at Mobility Global. It is fantastic to see so many of you in the room and so many more of you on the webcast. It's great to have you join us.

So we're going to have a very action-packed morning for you today. But first, I'm going to make the lawyers happy. So we're going to go into a few things on this disclaimer slide that it's important for me to mention, which is that this presentation is being recorded and webcast, and the presentation today will contain forward-looking statements within the meaning of U.S. and international regulations. Any such statements are based on current conditions and subject to risks and uncertainties, which are discussed at length in our Form 10 filing with the SEC.

As you know, Mobility Global plans to complete its spin from S&P Global to become an independent public company in mid-2026. And our discussion today will focus exclusively on Mobility Global with the financial outlook reflecting the company on a stand-alone basis.

We'll also be discussing non-GAAP financial metrics. We filed an 8-K this morning with information regarding these metrics and the financial targets that we'll be discussing today. And everything is available, the deck, the 8-K, et cetera, on S&P Global's Investor Relations website.

Okay. Now for the fun stuff, we have a very exciting and very informative day for you today. We're going to kick off with our CEO, Bill Eager, who will talk to us about his strategy and vision for Mobility Global. We're then going to move into B2B solutions with Joe LaFeir, the President of that division, who will talk to us about planning as well as sales and marketing. And then we're going to have a break for 15 minutes.

Many of you have seen the product demos that are outside. Please do spend time with them in the break. And we'll come back after the break to CARFAX with Scott Fredericks, who's the President of CARFAX. We'll have a data, technology and AI section with our Head of AI, Jeremy Morehouse. And that will be followed by the session that you're all waiting for, our financial framework section with Matt Calderone. There will be a Q&A session after that, where you'll have plenty of time to ask your questions. We'll also be taking questions from the web. So please, on the webcast, folks there, feel free to submit questions, and we'll select and address as many of those as we can. And after all of this, we invite you to please join us for lunch and spend more time with the product demo stations outside. So great.

With that, I'm going to introduce you all to someone very important at Mobility Global, the CARFAX.

[Presentation]

It's my pleasure to introduce someone who's dedicated the past 3 decades to serving the mobility market. Please welcome President of S&P Global Mobility, CEO of Mobility Global, and my friend, Bill Eager.

Thank you, CARFAX. As CARFAX mentioned, I'm Bill Eager, CEO of Mobility Global, and I want to thank everyone for being here today. We're really looking forward to sharing our story with you, sharing the opportunity that we have and our plans for going after it. We've had the honor of serving the auto industry for over 100 years. We were there for the Model T all the way to the Tesla 3 and every model in between. Today, there's over 1.5 billion, billion with a B, vehicles on the road globally. And every year, another 90 million new vehicles are built and sold.

Now at Mobility Global, we have a mission. And that mission is to provide trusted information to billions of people to build, sell and own vehicles with more confidence. Now for most of us, our vehicles will be the second largest purchase of our life, only behind our homes. And a car, a car is never just a car. Our vehicles become a part of us. They're a reflection of us and where we are in life. They're how we get to school, to work, to practice, the grocery store. Our vehicles are what we load up when we go off to college or on a family vacation. I apologize for the sound of my feet here.

But we look forward to that day, that day we finally get our license. How many people in here remember their first car? I see a bunch. But the first car at least that you had access to. I remember mine. I come from a big family. It was a 15-passenger van, big blue van. I eventually went and bought a Ford Country Squire station wagon, high mileage, wood paneling and all. And I love both. I love both those vehicles and the freedoms they afforded me.

Now today, we're going to throw a lot at you. We're proud of the business that we've built, and we want you to understand it. But if I could ask you to hone in on 3 things, just 3 things today. The first one is the market we serve, the massive $8 trillion a year automotive market and the runway that that's created for our business. Second, the assets that we have built to go after that runway. And then the third thing is our opportunity, the people, the team that we have, the strategy we have, the setup that we have that you'll hear about today to take those assets and go do it.

So let's hop right in. Here's what I plan to cover. I plan to give you just a high-level introduction to Mobility Global, some of the numbers and how we make money, where we operate. Then I want to go into those assets that I was talking about, and you'll hear quite a bit about them throughout the day. It's a big part of our business. Then I want to give you a taste of my vision for the business over the next 2, 3 years and then why we believe it's a compelling investment. So let's hop right in.

I'll start with revenue. Our revenue has been subscription first. The majority of our revenue is recurring. Now that subscription model has allowed us to give our customers overwhelming value over the years in all parts of our business. Now we operate in 2 segments. The first run by Joe LaFeir, and you'll hear from Joe next, is 35% of our revenue, and it serves OEMs, suppliers, dealers. After Joe, you'll hear from Scott Fredericks, who runs our CARFAX business, which is 65% of our revenue. And CARFAX is hyper-focused on the automotive information needs of consumers. Both are scaled, both are growing and both reinforce each other.

Now here are a few highlights from last year. You can see we had solid revenue growth at 8.5% and a healthy margin. I'll give you 2 stats from Joe's world, the B2B world. The first one is we do business with 40 of the top 40 OEMs around the globe. That's 100% and 94 of the top 100 suppliers. Two stats from Scott's world. Scott and the team do business with over 40,000 dealers and have a direct relationship with over 53 million consumers, helping them manage their vehicles in the U.S. and Canada.

Now if you look at these numbers at first glance, you've got 40 of the 40 top OEMs in Joe's world. Bill, where is the opportunity? But if you sat down and talk with Joe's folks and they're here today, they'll tell you we haven't hit the 50% mark on the stuff we can sell those 40. And on the 53 million number, that's Scott's world. If you talk to Scott, Scott would tell you, we're really, really pleased that we have 53 million consumers in a direct relationship with them. It's really, really hard. And nobody else has that in helping them manage their vehicles. But his goal in the U.S. and Canada is not 53 million, it's 150 million, and it's 1 billion globally. So when I look at that number and Scott looks at that number, we say we're 5.3% of the way there. Lots of opportunity.

Now the automotive space today is going through massive, massive amounts of change. You've got electrification. You've got supply chain issues, autonomous driving, affordability issues, chip shortages, changing consumer demands, just to name a few. And the convergence of these trends is just causing a tidal wave of change in our industry. And that change is driving up demand for data.

Now you'll see this slide a couple of times in my presentation. And in order to understand our business, you have to understand we operate across the entire automotive ecosystem, serving the 2 life cycles that matter most, those building the 90 million new cars and selling those new cars each year. That's the one on the left. On the right, providing information to the owners of the 1.5 billion vehicles around the globe.

The first one, and that's our B2B business run by Joe LaFeir. In that space, we're serving that new car market. Every new car creates thousands and thousands of questions and decisions. And the OEMs and the suppliers and the dealers, many of those people making those decisions rely on our data to do it.

And on the right side, that life cycle, that's the CARFAX life cycle. Scott and his team, they partner with OEMs and dealers to get our information in the hands of consumers as they shop, buy, service and sell their vehicles. Now this process benefits the dealer because when the dealer puts our products into that process, they sell their cars faster and they sell them for more money. And they create a much better shopping and buying experience for the consumer. And in that part of our business, we monetize primarily through dealer subscriptions, some direct from consumer.

Our history, I have to touch on our history. We got started in the information space in 1870, 1870 when R.L. Polk started this business. It was a directory business. We got our start in automotive in the 1920s with a partnership with Alfred Sloan of GM and then Henry Ford, providing them the critical information they needed to grow those great businesses. Then 60 years later, in Columbia, Missouri, 1984, Ewin Barnett started the CARFAX business, some say in a garage, but I think it might have been at his kitchen table with one file, 10,000 records and a dream. He wanted to help local consumers avoid really bad cars, and that's when CARFAX started.

Now when you start a category like that, you hope that your brand becomes synonymous with it. And we've been really fortunate in the Automotive business to have that happen multiple times. I'll give you one example. In the vehicle history business, consumers don't ask for a vehicle history report. They ask for CARFAX.

So let's hop in and take a look at some of these core assets that we've talked about. These are our core assets. If you want to know what we've done for 30 years, where our focus, our time, our money has been spent; it has been spent here. We're hyper focused on it. These are our core assets. It's our data estate. It's our brands. It's the network that we've built, and it's how embedded we are throughout the industry. And before I go and touch upon a couple of the things here, Scott and Joe will both go into far more detail. I want to hit on 2 things: One, how we built them; and two, the way they interact.

The way that we built them, we built these through a strategic lens. We didn't just build them willy-nilly. We built them with purpose. And as we built them, as we went after our data estate that you will see has over 177,000 sources, we're asking, is it unique? Is it differentiated? Can somebody else do this? We're asking those strategic questions that have led us to the differentiated assets that we have.

My second point is that this is a flywheel. This is the type of thing where one asset grows the other, and both Scott and Joe will give you some examples. I'll give you one though just to put it in context. I mentioned the 53 million consumers that Scott and the CARFAX team have in our CarCare app maintaining their vehicle. We send them reminders, hey, it's time to get an oil change. Hey, it's time to go get a service done. And what they do is they go to our 92,000 shops and get that service done. And the shop gives us the information. And the second they do, we pop a little thing in the app to that consumer. Hey, how was it? Just like they're stepping out of an Uber. And millions and millions of times a year, they tell us, here's how it was. And that data from our network then starts building our data asset. But we don't leave it there. We take that data and we say, okay, we now know who the best dealers and the best shops are in the country. Let's give them CARFAX top-rated awards for that. And we do, and we give them all kinds of assets and we send them out to them. And then collectively, they take those assets and send them to millions of consumers. Hey, we won an award. It's a CARFAX award. Here's what it is. You saw some of that in the video, and that builds our brand. And so you can see how our network feeds our data and then feeds our brand. And we have many, many of these. And that's what I mean when we say we have a flywheel.

Now I'll hop through each one quickly. Our data. We are data geeks at our core. We're a data company. We love it. It's some of the things like that 177 number. We had a dinner last night, and one of the team members came up to me and he said, "Bill, you mentioned the 177, but you didn't say anything about how good we are, making sure 177 sources flow." And every time they change one little thing in this or that, it stops. And we know how to keep that going, and we've taken 30 years to figure out how to get all that data that's scattered all over to the industry in one place and put it in a form that consumers can actually understand. We do the hard work that nobody else wants to do, and we've done it over decades. Our data is responsible for over 90% of our revenue.

Our trusted brands, our industry-leading trusted brands. Now we have a first-mover advantage. When you create a category and you create that brand, we're able to maintain and grow those brands at a fraction of what it would cost anyone else trying to follow. And in an age of AI, when people don't know what to trust, who to trust and what they can believe in, we're seeing our brands become a bigger and bigger part of our value proposition.

Now in automotive, CARFAX is one of the most recognized and trusted brands. And here's one little thing that we absolutely love. On a day like today, we're sitting here having this great Investor Day. But all over the country at thousands and thousands of dealerships, today, consumers will walk in and say, show me the CARFAX.

Now this is our network, our customer network. And as I mentioned, Joe and Scott are going to hit on this again. But I would ask you, when they talk about it, when you look at the numbers and when you start to understand this network, just think about the size and the scale. We go beginning to end. We start in that planning stage, and we follow that vehicle throughout its life. Most vehicles are on the road for somewhere in the neighborhood of 17 to 18 years. And we're following that vehicle cradle to grave. And we're not following 1 or 1,000 or 1 million, we're following hundreds and hundreds and hundreds of millions of vehicles, cradle to grave. But the amazing thing about what we do is we don't just follow the vehicle, we connect with the people, the planning team, the OEM that builds it, the dealer that sells it, the customer that buys it, the shop that works on it. We connect with all the people along the way for that 17.5 years. And so we have hundreds and hundreds and hundreds of millions of vehicles, and we have hundreds and hundreds of millions of people. And we're the connective tissue between the 2. It's really a pretty amazing thing that we do in our network.

And then last but not least, being embedded in the workflow. And we've worked for 30 years to get embedded throughout the industry in the places that our customers want us most at those points of decision. And what's happened is over time, we've gone from being just embedded and having our data embedded to having other assets and other things that we bring to the table embedded into our customers' businesses. And I'll give you just 2 quick examples. On the B2B side, I was in Asia about 2 months ago, and I went with a bunch of our leaders to meet with an OEM, and they were talking about a vehicle launch, and they were using our data, but they were trying to figure out the launch of this vehicle. And what was incredible to me over the course of that meeting was this is that OEM was making a massive bet on this vehicle, just a massive bet, and they needed help. They needed help navigating and coming up with the right data to make the right decisions. And our leaders were at the table with that OEM, figuring out the data plan required in order for them to feel confident in launching that vehicle. And I was also struck by 2 things. One, nobody else in the market had the data and nobody else in the market had the experts we had to go do that.

I'll give you another example on the CARFAX side. Somebody called me a few weeks ago, somebody that I worked with 10 years ago. And they called and they said, "Bill, I've been meaning to call you. I keep thinking about you." And I thought, oh, that's really nice. And they said, "Well, I've been calling on dealers in the Baltimore, Washington market. And I've gone into over 100 of them in the last 2, 3 months. And I've been struck and now that I've noticed it, I keep seeing it at how your brand is all over those dealerships. You're on the door, you're on the vehicles, I see you all over the showroom." And every time I see it, "Yes, I got to call Bill, I got to call Bill," but I keep seeing it over and over and over again. CARFAX has built a brand that is synonymous with transparency and trust in the industry. And we partner with those 40,000 dealers, Scott and his team, and we let them use our brand in their dealership. They use our brand to build trust with the consumer. They use it to build confidence in the vehicle, confidence in their price and confidence in their business.

Now let's hop in. I'll talk a little bit about where I want to take the business here in the next few years. Our mission. It all starts here. Our mission of providing trusted information that helps billions of people build, sell and own vehicles with more confidence. And our opportunity flows off of this mission. If you think of making sure that every single person at every single OEM that needs our information is getting it. Same thing at the suppliers, same thing at the dealers, same thing with the 1.5 billion vehicles on the road owners. That's what our mission is all about. And what it's done is it's created this massive, massive opportunity for us to go serve the information needs of this huge market.

Now when you think about it, it can be quite daunting. But we have a saying that I like, think big, think really big, but go step by step. And so what I want to do is I want to share with you my steps over the next few years in driving the business toward this mission. And they are these.

First, bringing Mobility Global together as one business; second, infusing AI in everything we do and continuing those efforts; and then third, expanding our market position.

So I'll start with the first, bringing Mobility Global together. For those of you that don't know, the Mobility division was 5 separate businesses a year ago. We were run as 5 separate businesses, 5 separate HR, legal and finance groups; 5 separate financial system; building product in 5 different places; 5 healthy businesses, all growing, but 5 separate businesses.

A year ago, we began bringing those businesses together, consolidating our data, streamlining our processes. One finance department, one legal department, one HR department, aligning the business to the customers we serve. We now have the business aligned with our B2B division serving those that build and those that sell those 90 million vehicles. We weren't aligned that way before. And now we have CARFAX serving that other side with one CARFAX, not 3 different CARFAX businesses. And we've got the right structure to go grow the business.

The second is the people, making sure we have the right team, from leadership right to our front line. And you might have seen last week, we announced our Board of Directors, an incredible group of people, and we're thrilled to have them. We have a new executive leadership team comprised of 4 people that have been in the business for an average of 22 years building this business and 4 people that have joined us in the last year, bringing with them a track record of growing performance in publicly traded companies. And they're all here today, and I encourage you to meet them and spend some time talking to them about our business and where we're going.

And these first 2 are feeding the third. We were going at the market from 5 separate siloed businesses. And now we are going to the market as one from a position of strength. And we're able to now not go into a customer 3 different ways, we're coming at it once. And we can see where our opportunity lies, and we can create a far better customer experience.

The second one, AI. And we're already seeing this as an accelerant in a bunch of different places in our business, but I want to give you an idea of how we think about it. We think about it in these 4 areas: One, drive productivity; two, amplify our data; three, supercharge our core products; and four, create new products.

Now as you can imagine, I mentioned we were data geeks. We started actually with the second one here, probably back in 2018, 2019 with some of those early models. And in our business, we're so focused on data, those early models gave us a little bit of lift out of what we were getting in all of those feeds. And when we got that lift, we'd have sheet cake, we celebrate all kinds of stuff, and it's only gotten better and better since then. Then we want to run an efficient business. We have a saying work smarter, and that drove us into that first one. And we started with tools for our tech teams and doing different things for our customer service teams to make us more efficient. And those you'll hear from Jeremy later, are part of our overall AI plan, and they're a big part of what he's working on.

The part that really excites me are those second 2. Our ability to supercharge our current product set and create new ones. And the first 2 actually feed the second 2. And Jeremy, I think we have 15, 20 minutes later where he'll walk you through all of that. But I want to touch on the last one, creating new product. And I'll just give you one example. You saw the Fox at the beginning of the video there, has to do with that.

Our flagship product on the CARFAX side of the house is the vehicle history report. And as we do a better job of going and getting more information, that report gets longer. There was a day when that report was 1 page long. Today, it's 4 for most vehicles. And consumers love it, and they spend tons of time on it. And we talk about getting it shorter, they said, no, we want more on there. But our team recognized that there was a growing subset of consumers that love consuming information from a 30-second video, not just entertainment, but information from a 30-second video.

And so what did the team do? The team took our 4-page report. And through AI and a bunch of other technologies, they were able to find the 30 seconds worth of content on that report that's most relevant to a consumer and then take that and arrange it in a way that makes sense to a consumer. And then they can take that and we take that and we convert it to voice. And now we have 30 seconds of audio on the most relevant information on that report that a consumer might have spent 8 minutes on. And then what we do is we convert that voice into the voice of the Car Fox, which is our IP, which is pretty cool. You've got a 30-second voice of the Fox talking you through the report. And then we plug it into the Fox. And 4 years ago, when we wanted 30 seconds of the Fox animated for a commercial, it would take us 4 weeks. CGI, and we have to go do that. Now we can do it on the fly. And we can take that audio, put it in and now we have a 30-second video walking a consumer through that report. And I'm happy to say that our core flagship product, that 4-page report, is still being viewed over 25 million times a month. But we're also delivering over 25 million of those videos today a month. And when consumers watch them, their engagement goes up. And that's what I mean about creating new product with the technology.

Now if you think of that premise before I move on, we have this massive amount of data, and we have owners of 1.5 billion vehicles that we want to help shop, buy, service and sell. And we now have the ability to take that data to create something meaningful, plug it into the Fox, create a video and walk a consumer through that process. It's pretty amazing and tons of opportunity moving forward. Now you'll see this framework in Scott and Joe's section. The things I talked about are really that foundation, this foundation of growth for the business. And this is what we're laying on top of it, our growth vectors. They'll talk about growing our core, these new solutions that we're building, and they'll go into what those solutions are. And they're not solutions that we're going to deliver in the future. They're solutions that we've been selling for the past year.

And then our international footprint. We have a big international footprint, and we plan to take the business through what we already have there.

And in our core, we have a ton of cross-sell opportunities. We've been operating in 5 separate businesses, and we haven't been selling each other's products. And Joe has all kinds of data sets that would be really interesting to Scott's dealers, but we haven't been moving them over and selling them to them, and we now can.

As we build out one data estate, the insights that we can get from it are going to drive that middle column. And both Joe and Scott will talk to you about our international plans.

And I want to touch on this TAM chart here. Oftentimes, when people put TAM charts together, they put them together to show opportunity. I will not come to you in the next 5 years saying we are struggling to find opportunity. It is not a challenge that we have. But when I think of this chart and I think of where we're focused, we are focused in the core right now, and there is plenty there to keep us busy. There's tons and tons and tons of white space there. Now Scott and Joe will touch on a product or 2 that will bleed us over into that extended. But for the next 5 years, we won't go beyond those 2 rings. There is just so much opportunity for us in those 2 bottom rings. And so my job won't be to create opportunity. It's going to be to keep the business focused on the best opportunity, the stuff that's right in front of us.

So why are we a compelling investment? It really starts with what I started out with, right? We are part of a massive, massive market, $8 trillion market with growing information needs. We're going into that with incredible assets that we have built over decades, anchored in our data estate and our market-leading brands.

And then finally, our opportunity, our setup with the right people, the right team and structure, the right setup to take those assets and just go do it. And so the framework or the way that I think about this is 3 parts. One, we have to drive the business. Two, we've built a business creating overwhelming value for our customers, and we're going to continue to do that. And then three, strong shareholder return. And Matt will go through a lot of these numbers for you and talk about how we will go about it and what you can expect from us. But our business and the low capital intensity of it allows us to convert EBITDA to free cash flow. And we're committing to returning 75% of that to you annually.

And so when you think of our profile, as a business, the financial profile is strong growth, expanding margins and healthy returns.

So I thank you all for being here today. I hope you enjoy the rest of the presentation. As Tejal said, we have stations outside that highlight our products. We want you to know our business. We want you to see our products. We want you to ask questions on those assets. We're proud of what we've built, and we really look forward to you getting to know our business.

So thank you for being here, and I'll turn it over to Joe to start walking through the B2B business. Thank you, everybody.

Thank you, Bill. I really enjoyed having conversations with some of you this morning at the demo station, but I have to give this on the table. I was a little animated and I spill coffee on me, so there might be a little bit of coffee on my shirt. But I promise this morning, I had a clean shirt when I started.

So I'm excited to be standing on the stage talking about our B2B business with everybody. My name is Joe LaFeir. I'm the President of Mobility Business Solutions. I have to give a big shout out to our team and colleagues all over the world for helping to build an amazing business, and I'm extremely proud to be standing here talking about it. I want to start the conversation today by touching on something that Bill talked about earlier, and that's our legacy. We didn't enter into this category. We created it. We created it over 100 years ago, and we've been leading it through this focus on relentless innovation ever since.

The foundation of the business when it originally started was around this concept of performance truth. Essentially, we created an independent scorecard for the automotive industry. And then 40 years later or 40 years ago from today, we introduced a new category. We launched the industry's first global forecasting standard. And today, we're the reference point for OEMs and suppliers and dealers when they're looking at assessing market share or they're validating a strategy or they got to make a really critical decision. You see for decades, our customers have trusted us to really answer and help them with a really fundamental question. What's really happening in the market and what do I do next?

Our customers have pulled us into the fabric of the industry. We're not just a data provider here, we're helping them answer those critical questions. And this is an industry that's moving fast. It's getting more complex, and those decisions are getting really hard. And that's what's going to drive our growth in the future. We're also going to be connecting AI into our core assets to strengthen our leadership position and help answer those questions of today better and well into the future.

So how do I want to spend the time? I'd love to spend the time talking just a little bit more about who we are. I want to drill into some of those differentiators that Bill talked about. But the really exciting stuff is where we're taking this business and how we're going to grow it going forward.

So let's get right into it. This is a strong, resilient business. We have over $600 million in revenue last year, and we operate this business on 2 complementary portfolios. Our Strategy and Planning business, which is primarily serving those suppliers and OEMs. And that's where the high-stake decisions that we're talking about really start. And then in our Marketing and Sales division, we're helping dealers and OEMs in those downstream critical workflows that are helping to get cars into the hands of consumers. 82% of our revenue is subscription based.

Now there is some transactional revenue here, but I think it's kind of important to note that, that transactional revenue is almost entirely driven by our subscription customers, and that revenue is driving retention and account expansion. A couple of simple examples. We got USMCA coming up for review this summer, and that's the North America free trade agreement there. And there's huge implications. Suppliers will come to us to do custom studies to understand the implication for their business. An OEM launching a brand-new vehicle, and they want to get the biggest reach possible to get consumers to purchase that new launched vehicle, they're coming to us for those campaigns.

Now I talked about this being durable and highly reoccurring revenue. It was stress tested. If we go back and we look at the challenging times during COVID, this industry was hit particularly hard. But when the dust settled in those most challenging years, our subscription revenue for OEMs and suppliers actually grew. It really shows the resilience and the indispensability that we have with our services that we're providing the industry. And we're operating at scale. We're highly reoccurring, high retention. We're not fighting a churn here. We're sustaining value, and that's helping us grow the business. And Bill mentioned it, we're working with all the top OEMs. We're also working with all the top suppliers. But really, we're working with thousands and thousands of suppliers. We just happen to be pointing out 94 of the top 100.

And our data moat is unmatched. 13 billion records that are representing the transactions in the marketplace, over 800 million VINs, and we're covering 99% of the global vehicle production. And that scale, that's impressive, but what we really focus on is what we do with that. We're creating better signals, better models, all focused on helping our customers get better outcomes from that data. And that allowed us to serve this really wide range of offerings across the industry. And Bill mentioned that life cycle. Yes, we're operating across that entire vehicle life cycle, where it starts in planning solutions is like the tip of the spear. This is where OEMs are determining what to build, how to configure them, how to source the components and how to bring those vehicles to market. And as those top 3 nodes in that life cycle. This is where their long-term competitiveness and their cost structures are set.

On the sales side, we're extending downstream, helping OEMs and dealers translate those plans into effective pricing strategies, targeting strategies to go to market and get those vehicles into the hands of consumers. The spanning of the entire life cycle sets us apart. We don't have anybody in the industry that does this in complete life cycle. We're connecting what the industry often is separating this kind of upstream planning intent with the downstream market behavior. And it gives us a great opportunity to expand our business in many ways. Each one of those nodes are growth opportunities for us. Just think about that thing growing outward in any one of those directions.

So just to go a little bit deeper into our strategy business in the forecasting side, we're helping -- our intelligence is helping suppliers understand what to do this year. How are they thinking about their production. And then we're also making bets 5, 10, 15 years down the road, big bets that are often irreversible and can cost a lot if they get it wrong.

Across our sales and marketing, our intelligence is actually helping to inform how is that vehicle actually competing in the marketplace. Who is buying it? What are they buying? Who are they buying it from? And how much are they spending on it?

Through our sales solutions, we're helping the industry to effectively spend billions of dollars in marketing spend and tens of billions of dollars in incentive spend. Because we're connecting those signals, those upstream planning signals and actual behavior in the marketplace, we're not just describing what's happening, we're helping our customers identify where those opportunities in the markets are and also as early as possible, identify where those threats are so they can take action.

So let me talk about the 4 core assets. Bill mentioned them earlier. I want to drill into those unique assets in the B2B business. They are ones we talk about proprietary data, our trusted brands, our scaled network and our embeddedness in the industry. And these aren't static. They're continually changing, we're adjusting them to address the needs of the day for the industry. And they've been in place for decades supporting these customers. And individually, they're powerful. But when we combine them all together, it creates this compounding advantage, and you should see that as I walk through this.

Let me talk about them. The first one, let's talk about data. Our moat starts with data, and it's comprehensive. Over 90% of our revenue is being generated from this proprietary data. In our strategy and planning business, we're covering every major aspect of the industry. We're talking about commercial vehicles, passenger vehicles, the powertrains that move those vehicles, every component and technology that makes those vehicles unique. We're tracking all of that, and we're defining 85,000 variants of vehicles that are getting manufactured around the world.

And when you go underneath the covers on that, you'll see we know where every plant is. We know what they're making in those plants. We know who they're making it for, and we know how long they're going to be making it. And all of that is to inform how 90 million vehicles are going to be produced each and every year.

In our sales and marketing solutions, we connect the vehicle, the consumer and the transaction, a combination our competitors just don't have. I talked about this 800 million VIN that we're tracking. And when I talk about tracking, I mean, we know specifications on each and every one of those vehicles. We know who bought each and every one of those vehicles. We know how long they own that vehicle. We know where they were when they own that vehicle. We know when they sold that vehicle, and we know what they bought next.

We see the patterns. And if these blinds weren't down here, I'd tell you to look out the window and just look at the vehicles on the road, if you're in the shopping mall and you're in the parking lot, look at the vehicles. I know there's not a lot of shopping malls here in New York, but you get my point, next time you're in a parking lot, every single one of those vehicles is in our database. And it has tens or hundreds or thousand records depending on its age that represents its lineage. This depth and comprehensiveness of data is what's powering our AI. This is how we're getting to predict behavior prediction scores I'm going to talk about. This is how we get to understand effective pricing and many, many other things that we're going to get out of integrating this with the AI infrastructure, which is the way this industry is going to make decisions going forward.

Now having great data is good. I'm a data guy, I'm a technology guy at heart. I love this stuff. But what really matters is what we do with it. And we're the gold standard in this industry because we've earned that right to be the gold standard. We know how to turn that into valuable solutions. So we are the reference point. Very simple example. If an OEM is going to claim best-selling vehicle, longest-lasting vehicle on the road, well, they're claiming against our data. We're the independent scorecard.

We bring on-the-ground expertise across the world. And we don't just have analysts. We have like industry practitioners. Bill mentioned this when we were talking about his experience in Asia. They're not locked up in the backroom writing white papers. We have them write white papers, don't get me wrong. They're smart guys. They like to put their stuff on paper sometimes, but they're really focused on being out in the market talking with our customers. And when major events happen in the world or in the industry, the industry is looking to us, major media outlets look to us to understand our perspective on the impact to the industry. When the war broke out in Iran, our analysts were immediately communicating our perspective on the implication of that industry if the war lasted 1 month, 3 months, 6-plus months, what's happening today. They're turning to us.

We also host briefings all around the automotive hotspots around the world, Tokyo, Shanghai, Seoul, Detroit, Frankfurt, among others, where we're bringing together hundreds of customers into a room like this multiple times a year to discuss the industry and where things are going. You see we're not observing the industry from the outside, we're inside working with them where the action is really taking place. And what this is doing, it's creating that powerful network effect. It's a flywheel that compounds in value, and we get better, our value increases and more participants want to join in that conversation.

Now why do they engage? They engage for a lot of different reasons. I'll outline a couple of them. One, we create an independent view. When the executive will come to me, he'll say or she'll say, you guys remove our blind spots, and that's what we love. And they know when they go to a Board with a $1 billion decision, they're going to ask what data validated that decision. And they know that we have that reference point in the industry to be used. We have an understanding of what those OEMs are thinking about building. And actually, we have to create a reference point that the industry can feel comfortable with. And if you look at the way an OEM will operate, God bless them, everybody is ambitious. You add up all of those plans, guess what happens? It's going to exceed the demand in the marketplace. It just will. So we have to be there as a reference point to take that noise out to reconcile those volumes so that if you're a supplier and you're going to make a major investment on a program, you're protecting margins by understanding what the likely volumes of those vehicles are going to be.

We also have high-value interactions at the dealer level with our automotiveMastermind team with dealer relationship managers that are in those local markets, working with those dealers to understand how to deploy campaigns to keep customers loyal and to perform against the competition. And our competitors struggle to replicate our data advantage. But the reality is they'll struggle probably even more to replicate this interaction model that we've created.

Now I have one more differentiator I want to walk through before we get to the good stuff, which is the growth story. But I really think it's important to talk about how deeply embedded in the industry we are. So we have full ecosystem reach. I talked about this, top OEMs, top suppliers and top dealer groups. The OEMs -- in our sales and planning side, the 6,000 OEM users will be logging into our tools every day to understand how to manage the markets that they're operating in. And when industry disputes come up, it's our data that's been tested in court and considered the truth. Our pricing and payment engines are embedded in over 10,000 dealers, helping to make sure monthly payments are computed correctly for consumers.

If you register a car at a DMV or you insure your vehicle or you get a recall notice or you go to your local auto parts store, and they just happen to always have the right part in stock for you. If you're on your favorite social media platform and you see an ad for a car that you're really interested in, well, that's probably being powered by us. We're taking friction out of the workflows across the entire industry.

So I do have a little story I want to share. About 10 years ago, an OEM, a major OEM was bringing a new vehicle to the U.S. market. They're building it in Europe, brand-new platform. And when the vehicles landed here, 20,000 of them, they couldn't get registered. Someone got the VIN specification wrong. That was $1 billion of stranded inventory sitting there for that manufacturer. It was an all hands-on deck situation. They turned to us. Well, why did they turn to us? Because we're the embedded intelligence across the industry that makes those workflows function. We systematically work with every state DMV deployed workaround so those vehicles get registered. We then deploy those to insurance companies that we work with so they can get insured, and we resolve that problem for them. Now we're proud to be named one of the suppliers of the Year, but we're more proud of the fact that we were there in the time of need for our customers, and it illustrates how deeply embedded we are in this industry.

Now let's get into the growth drivers, the exciting part. Bill mentioned this, we are undergoing structural change in this industry. And that's going to influence where our customers go and where we're going to drive our growth. Now we thrive in stable periods, a lot of organizations do, but we also excel in times of uncertainty and volatility because this is the time when some of those decisions are going to matter the most. And we're looking at some of the trends at play right now in our strategy and planning space, we see cycle times compressing. So the time it takes for a manufacturer to bring a new vehicle to market, leading OEMs are doing it in 3 years now. Most manufacturers are struggling to do it in 5. The complexity of these vehicles are increasing and with $1 billion, $2 billion, $3 billion bets to be made amid uncertainty on tariff and regulations, there's risk all over the place here.

On the sales side, pressure is building downstream. The inventory dynamics are changing constantly. And some would say there's an affordability crisis for the consumer. We're seeing over 20% of car loans at 84 months now. This is a rising trend. It only stands to reason that consumers are probably going to hold their cars longer. And what does that mean? It's going to put pressure on volumes. It's going to put pressure on loyalty. It's going to require manufacturers to increase incentive spend just to hold volume and share. As these forces are accelerating, our customers can't afford to wait. They have to take action. They need clarity. They need data and information in this rapidly changing landscape, and that's what we're here to do.

So Bill talked about the TAM. When we look at the B2B side of the house, we're serving a $6 billion addressable market, about 10% market share here, but we do see a clear actionable path to an $18 billion opportunity. Now we're going to stay focused in those first 2, the core and the extended core. But the global automotive industry is an $8 trillion industry, and it's not about inventing demand, like Bill said, it's about us going deeper into the industry we know really, really well. That opportunity is sitting in our backyard. And we're going to do this in 4 ways. We're going to extend our core. We're going to deepen the value in our existing products in sales and planning. We're going to move into adjacent use cases that we naturally go into with our data and expertise. We're going to scale internationally with our customers in those growing markets. And we're going to unlock new categories through AI, turning that insight into predictions and decision-grade intelligence.

So let me walk through what we're going to -- what we have in our plan in a little bit more detail. So Bill mentioned, we have significant growth opportunity in the core, just selling the products we currently have. We're under halfway -- we're less than halfway penetrated with our existing offerings. And with automotiveMastermind, we have a tremendous runway, especially as we start to connect into the CARFAX dealer network.

We are embedding AI into the core of our products. We know that AI agents in the future, deployed by us or our customers, are going to be operating the workflows we're touching today. That AI technology combined with our data is what's going to unlock an entirely new level of insight, wasn't previously possible. Take a look at some of the demo stations that we have out there to see this in action.

Second, I want to talk about new solutions where AI is helping us win. And I'm going to walk through 3 examples today, but we're really taking and moving beyond insights, and we're talking about prediction and simulation to support actions.

And third, international. We're going to scale alongside the global OEMs, particularly in China as they start to take their brands international. We're going to be looking at scaling our sales solutions across Europe, Canada and Australia, and we'll go deeper into India.

In One Mobility Global, our teams are collaborating. We've just recently brought them together. I can't tell you how exciting it is to see these guys in the rooms in Virginia and New York, thinking about all the ideas. They're like kids in a candy store. It's great.

So let me get into the growth opportunities. AutomotiveMastermind is one of our fastest-growing products and has significant growth opportunity ahead of it. It's growing at double digits. It's deeply penetrated into the luxury market of dealers, so where it got its start. But over the last couple of years, we've proven the fit for the mass market, and we're building a tremendous amount of momentum in that space.

So you guys might be saying, Joe, what's this Mastermind thing? I heard Mastermind, I heard automotiveMastermind. Like really simply put, this is our solution for dealers to help them reach a customer to sell a car. And while it's a workflow solution, the power is really embedded in the analytics. And if you get to the demo station, you can see the depth of analytics that's in there because reaching a customer today at the right time with the right message is harder than it ever was. It's a fragmented digital world where people are consuming content on so many different platforms. It's making marketing to them extremely complicated and expensive. Gone are those days of the Sunday paper with like, I don't know, like tons of car ads in it, like I remember those, and local TV ads, they're all gone.

But our behavior prediction score is delivering that targeting that's necessary, and it's not a one size fits all. So we've taken thousands of data points and we run it through our machine learning and AI infrastructure. And we're considering things like are they near the end of their lease term? Okay, that's an easy one. Are they about to go over their miles on their lease? Did they have major service events? Are they in a positive negative equity position? Or maybe the version of the car that they're driving was just refreshed and there's a nice new one that's better looking than the one they have, and they might want to get into that.

Well, those scores that come out of BPS are being delivered to the dealer sales professionals to help them engage with each and every consumer for the things that are important for that consumer, for that transaction. It's been proven. We have significant loyalty lift, 10% through our customers that are using this product. And we hear from them, and it's crystal clear the value that we're creating. They're telling us things like, I get 10 to 15 sales a month in my dealership by using this. And that's significant for a dealership. It's not table stakes anymore. It's becoming table stakes. It's not nice to have.

Now I want to shift over to another product that we have in our planning business. It's called FAST. We're putting 40 years of forecasting experience and expertise into the hands of our customers. Planning used to be really hard. Now it's really, really, really hard, multiple powertrains in play, compliance things in play. FAST, which our forecast adjustment and scenario tool, it codifies that expertise that we have and allows our customers to create their own unique scenarios to understand its implication in the marketplace when they decide they want to make a change. Today, the only real alternative is a spreadsheet and pumping some of our data into it and trying to do some things manually.

And when I say 40 years of forecasting intelligence, what am I talking about? I'm talking about a deep understanding of how variables will change the forecast. So things like we understand the life cycle of vehicles. When a vehicle gets launched in the market, it might spike in volume and some vehicles are going to tail right off the next year or 2 after a launch. Some vehicles are going to spike and they're going to hold that volume for a while. But you know what, we know what those life cycles look like by vehicle. We know how long they'll hold their volume. We also understand the sensitivity on things like powertrain and features and price and how those move the forecast. Imagine taking the horsepower down in a high-performance vehicle segment. Well, guess what, your volume is coming down. Think about raising your price $5,000 in a compact vehicle segment. Guess what? Your volume is going to go down.

Those sensitivities are built in, and they've been developed over decades of understanding how the market moves. Our value is very measurable here. It's automating 90% of the workflow, and we're generating 4x improvement in forecasting quality. We're talking about integrating a tool, an AI tool at scale for the enterprise.

Last, my favorite for last. Well, I love them all, so I can't say that. Someone is going to get mad at me. But this is really the last one. It's Data Studio. And Data Studio addresses one of the biggest hidden drags in the industry. And when I say there's a misalignment between tiers. And when I talk about the sales side, tiers, Tier 1 is the OEM and Tier 3 is the dealer. They often send mixed messages to the consumers. And consumers are getting one message from an OEM, one message from a dealer and they're different and they're confused. And there's a lack of priority within those organizations to connect all those data assets together. So the information isn't flowing through the industry.

Well, we have a trusted relationship with the OEM, and we have a trusted relationship with the dealer. We're pulling the first-party OEM data into our platform, we're pulling the first-party dealer data into our platform and we're integrating with our proprietary data into this clean room environment where we're the independent steward, and we're building solutions to help them both, the dealer and the OEM.

Our first solution on this platform is something we call EEQ. And this allows OEMs to deploy incentive programs -- personalized incentive programs out into the marketplace. The tool allows them to run scenarios and look at what the cost of that program is likely to be, what their volume -- what volume will they get from that program. And then they can execute and measure that program and it gets activated and deployed through our automotiveMastermind product into the dealer network, and there's a consistency and linkage there.

And the results are strong. We're seeing 40% improvement in close rates on those campaigns, a 10% lift in sales. We're having a reduction in incentive spend, increase in margins. And it's not a one-trick pony. We're talking about a data platform that we've built that we're going to build other products off of the top of to help both the OEM and the dealer. It's a full suite of solutions going forward.

So I could talk all day about this, and now I can already see I'm probably running over time. Bill is probably going to take it off-stage, but let me close where we started. This is a proven model, $600 million in revenue, 82% subscription, highly reoccurring, very durable. We're deeply embedded in this industry, and we're trusted by all of the largest players in this industry. We've only begun to tap into the expanding opportunity that we have sitting in our backyard, and AI isn't theoretical here. It's scaled, it's delivering results. And in my mind, the opportunities are mind-boggling where we can go with this. And as the complexity of this industry increases, our partners are going to continue to turn to us just as they have for a century.

So with that, I want to thank you all for the time today, and I think we're ready for a break.

[Break]

Thank you very much. Hard to follow all of that. My name is Scott Fredericks. I am the President of CARFAX. I have been a part of this business for over 29 years. Yes, since the 90s. And I can tell you that we have been on a great ride. I'm happy to share some of that with you today. But to me, the most exciting part is our brightest days are ahead of us. We have a huge growth opportunity in front of us and a great story, and I'm happy to share it with you today.

And it really all starts with the consumer. We have long been on the side of helping the consumer. They have anxiety. Think about yourself getting ready to buy a car. You have a lot of questions about it. It's a lot of money. You don't have a lot of information. You may think the person on the other side of the table has more information than you have. So this spawns questions. That anxiety creates questions all the way around this life cycle, when they shop, when they buy, when they own the car and take care of it and then eventually when they sell it. CARFAX answers those questions. And these are just 4. Consumers have thousands of questions. And we use our data, data that you can't find anywhere else, wrapped in our brand, that Car Fox, to help them feel confident. And when consumers feel confident, they're ready to take an action. They're ready to buy the car. They're ready to take that car in for service or they feel like it's time to sell and they're getting a good value for the vehicle they own. This is what we do, and I'm going to walk you through it a little bit today. It is the power of our business.

So we'll do a quick introduction to CARFAX. I'll walk through the core assets, and then I'll show you some of the key growth drivers we have ahead of us. But let me show you some numbers, okay? So we are a diversified, resilient and subscription-led revenue model, okay? 80-plus percent of our business is built on subscription recurring revenue, highly visible, clear visibility line of sight, very stable, durable. It's built on a lot of diverse product sources.

So our core product, hopefully, you've seen it out in the demo station, is the vehicle history report. That's the CARFAX Advantage line you see there. It doesn't even represent 40%, and that's because the other products that we've launched over the years have grown so well. And so we have a very diversified set of products, and we're now taking those products more broadly internationally. So you can see we primarily are operating in the United States, but we are growing our international footprint. The same troubles and questions consumers have in the United States, they have those same questions everywhere in the globe and our products can help answer those questions.

So let me give you a few more numbers. We have a very high-growth organic business. This is all organic growth. And it's built on these assets, these assets that Bill talked about, and I'll talk a little bit about as well. So look at these highlights. We have huge brand awareness among in-market shoppers. Virtually everybody knows us. We have 38 billion records on all the cars on the road that answer those questions consumers have. Was this car in an accident? Is the car well maintained and many, many more. We distribute our products through a growing network of dealers, 40,000 dealers strong.

And then the newest asset is we are building a direct-to-consumer audience. That's the Car Care program. I would encourage you to download it. It's a free app, and we can help you take care of your car. And we could actually add to the 53 million and grow it even further. But consumers depend on us to help them when they need to get their car serviced and maintained. That's the audience that we are continuing to build. And Bill said, we got to go to 150 million, okay?

So we have these 2 life cycles. Bill talked about it. Joe talked about the one on the left. I'm going to talk to you about the consumer life cycle on the right. And we have been in this for a long time, and we have scaled our reach in each one of these areas. So when consumers shop, they're coming to our listing site millions of times a month to shop for cars. When consumers are ready to buy, they are asking and demanding and wanting CARFAX reports at the point of sale or online. And then when they want to take care of their car, that's that big audience I just told you about. And more and more, we are helping that consumer connect at the right time, get the value of the car that they currently own and then connect them with willing dealers that want to buy those cars from them. And that's the sell side. And this is a big, big market opportunity. In the United States, we have hundreds of millions of cars that we touch, but globally, 1.5 billion. That's the audience that we're talking about.

All of this is built on that same flywheel that Bill outlined earlier, okay? So that's on the left. That's that Mobility Global engine. I'm going to go into each of those for CARFAX and what we bring to the table. But you can see over the years, we have launched core products. Vehicle history now more than 40 years ago, CARFAX Car listings in 2014 and then the Car Care program in 2019. Those are our core products, and we've built them over many years. What I'm proud of is we have actually launched new solutions in the last 12 months. These are new revenue growth opportunities for our business built on those same data assets and brand, and we can operate and grow these new products into the market.

Why do we have these new products? For 2 big reasons. We've been able to accelerate our product innovation using AI, and I'll show you some of that, and I know Jeremy will get into even more of that later. And there is this insatiable demand from consumers. They want the answers to more and more questions, which spawn these new solutions. And like I said, these questions that consumers have are global. So we can take our show on the road and bring them to Canada and Europe and beyond.

So let me walk you through these strategic assets. So here's that flywheel. In the upper left, we have the data, the 38 billion records driven by 177,000 different data sources. We have this trusted brand that consumers know and trust. Our mascot, the Car Fox, is better known than the Pillsbury Doughboy. It's pretty good. The Michelin man, all right? These are brands that people know and trust. CARFAX is at the top. We have this unmatched customer network. So we bake ourselves into how dealers operate and make it easy for them to use CARFAX information to make business decisions, but then also to share our products with their customers, with the consumer.

And then this is the magical part. The magical part is it's driven by embedding it in how people operate. And we have loaded the lips of consumers to say, show me the CARFAX. And what that means is they want the transparency that only we can provide. So when they walk into the dealership at that moment of truth, they're saying, "Hey, before I buy this car, show me the CARFAX."

So now let me walk you through each of these just a quick double click. So here comes the data. So 10,000 records way back in 1987 and now 38 billion. And this comes from a huge network that I'll show how it works of data providers, including 92,000 service shops, practically every service shop in the United States. What's important here, maybe the most important number here is our revenue, 90% of it is driven by this data estate that nobody else has. It's proprietary. It's built with IP and analytics.

So how do we do this? How do we get all of this data? Well, it comes from this network that we've built. And you can see the categories of data providers that we have around this circle. And it's very diverse, and we get more than 6 billion new records today. Even right now, we're going to -- 6 million today. So I'm going to walk you through one of these examples. And let's talk about the 92,000 shops that work with us. And Bill mentioned it earlier, but why would they give us their information? Well, the reason they give us their information to put on the report is because we give them 2 things back.

First, we give them data back so they can be better mechanics. They can use our information to better diagnose a car and repair it better. So they like that.

And then two, they get brand exposure on the report next to every record that they give us. So we give them their name, their phone number and their URL, and that gets more consumers to come back to that shop to get more work done in the future. They see that as a huge marketing engine for their business. We've done that for every single one of these 177 data providers. We provide data and insights, value to them and they exchange that with data back to us. And it's a relationship by relationship shop by shop, dealer by dealer, police agency by police agency, ground truth built over 40 years. Good luck trying to replicate it.

Our brands. So we take all that data and we wrap it in a brand that consumers know and trust. The Car Fox is well-known fella, cute guy. There might be some stuffed Car Foxes outside, I don't know. For anybody who wants to take them home, dogs love them, FYI. But we've been able to become the #1 place consumers go to when they're shopping for a car. So 54 million visits a month, consumers coming to us as they're getting ready to shop for their next vehicle. And we have all of these consumers that depend on us when they own the car and want to take care of it.

So this is something that's really unmatched in our space. Dealers put up 25-foot Car Foxes in front of their showroom on the weekend because they know that it helps build confidence. It makes them look trustworthy, and they want to use that trust in order to earn the trust with the consumer.

So how do we make this product easily available for our dealers and OEMs and banks and financial institutions to use it? We embed CARFAX everywhere, in all the tools and workflows that they use every day. And you can kind of see the long list. In the CPO area, we have 36 OEMs that will not certify a car without a CARFAX report. And then they make that report available to the consumer to build confidence in their certified pre-owned program. That started with Mercedes-Benz back in the late '90s, and now we've added 36 more.

I'm going to walk you through one example on the dealer side. My favorite dealer is in Fairfax, Virginia. He's a Ford dealer. And he is going to go to auction today and his auction buyer is going to consider many cars online at auction, perhaps as many as 300 cars that they'll evaluate in order to buy 5 to bring into retail inventory. So 300 CARFAX reports to figure out which 5 cars we should buy to put on our front lot next week. And the reason that Ted Britt does that is he wants to know what the consumer knows before he acquires the car. So he wants the knowledge anticipating that consumer need and demand before he gets involved with that car. That is how we've changed the industry. They're using our information before they get involved with the car, just like the consumer wants to use our information before they get involved with the car.

Show me the CARFAX. This might be the magic secret sauce. This is push, pull that nobody else has been able to replicate. 2 million times a month, consumers come in or go online and ask the dealer for a CARFAX report. They say, "Show me the CARFAX." And that powers this entire thing. Consumer pull is the monetization engine into the dealer. Dealers have then learned, "Hey, you know what, it's a really good idea for me to share CARFAX proactively to the consumer. Let me put it on my listings online. Let me share it in my advertising that I use CARFAX. Let me put signs up in my showroom that say, I'm a CARFAX dealer. And then let me show it to the customer at every deal in the showroom." And so now dealers are starting to present and push CARFAX 28 million times a month. So consumers say, "Show me the CARFAX," and that spins our flywheel.

This all translates into proven ROI. Dealers get huge business benefits from working with CARFAX. They get more service visits, they get more customer loyalty. They sell cars fast and they sell them for more money. This translates into 10 to 15x ROI. That's right. It's alarming. Unbelievable. [indiscernible]. You can't make this stuff up. Banking and financial institutions use our information to make better decisions, okay? So they use it to reduce fraud risk. They use it to underwrite at the right level. And then, of course, consumers depend on it. They love our products. We get a very high customer satisfaction. And they use it to make sure that they're getting a good deal and they're also selling the car and getting -- when they're ready and they're getting a good deal for their vehicles that they're selling. Unbelievable. I couldn't make this up if I wanted.

Okay. I'm going to keep moving here. Key growth drivers, 2 trends that are kind of underneath this business working in our favor. One is cars are expensive. New cars are more than $50,000. Used cars are almost $30,000. So when you -- when the stakes are high, people have questions. Vehicles are on the road for longer than ever, probably because of the trend on the left, right? So what does that mean? That means more CARFAX, more CARFAX when you're about to buy a car, more CARFAX because you want to make sure you're servicing it right. So more car care relationships, more service records, more lending decisions, all of these things equal more CARFAX.

We have this big TAM, okay? Huge opportunity in front of us. I'm going to focus on the core TAM for a second. Our core business still has big runway of growth. People have asked, well, you've been in the market for a long time. You must have a lot of penetration. Well, in our core product, we do have a lot of penetration, but we actually have more opportunity with our core product. And then we've added other core products on top of that, the Car Listings product, the Car Care program. Most dealers are only on 1.5 products. We know that we can sell 3 or 4 or 5 products to those dealers. So there is a core growth market opportunity there that we can go into.

In the extended area, we have new things that we're adding, digital advertising, Sell My Car, a new program to connect the consumer at the right time with the dealer that wants to buy their car. And then, of course, we can take these products that we currently have into other markets internationally. So I want to focus really on that $26 billion as we hop into here are the 3 places we're going to grow to reach our TAM. So core growth, we have more solutions that we want to sell in, higher adoption and retention of those. We're going to capture value. We continually innovate on our product. When you go out to the demo station, you'll see the vehicle history report, and we've innovated more on that product over the last several years, and you'll see some of those innovations. That enables us to deliver more value to our dealers and capture that value over time.

We also have upsells where we can sell dealers on the Lifetime Program. I'll show you what that looks like. We have some new solutions, Sell My Car and showroom listings and service marketing coordination. I'll show you what those look like. And then we have international expansion. We have some of our products in Canada, but we can bring more, and we continue to expand in Europe. We're in a few markets in Europe, but we want to go to more markets in Europe as well. And then underneath this is One Mobility Global. This is where Joe and his team have data sets that we can use to make our products smarter. And we're already starting to do that with Market Scan and the prediction scores. So that -- all of that works together.

Let me talk to you about the Lifetime as one of the examples. So we have taken our 3 core products and stitch them together into the Lifetime Program for dealers. And when you do that, it unlocks more value and helps them solve big problems. Dealers have low service retention. Most consumers don't go back to get the car service at the dealer. They would love to have that. They would also love to have the customer turn the car in and buy another car from them down the road. And they see these as big, big leaky buckets in their business. When they stitch these 3 products together, they see big lift. They see more service retention, 19 points. They see higher OEM brand loyalty, 16 points. And the OEMs have definitely taken notice because 14 OEMs now support this program with co-op funds for the dealer.

So we are just getting started on this. The traction is really strong. We started doing this in Q4 of 2025. We already have 1,600 dealers that are on this program. And we are just getting started. So it's really building in momentum. This is a vehicle history report. It's often been thought of as strictly a history report. I can tell you now it is about the past of the report, the present, what's that car worth and in the future, tell me how many more miles this car will go, tell me how many major repairs are going to be needed on this car. And let me compare the futures of different cars so I can determine which car is right for me and my family. But I don't want to talk about it. I'll let the Fox tell you about it.

[Presentation]

So that's just the beginning of the Fox telling you the future. You'll see more and more of that as we innovate and bring more granularity. We're going to be able to tell you how many more miles a car has life left in it. And so you can use that to make a smart decision. It's just the beginning. But we also can take our show on the road, and we're primarily operating in North America right now.

We have a little bit of runway already started in Europe, but you can see that there's big opportunity still in front of us. And the questions that consumers have that power this market are the same in these other geographic locations. They worry about spending too much on a car that might not be a good car. They worry about should they get the car fixed and who should do it that I can trust. And then they worry about, am I getting the right price for my car that I'm trading in? So we can take the same questions that consumers have and answer them using our same data assets, our same trusted brand.

Let me wrap all this up for you before the alarm goes off, okay? So we have this proven financial model, subscription business, very durable business, clear line of sight on our revenue. We have these key differentiators that power it, this awesome data, our trusted brand, great network of dealers and such. We have these core and new solutions that are powering more value for our dealers in the current and new growth opportunities. So we can capture that value as we deliver that on existing and then we can add on top of that new revenue streams from these new products. And then we can go out on the road and take this story internationally and help consumers around the globe.

And that's my story, and I'm sticking to it. I'm going to invite Jeremy to come up before the next alarm goes off to talk about our AI. We have a huge AI initiative, and I'm going to let him talk you through it. Thank you very much.

All right. I have on good authority that we're not going to have a disco ball going on. So that's exciting. All right. Hello, everybody, in the room and online. I'm really excited to be here to talk about my favorite topics, data and AI. Bill, Joe and Scott were talking earlier about where we're taking the business and how we're using AI and data to do that. I'm going to try to dive a little bit deeper into that. My name is Jeremy Morehouse, and I have the privilege of being the Head of AI Office for Mobility Global.

Before I get started, I was hoping you can help me with an exercise. Could you please look under your seat, if you reach under your seat just for 1 second, you'll find that there's absolutely nothing there. But the demonstration of how a little bit of misinformation or hallucination from an AI model can have a real-world impact. And while looking under your seat is not a big deal, making a decision that's a major financial impact, whether it's capital misallocation or buying a car is a big deal. We take our mission very seriously of providing trusted information regardless of technology.

Before I jump into the AI piece, so I want to talk about the demand for our data and how AI is changing the world and how we consume data, whether we're a consumer using an LLM to search for a vehicle, an OEM who wants to plan smarter, a dealer looking to manage their inventory a bit better or bank and insurance companies looking to do better underwriting. The demand for -- the demand to change those businesses to use AI means that there's a major demand for data. I'm sure everyone in this room has heard that data is becoming a new currency and demand is increasing, not decreasing. AI is not replacing the need for data. It's actually increasing it because all these people on this slide can't use public AI models to make their decisions. Public AI models are trained on public data. They have access to public data.

And one thing we've learned over the years that these models have been available is that this is not the kind of data that we want to make decisions with. It's good enough, the data. Data do lots interesting things, but it's not decision-grade data. We have decision-grade data, VIN-level data, global data that allows us to provide these services to customers in a trustworthy way that public AI can't do. Because the cost of doing things wrong and just using good enough data, our hallucination means major fines, legal exposure, capital misallocation or everyone in this room buying the wrong car for their family and having to live with it for the duration of their lease or their finance.

So our mission hasn't changed. Even though we need to provide more data to these systems, we need to find new ways of providing that data and provide the trust information in a safe way. You've heard this a couple of times now about our data moat, and our data moat is deep and wide. We also enhanced it with AI, which I'm going to talk about in a little bit. Every one of those 177,000 sources our contractual relationships are slow to replicate. We have that 2-way relationship that Scott mentioned that makes it -- there's no incentive to leave to continue providing that data to us is a very, very important thing for them. It's a very important thing for us. And the data we have isn't scrap, it's not publicly available, and it's not synthetic. This is real-world data, real things that are happening in the industry to the vehicles and to the people in this room.

As I mentioned earlier, this is all VIN-level, too. It's global. We know exactly what happened to that car. As Joe mentioned, there's so many things that happen, whether it's the vehicle itself, the people that own it. There's a lot going on, and we know that data better than anybody. More importantly, this moat is not static. It's growing all the time. You've heard numbers, 6 million millions -- millions of records pour in every single day. I'll talk a bit about how we ingest all that. And we use AI to enhance that even further. Many of those records contain more than just one piece of information. We want to extract all the possible value that we can.

So this living data moat is just constantly evolving, and we keep all that data. We have decades of data that we look back on and say, what else could we do? What other insights could we bring? What other forecasted models can we create? And this data is embedded in workflows today, and it's very sticky. We talked about CARFAX. People don't go and say, can I see the history report? They say, can I see the CARFAX? The OEMs planning cycles. They're using our information. We're so embedded in these systems that the switching cost is just too high. It's way too high. And if they did switch, they have to go revalidate all the decisions from the past, rebuild trust with their customers, redesign their workflows. It doesn't make sense to do that.

So that's our data. You've heard a lot about our data. And I'm going to go through each one of these, excruciate in detail. I'm just kidding. Actually, what I want to highlight here is that we are not just getting started in AI. We have this powerful data moat, but we've been working in AI for nearly a decade. We've been building this institutional AI excellence within our business for a very, very long time, where others are just getting started because GenAI has changed the world and people are excited about it. We've been in the business of AI and machine learning for a very long time. Today, we have over 100 dedicated data scientists and AI experts that just love solving problems using AI. This is all they do, and they love creating value with AI. They're not just playing around the technology. They're understanding what problems we can solve and what value we can create with this technology.

Let me take you back a little bit. In the very beginning, we brought the very first neural network models into our business to solve some natural language problems. The reason why we did this wasn't because it was fun, it's because we wanted to provide signals to our consumers that were the highest accuracy possible. When we told them they need to get an oil change or tire rotation, we didn't want a big error rate in that. We want that to be as close to 100% as possible. And the only way to do that was to make sure the underlying services were decoded extremely well. We designed that program to have a 98.5% accuracy in everything that extracted. And today, we do over 180 services with that program at that rate. I actually pulled some numbers for this presentation. And currently, our production models are run at 99.5% accuracy because the accuracy is super important in that program. So those signals are correct at all times.

Like everyone else, we moved into GenAI really, really early. We wanted to understand how would -- this technology would transform our business, how people would want to interact with our data, how chatbot might change things. But more importantly, what would the cost of that be, how would hallucinations affect trust in our business and our brand and how we could start getting ahead of some of those concerns. We established our very first formal AI teams to focus only on AI technologies, some more to add AI. And along the way, we've compounded a lot of our AI layers, which I'm going to talk about next, and create more advanced products like our enhanced reliability that Scott spoke about.

And we've also created this very mature AI operations group and platform. What does that mean? That means these folks are creating models that operate the most efficiently possible, but not necessarily using large language models and frontier models that are very heavy to consume and very costly. They're creating cost-efficient models, high accuracy. They're creating programs to repeat these, test quality. And this year, we're actually launching something called the model health initiative to take a proactive look at the models we have in production and ensure they're always running at the highest efficiency possible and the highest quality possible.

What we've learned over the years is that getting into AI is very easy and everyone is talking about it. But doing it right, making sure that it's accurate, that's scalable and that it's safe is very, very hard. This is something that we do every single day for the past decade. You saw a similar slide earlier. Bill talked about this. These 2 sort of key moats, key features, key skill sets, our data, our AI expertise feed into these 4 engines. It's productivity and efficiency, our data amplification, supercharging our core products and our new growth opportunities. And I want to talk about each one of them individually.

The first is something that everyone should be talking about right now, and that's productivity. If people aren't talking about this, then they're behind. We're not behind. We've been ahead of this for a long time. I picked 2 of many examples to talk about today, but we look at this as a key staple and using AI in our business. In our customer operations, for example, we introduced AI to answer some of our chat and e-mail questions. And today, 84% of those queries are deflected into an AI system to answer those questions. Now when I talk about that stat, I always get asked, well, what have your CSAT score? Do people like that experience? Well, yes, because what happened was that freed up a lot of our staff to be able to focus on the highest complexity problems, the ones requiring the most empathy, the most care, our CSAT actually went up.

Of course, when you talk about engineering. How do we actually use AI and engineering? And we want to do this in a safe way. We don't want to be on the news, making mistakes with AI and engineering. And last year, our programs saw a 10% to 15% lift in our engineering programs. That's embedded in coding, reviewing, reviews, things like that. And we're just getting started in both these pillars. For example, in customer operations, we're talking about how we can actually create systems that allow them -- allow customers to resolve their own billing disputes, interact with live avatars, do lots of really interesting cool things. What more can we do in that space.

Even more excited on the engineering side, we introduced programs for agentic engineering this year. In the first quarter, we're already seeing 4 to 5x what we saw last year in productivity. We're very excited to see what those results will be by the end of the year. We're also talking about policy aware AI for compliance. We do a lot of reviews, as you can imagine, whether it's legal, security, in my office. We want to make sure what we're doing is safe and it makes a lot of sense. So having a policy-aware agent right beside us to help us make sure we don't make any mistakes is incredibly powerful. I just want to highlight this because we're not just starting productivity. We're already compounding it. We're trying to find out what's that next level for various different areas of our business.

CARFAX again. This is my favorite layer. We're going to talk about ingest enrichment and coding. We call it our data amplification layer. Acquisition of data and ingestion is hard all by itself. But to me, it's just a start line. We want to go beyond that. We want to amplify that. We want to use AI to find even more details after we already have the data in-house. Let's start with the ingest layer. We have all these partners, but what's really important to highlight is that we work with them and we take data however we can get it, whether it's text, images, structured or unstructured, data feeds, FTPs, you name it, we'll take it. We even collect some data through CD-ROM and fax, still, I'm not even making that up.

But we'll figure out how to make sense of it and how to bring it into our system so that other groups within the company can use it, leverage it, and it becomes a product that you guys see today on the floor. But we don't stop there. We know that each one of those records has more to tell. And we use different types of proprietary models to understand and unlock more value in each one of those records. Let me give you an example. When you take your vehicle to a service shop, they're typing up what they're doing to your car in the back, and they're doing this. There's typos, there's codes, there's different ways of saying things. Someone told me a long time ago, there's 1,500 ways to say oil change. I can count them all, but that's a lot.

We use AI to really understand what's happening to that vehicle and what hasn't? What was recommended? What did you decline? Because we need to understand the difference between what's in there and what actually happened to the vehicle. And that's incredibly difficult to do. It's something that we do every single day. An accident record typically contains at least 2 cars, maybe some more that all had a really bad day. You saw CARFAX talking about the point of impact and the severity earlier. So that information is in there. But there's other stuff in there that's very interesting, the intersection, the time of day, was there a fire? Was the airbag deployed? There's all sorts of stuff that we're really interested in learning for future products and things we might be able to do with that information.

And along the way, in this layer, we have compounded feedback loops as well. There's humans in the loop every stage that's necessary. Every time we do find something wrong, we make sure we correct it right away, upgrade the models, redeploy. We're always doing our best to make sure we maintain that 99.5% accuracy and the things we're doing in this layer.

And this is what actually powers the CARFAX. This is why he's talking right now, while I'm talking. All the data he's talking about, all the facts he's talking about come from this layer. Everything you see in the vehicle history report is this data amplification layer that powers that, simplifies it in a way that we can all consume it in an easy way -- easy way to do that within 28 million vehicle history reports a month. There's a lot of reports. It's a lot of technology that goes into making that data simple to consume.

But I love this because that base, that rich data set that we're getting from that data amplification layer, we can compound that. We can build on top of that. We can build forecast and we can build prediction systems. And we go beyond just the data amplification layer, and we really supercharge our core products. What more can we do? We can take them into a higher order of predictive capabilities that can only be done because we have that layer. These systems aren't possible without that foundational data amplification layer that we've created from our ingest and from our AI systems.

You've heard about reliability. That isn't just a feeling that the car might last a little bit longer than the next one. That's based on thousands and thousands of records of similar vehicles of that particular event, everything we know about these different vehicles, we're not just feeling like it's a good reliability. We know that it will be. And that does lead into other products like top repairs, how long the car will last. Where I would love to see it go to remind me what to expect of the next service visit, not just because of the OEM schedule, but because of everything that's happening in cars like that. Oh, I declined the bridge job last time I was there, that's probably going to come up.

Behavior prediction score, you heard about as well, our ability to understand what a consumer might respond to before they even show up. In our market response model, you can see about that on the floor, that allows the OEM to simulate incentive programs, understand what different types of levers might do to their incentive programs globally. All these are built on that rich data set that we create in the first 2 layers.

Bigger picture here is that these systems aren't possible without the proprietary data at the very beginning, the ability to ingest it quickly. I don't think we've talked about this, but there's an example I'd like to use where if an accident happens, we have it within 2 hours on our systems, very, very quick. And then amplifying that further using AI and creating rich data sets that nobody else possibly can have. So those layers get us ready for what's happening right now. I've heard a couple of folks ask me today, and this is happening across the globe right now is this fundamental shift to agents, agentic workflows, things like that.

So our enterprise partners and everyone in this room, we're changing how we consume data. We do want to use agents to not just search, but maybe do things autonomously for us, maybe find vehicles that I'm looking for. I'm in the market, just go find me something that I want. That's where we're going in this space. But so are our commercial partners. They want to use agentic AI workflows. They want to consume data through MCP servers, model context protocol servers that the language that agents communicate that we can expose the data that we want to expose to those agents and provide them the power to make the decisions they need.

Some of these things are already in motion. We already have internal agents to unlock data for our ideation and product discovery. We really want to empower people within the organization to think about what's next. We're designing infrastructure to monetize those agents. I had a lot of good questions already today about how do you monetize MCP service and agents. I think people are trying to figure that out. We're already ahead of that, trying to figure that out, too. And of course, we're trying to think of what are the higher value use cases in this layer. What else can we do? Because I feel like this moves us up the value chain from providing data to providing actionable intelligence and answers directly.

Let me give you an example. Scott talked about the buyer at the dealership. Tens of thousands of dealerships all have this person. They have to go and buy vehicles for their lots. And today, we aggregate all that data and they use all this data and they're figuring all these things out. I think the numbers you use were they buy 5 cars out of 300. That's a lot of work. That's a lot of time and money spent every single week trying to find vehicles. Well, we're already building agents to help them in this case. Agents to understand what they prioritize. They prioritize profit, time to market, certain mix models, maybe a clean CARFAX report, what is it that they prioritize. And then you combine that with intelligence about what's going on in their community, what other cars are selling, what the cars are not selling.

We bring all that together and we can provide them the answer. We can just tell them go buy these 5 cars, right? Don't spend that time going through 300 different vehicles, just go get these 5. These are the ones that will fit your business. Maybe one day, we even give those agents a balance and allow the agent just to go buy the cars and just notify the buyer when they're going to show up. Now there might be some skeptics in the room and they go, that's not going to happen, but it might happen. It might happen soon. But that's what we're thinking about is how can we automate these workflows and how can we change them and empower our customers to do more. That time that they're not spending going to 300 different rows, they can spend with the customer or spend on strategy or think what's next for their business.

So all of that, though, is just things we're doing, and we're just getting started. To me, this is the biggest opportunity that gets me excited about Mobility Global. We have this proprietary data moat. We're enhancing with AI all the time. We're super excited about that. But if we can unify this all together, all of our data, all of our AI strategies into one cohesive strategy and create enterprise AI data fabric, that will securely connect everything, allow us to manage and govern our data across all of our ecosystem, allow us to create all these new ideas and new products, allow us to prototype faster. I want us to get into a position where we're prototyping ideas at a huge fast rate. Lots of them aren't going to work, but that's okay. Let's prototype faster. Let's get things to the market quicker. Let's see what our customers want. Let's get to market as quickly as we can and help our customers power their futures as well.

And this will be the beginning of our ability to provide AI-first products. We'll have that mindset of how do we create these from the ground up to be AI first. And only that, this is a major operational multiplier. If we combine all these things, we can do things that supercharge in all of our data feeds. Some of the layers I talked about before, we can do more of that. We can get lower unit costs. Because again, there's economical side to this. We can't just throw all this all, it's very expensive. I'm happy to talk about the numbers later, if you want. It can be really expensive. We can lower the data costs, and we can create new predictive intelligence products. And this isn't years away. We're already talking about this and we're already on our way. Over time, I'm going to flashing red light at me.

So in summary, I really want you to take away that AI is not replacing the need for a company like ours, actually creating a global demand for our data because the data we provide is decision grade. The kind of decisions our customers need to make and everyone in this room needs to make, we can't make with just good enough data. We need to know that it's decision-grade data and only we can provide that. And then we have years of AI experience. We're not just getting started. We're not at beginning. We have nearly a decade of experience, hundreds of people working in this space. We are amplifying this business every single day. And that's what drives all the rest of our growth. And just finally, we are ready for the agentic AI revolution, and we're right there with our customers to be ready for it, too. Thank you, everybody.

All right. Good morning. Still morning. My objective is to finish before noon. So I always laugh when Tejal says, I want to save the best for last because I know you do exactly what I do when you had a big presentation. You go right to the end, you look at the numbers, you start there. I got a lot of great questions today. So I'll hopefully provide you some context for those numbers, bring it all together, right? The great stories, business strategies, data that my colleagues have shown, I'll put it into a financial context for you today.

But before I do that, I wanted to just share a little bit about why I decided to join Mobility, what makes me so excited. First, the team, right? Folks you saw up here, my colleagues and friends and the leadership team, the extraordinary people you met out there. It was funny. I was supposed to at this point, say, well, I really hope in the break, you go engage them, but that's happened already, right? And there's a reason why we started there because our people are amazing. And then of course, the 3,400 people at Mobility, these women and men, they're just -- they're innovative, they're customer focused, and they are deeply, deeply technical. So that's number one.

Number two, the assets are pretty awesome. I won't go through them again, but what a foundation on which to build. And number three, spinning this company out and going public is going to be a lot of fun, right? It's exciting. And I'm quite confident that Mobility Global is only going to get stronger as a stand-alone public company. So with that, let's get into the highlights.

We are a compounding organic growth engine, right? That's the core. That's the fundamental to our value proposition to you and our value creation framework. It's what we do. It's what we're focused on. It's what we will do. That is number one. On top of that, we're relatively unique in that we have this great compounding organic growth engine, and we're a high-margin business, right? We high margin because we create a lot of value. We're high margin because we have good operating leverage. We're high margin because we continue to innovate. Growth, margins, that generates a lot of cash and supports a strong balance sheet. We intend to use that cash and that balance sheet to create significant additional value for investors through a disciplined approach to capital deployment. We think all that adds up to a compelling investor value proposition. Bill touched on it. I will describe it in a little more detail. And then perhaps most important, it's why we're here today, we are on track for a 2026 -- mid-2026 public company launch. It's going to be a lot of fun.

But as I said, growth is the key. You heard this from Bill. You heard this from Joe, you heard it from Scott. We are a compounding growth engine. I do want to highlight a couple of things just to reinforce some of the messages you heard today, highly subscription-based, increasingly diversified, right? All parts of the business are growing. Everybody is pulling on the oar with one minor exception, recall business. We don't have a lot of -- we can create demand in a lot of places. We can't create demand for recall. But everybody is pulling on the ore. And going forward, we expect to continue to deliver consistent organic growth. You saw we just reaffirmed guidance for 2026 at 7.5% to 9%. We're going to continue to compound in 2026. And going forward, we hope we see some potential to take that top side up. We are targeting 7.5% to 10% organic growth in the medium term. We will continue to compound.

So I thought I'd take us back. The point of this chart is we are not just countercyclical. We're relatively acyclical. If you go back to 2014, right? Auto industry and the broader economy have gone through a lot of perturbations, a lot of change. But we've kept going. Now each of these markets are different. I've heard stories. Some are easier markets, some are tougher markets. This is the year we're grinding it, to be honest, right? There's a lot of work to be done. We're making progress. But look at the remarkable consistency of that growth, particularly if you average the 2 COVID years, right? We didn't just "recover" in COVID and get back online. We actually made up for the first year in COVID.

So is it always easy? No, right? But why does it hold? There are some structural reasons. There's some natural hedges in the business between new cars and new cars, used cars and new cars between different players in the automotive ecosystem. But more than that, it is the value we bring. And I hope that has come through for you. And it's actually -- I think the thing that surprised me the most as I learned the business as a relative newcomer is we are on the revenue side. The vast majority of what we do is on the revenue side. You heard it from Scott, you heard it from Joe, you heard it from Bill. We provide the information that makes transactions happen. And transactions are valuable, right? They're valuable for the OEMs, for the dealers, suppliers, for the consumer, right? So we are not discretionary in the vast majority of what we do.

And lastly, you don't grow this consistently for this long without changing, right? And I hope you heard that today as well, the capacity to change, to innovate, to adapt. So I won't belabor this. You've heard quite a bit about it. But the subscription-based model does provide a tremendous amount of predictability for our business. Our retention numbers are excellent. You don't grow as consistently as we do without the ability not just to retain customers, but to continue to upsell to them because we provide more value. We expect these numbers to continue to increase through the Lifetime Dealer Program that Scott mentioned, a lot of what Joe described in terms of where he's headed. And as a CFO, this is great, right?

The stability of the revenue stream is a real asset. It allows us to plan the next wave of investment and manage the business, right, at the same time, so we can keep that flywheel growing, right? The next wave of investment to fuel innovation to fuel growth and to fuel diversification. So this adds up to a strong business. $1.75 billion in revenue, increasingly diversified, building on a core of products and solutions, taking them to new customers. And we expect this to continue -- this trend of diversification to continue as well. We anticipate continued diversification across the business lines. You've heard about some where we're taking our core products out in the hall across geographies and across customer sets.

So as I mentioned, Mobility Global is relatively unique, right, compounding growth, subscription-based model, very predictable, increasingly diversified and also high margin. Our margins have been on an adjusted EBITDA basis in the 40% range, give or take, over the last 3 years. Very stable and starts with unit economics, right? Our stuff is valuable. We produce it in a way that's efficient, strong, strong unit economics. This produces growth that coupled with operating leverage, provides us the ability to continue to invest while maintaining or expanding margins, and we anticipate that to continue.

Now we are going to see a period of brief margin reset. There's costs associated with becoming a stand-alone public company. I'll describe that in a minute. But after that, we expect margins to increase at a steady pace. Now, at the root of this, is not just unit economics, but the fact that our strategic assets yield significant economic advantages. You've seen this wheel a lot. I want to sort of highlight what it means from an economic standpoint. And I'm going to start with the bottom right. It's always hard to do this in the opposite direction.

Number four, we're embedded in decision-making, right? A lot of what people think about when they think about being embedded has sort of negative connotations, right? It's a moat, it's stickiness. It's hard to replicate. It's this and that, that is true, right? But the real value, the real value of where we're headed for growth and innovation is how well we know the customers, how well we know the market, how well we can tailor products and solutions to them. Many of these products are being built, they're co-developed with our customers. They're inside our development process, and that's hugely impactful for us from an economic perspective because that, coupled with, number one, the power of the proprietary data estate that Jeremy described so well, building on what you heard earlier today, allows us to build solutions that are better, faster, cheaper, right?

We have the data. We have the depth of the data. We have the breadth of the data. We know how to manipulate it. It's on top of a scaled AI platform, not perfect. We had a long pedagogical debate, I think it was last week about whether fully AI native or partially AI native. And I'll let the experts handle that one, but we are well up the curve, right? So we know what people need. We're developing it with them. We've got the data to do it. We've got customers who trust us, who are welcoming us in. And we've got a distribution network through our unmatched customer reach that provides significant economic advantages. So that's how we sustain our margins going forward.

So let me translate some of this for you. We do expect on the right-hand chart of this slide -- side of this chart that there's going to be 3 impacts of building a stand-alone public company foundation. First is an incremental $20 million to $25 million in run rate expense for standing up a public company. It's nontrivial, integrating on Mobility. That's going to occur. We'll hit that run rate in sort of 12 to 18 months. That's at the same time that we're ramping up as we're ramping down the TSA from S&P. They've been phenomenal partners. We love working with them. I think we're also looking forward to standing on our own.

And then lastly, our equity compensation is going to increase to be in line with public company peers. I think list, right now, we're at the 1% range, a little more, but we anticipate that being more in line 3% to 4% with our public company peers. That's a huge advantage. I know a lot of -- I've already gotten the question about how are you going to align management's incentives to investor incentives. This is how you do it, right? Stock-based compensation is a great tool for public companies, both to align incentives and to attract and retain talent. So there is going to be this sort of period and reset. I think it's important that we're transparent about that.

And at the same time, we're going to be driving margin expansion. It's not going to -- you're not going to see it necessarily in the first 12 to 18 months, but it is there, right? And it's there for all the reasons on the left-hand side of that. higher-value products, we talked about quite a bit. The advantages of acting as one, both on the revenue and cost side, ultimately, operating leverage that comes with growth, that comes with a scalable business model. That's already in place. And the AI-driven efficiencies that Bill talked about and Jeremy described in more detail. And we anticipate that over the medium term, that will provide 50 basis point margin expansion or more even while we're investing to fuel the next waves of growth because growth comes first.

So as a result of growth, margin, margin expansion, we generate a lot of cash flow. These are the numbers in the Form 10. I do want to call out on the left-hand side, a few things that I think are important when you bridge from legacy to where we're headed. The first is, along with the run rate cost, there is going to be a onetime cost of standing up a public company. S&P has already spent a lot of money to help us get there get here. We anticipate spending a little bit more in the first 12 to 18 months, $75 million to $100 million of cash over the first 12 to 18 months to fully stand this thing up.

On the other side, our medium-term effective tax rate, we expect will be lower than what you saw in the Form 10. We have a set of initiatives already underway that will get us to the 25% to 27% range, I think, more in line with what one would expect. And then this was called out in the Form 10, but it's material enough that I want to make sure I highlight it here today. We are inheriting a $1 billion deferred tax liability associated with the IHS merger, and that's going to impact our cash to the tune of approximately $80 million to $90 million per year over the next 12 years.

So -- but all told, the power of our organic profit growth and cash generation is going to support a strong investment-grade balance sheet. That's the next slide. This is what we anticipate our balance sheet to look like and our capital structure to be. We've already secured a $0.5 billion revolving credit facility that was completed last week. We anticipate adding approximately $2 billion worth of bonds prior to launch. So that's going to be the balance sheet side of that $2 billion, and this was in the Form 10, roughly -- almost all of that is going to be dividended back -- dividended, I can never say that word. Dividended back to S&P, but we are building up cash inside of Mobility. So we expect that at launch, we will have $150 million or potentially more on the balance sheet to start us off.

And the bottom piece I do want to spend a little bit of time on. We do believe we are going to be an investment-grade company. It's important to us. It's consistent with how we manage our business. So we expect that we will expect -- we will manage this business to a target gross leverage ratio of 2.5x or below, likely start off a little bit higher than this. But given the power of the business that we've talked about today, we'll delever relatively quickly. So that's the balance sheet side gives a lot of capacity to generate additional growth and value for shareholders.

Here's our capital allocation framework. Start on the right. Organic growth comes first. We are a low CapEx business. This is not going to consume a significant amount of our capital, but it's going to come first. And you heard about some of the areas, both on the AI side and in the business that we expect to invest. That said, our CapEx will remain relatively low. The middle, I'm sure, is where you're most focused. We are targeting returning 75% or more. I've already received a couple of questions about the 75% or more of free cash flow to investors. That will come in 2 forms: a dividend with a dividend payout ratio of 20% to 25% of net income that will help us maintain our -- the dividend aristocrat status that we're inheriting from S&P as well as share repurchases through a balanced approach.

I'll note, we're likely not going to do share repurchases until 2027, just to give things time to settle, but it's going to be a consistent mechanism that we employ to return value to shareholders. And of course, if we're growing, delevering, we'll have additional balance sheet capacity, either to return more capital directly to shareholders. That's the plus there or to do M&A, targeted tuck-in M&A. We are an organic growth company first. We don't anticipate doing M&A -- any M&A in the first 6 to 12 months, certainly. But on a situational basis, when we have a strategy, an organic growth strategy that we think we can accelerate through M&A, we'll entertain those opportunities. So that's capital allocation.

But growth comes first. And you've heard a lot about the 3 buckets. I wrote them in a slightly different way here. The core growth, new solutions, and as Scott likes to say, taking our show on the road, although honestly, we're already on the road, we're taking it further down the road. This is how we get to 7.5% to 10% organic growth over the medium term. Of course, it starts with the core, right? The core, the stable foundation, the 5% to 7% revenue growth visibility that we typically have every year. That's a great place to start. And it's a place that we delivered consistently over time. You add to that new solutions. And I will just say, as an editorial, in some ways, these aren't even new, right? I mean you saw most of them out in the in the hallway here. They're already launched. There's the next wave and the next wave and the next wave of solutions that the team is already planning.

Bill mentioned this, I think, in some ways, our bigger challenge is how do we gate that and structure it, something that Bill and Martin Metzker, our Chief Strategy Officer and I are going to be working with the team on so we can sort of build in a sequential way over time. And then there's upside in international that we have all described, supported by One Mobility synergies, we expect that, that will generate 7.5% to 10% annual organic growth over the medium term. So growth is the foundation of our framework for investor value creation, pretty simple.

Growth on the right, we think we can get between 7.5% and 10% margin expansion after this period of reset. That should generate 8% to 11% annual organic adjusted EBITDA growth in a capital-efficient business. We can return a significant amount of that back to shareholders, the 75% plus of free cash flow we discussed, inclusive of a stable, consistent dividend. And we're still delevering. We're still building up cash to either deploy more capital back to shareholders or for tuck-in M&A. Organic profit generation, consistent capital returns, great investment.

So we are on track for a mid-2026 public company launch. I do want to take a small break just to thank S&P. We wouldn't have gotten here without them. It's been an extraordinary effort. We think about all that we've accomplished already, whether it's the initial Form 10 filing, it's the announcement of the leadership team or the construction leadership team. It's some incredibly productive discussions we've had with the rating agencies. It's a revolving credit facility. It's the new Board that we just announced last week, which is awesome, the public 10. It was a Form 10 public flip.

Being here today, really exciting opportunity to sort of begin the conversation with our investor community. We are on track. We look forward to continuing this conversation with you as a public company as we go public, we do our first earnings call. We hit the road to do equity roadshow and bond roadshow. It's going to be a lot of fun. It's a phenomenal business. Hopefully, you've really enjoyed the opportunity to hear not just from people on the stage, but as important the people out there about this business and their passion for it.

So let's get this conversation started. I think now is the opportunity for Q&A. And Tejal, I believe that I have caught us up fully. We are back on track. Hopefully, this gives you a sense of the culture of this team, right? We bring our own shares.

Two questions. On the algo, is that particularly -- I'm going to say Matt but everybody, is that intended for every year? You call it medium term? Is that 3 to 5 years? And is that every year? Or is that a CAGR? And then my second question is about the competitive landscape. Could you just comment on how Mobility competes on the CARFAX side versus experience order check product and then of course, on the Polk side versus mobile data [indiscernible].

Sure. So let's break that up into 2 parts. We'll take the first one, and I'll kick that over to Matt, and then I'll have Scott and Joe help me out on the second.

Yes. So the question, if you couldn't hear it online, was about the growth algorithm. I think the third to last slide that I went through. We say medium term, I would think of that as sort of '28 plus a couple of years. If you think about -- we're guiding to 7.5% to 10% this year, right, or 6% to 9% this year. So the medium-term growth algo is 7.5% to 10%. All that says if you believe the 7.5%, then obviously, we've got a tremendous amount of stability and predictability in our business on top of all the new things that were -- that we're launching both in B2B and CARFAX. And then the 10%, can we add an incremental 1% to our current year guidance through some of the new growth opportunities and international expansion, plus One Mobility. We believe that, that's feasible. But I would think of that -- we're not giving specific guidance. It's a framework, but I would think of medium term as sort of meaning 2028 and beyond.

And [indiscernible] be a CAGR or should that be the target range every year?

That was target range every year. And I think that should end up equaling a CAGR over time, but there you go. And I think the second question was about...

Yes. Second question was about competition. And the way I would frame it is this, is that we have the 2 life cycles. You saw the new car life cycle, which is Joe's world and then the 1.5 billion vehicles that are on the road today. And if you think about it, we don't compete with anyone directly across that entire thing. And so when you look at a life cycle, I'll use Scott's as an example. Scott has a different set of competitors that each stop in that life cycle, right, whether it's shop, buy, service or sell. And Joe has the same thing as you go around his life cycle. But I'll let Joe comment on what we're seeing in the B2B space and then Scott on the CARFAX space.

Yes. So relative to the planning side of the house that you mentioned, I think there's a fundamental difference there in the level of detail we go to versus the alternative that's in the marketplace, and we've branched off into a number of different additional products that get built off of our forecasting data set. And if we do typically see that competitor, it's a low-cost alternative to what we're providing and a very, very different product.

On the sales side, we have competitors that operate at different points in that life cycle. And in our core market reporting, legacy Polk business, that's certainly there. But we've wrapped around that core data asset, many, many more assets. So as we extend out and add inventory data to that mix, as we add pricing data to that mix, it's opening up and moving us into close adjacencies where they're just not competing. So we're kind of knitting together this kind of full life cycle that really they haven't been able to do.

Scott?

Yes. And on the CARFAX side, let's talk about the vehicle history report, which is our flagship product. And we talked a little bit about here today that it's driven by what consumers want. And consumers are about to spend a lot of money on a car and they want the answer. They want the right answer, and we have more data available to answer those questions than anybody else, and we showed a little bit about that today. More important, they want that data and answer around a brand that they know and trust. And when you talk to a dealer, they say, wait a second, I can build my consumer confidence with a relatively low-cost part based upon -- as a percentage of the total price of the car.

Cars continue to go up. The cost of the CARFAX report as a percent of that continues to decline. So a dealer looks at that and says, it'd be crazy to try to bring an alternative in here to try to inject that into the process. The consumer walked in and said, show me the CARFAX and you want to put in brand Z in front of them and the dealer loses confidence with the consumer, the consumer decides I'm going to leave. And the dealer does not want that.

And the consumer never [indiscernible].

We do have some consumers that come online, and we welcome it. If anybody would like to do it today, we'd encourage you. You can go online, employ your credit card. Most consumers, though, the typical scenario is the dealer makes it available at no charge online and in their showroom because it builds that confidence.

Toni Kaplan from Morgan Stanley. I was hoping we could talk about proprietary data that you have. You talked a lot about why the shops might give you the data. But maybe talk also about do you have long-term contracts? Are they exclusive agreements? Anything else in terms of trying to really solidify that you're consistently going to be getting this data and no one else is.

Yes, sure. And I'll tell you kind of how we think about it. Like you had mentioned the shops, and that's probably a good example. We first started building those relationships 20 years ago. And at that point, that our data assets and all of our assets combined we're nowhere near where they are today. And we're able to offer parts of our assets to that shop. And it's grown over time as those assets have grown. But Scott and his team are firsthand working on that exchange. And I think that what they've done is really an amazing thing, but we're able to pull that data, but we're driving their business. And as our exposure gets greater, as people look at more reports and do more and more, that value back to them just has continued to grow.

And maybe, Scott, if you'd walk through 1 or 2 of those value exchanges, I think it's helpful.

Yes. So I'll give you 2. One, we talked a little bit about was the service shops. So they get data back, and that returns them things that they can do that benefit their business. So that is the way that we build that deep relationship where they're fully committed to working with CARFAX because we help them operate their shop more efficiently. They make more money because they're able to better diagnose the vehicle and repair it better. And they know that they're also getting advertising from CARFAX because we put their name right on the report. So they like that.

So that builds that deep relationship where they don't have any need to work with anybody but us because of the value exchange that they get that's so tangible. We also do that with police agencies. And police agencies work with us, and you can see we have more than 6,000 that do so. And we provide them with tools that they can use to help investigate crime using our information, which is very, very powerful for them. And so we give them access to that information so that they can actually solve crimes better, which is their mission.

And that's why they want to share it with us. So those are 2 examples. And we've built those value exchanges relationship by relationship times 177,000 data providers. And that's the way that we feel like we build the unique asset that we have that can't be replicated and is hard for anybody else to come in and provide.

Are they exclusive agreements?

Are they exclusive agreements? I mean there's -- we have 177,000 of them. It's a mix. But in that case, we would prefer that the value that we deliver creates the relationship. And they're solving a really big problem. Shops have a massive problem. And that is that every year, they lose 22%, 23% of the vehicles that they work on. right? If they could run the best shop in the world, have customers think it is the greatest thing, but that car is going to change hands and they will lose that vehicle, and they have nothing to do with it. And there's a big problem, which is they don't know who now owns that vehicle. And there's no way for them to connect except through us.

We are that connecting tissue because what will happen, you can see it on a report out there. They'll give us the data. They've serviced that vehicle for the last 5 years, and it's on the CARFAX report. And then the vehicle gets sold and that consumer is using that CARFAX report to understand the vehicle. And now they own it. And the likelihood that they go back to that shop goes way up if those are on there because I know that shop knows this vehicle. They've been working on this vehicle, now I'll go back there. And so that's one of the biggest challenges that both shops and dealers have in their service base, and we're the solution that connects them to that next buyer.

Jeff Meuler from Baird. A follow-up question, sorry. But can you be any more specific? I get the CARFAX brand advantage and market position advantage. But just from a raw data perspective, what -- in what ways is your data superior? Can you give us some metrics relative to what Experian AutoCheck has? And then for Polk, to what extent is the registration data public? Or where do you have unique data rights or nonpublic sources? And then anything that you'd want to highlight from either Market Scan or aMM in terms of unique data beyond what you already have with Polk and CARFAX that you put into those products?

Sure. I'll start, and then I can have both Joe and Scott help here. When you think of this asset, the 177,000 and how we have built it, it's a blend. And you'll hear us talk about it in a very big way. And sometimes the proof is in the pudding. I would tell you, if you go run a bunch of reports, you'll see exactly what that difference is. But if I could describe our culture around data a little bit, we're paranoid about it and the way that we build it. And what I mean by that is this, is that we have data sources that come into our business that nobody in our business, 3 people might know what those sources are. And we do that, we do that because this is such an important asset for us, and we'll put it under a code name, and we may have 500 people that touch that data source and may not know exactly which source that is.

This is part of our secret sauce. This is part of what we do. It's ingrained in what we do. And we're not going to put a map out there that says, you know what, anyone who wants to follow us, here are the 177,000 sources, here are the contacts there. Oh, by the way, this is the way the data comes in, so on and so forth. It has taken us decades to build and learn that. And when that data comes in, somebody said this, and I mentioned this at dinner last night, those 177,000 sources, when we built the relationships with them, and they said, what format do you want it in? Our response was any way you've got it. We'll take it in any form, any -- and we'll take it in and we'll figure it out and we'll learn that data and it will become part of this ecosystem.

We'll take it on paper. We'll take it in this format, that format. And we've learned that data, and we know that data. And when we have a feed and something changes in the feed, we've put the systems in place to understand that it did change. And we've worked with OEMs, dealers, municipalities, shops to get to the point where after 30, 40 years that we have that as a well-oiled machine. And it is a massive data advantage for us. And you probably won't hear me or anyone on our teams talk publicly about all the work we've done to create that, all the detailed work underneath to create that. But I can kick it to Scott.

Yes. I'll give you 2 examples. Number one thing consumers want to know before they buy a car is the accident history, okay? We go out and scour the earth to get that accident history, and we have the best accident information and we continue to extend that lead. The consumer wants to know the beginning, the middle and the end of every accident. They want to know the point of severity. They want to know what did the airbag deploy. All of these different details that we go out and get from many, many sources in order to compile together. Nobody else can touch it.

Our lead continues to expand there. The #2 thing consumers want to know is tell me about the service and the maintenance history of this vehicle. And they want to know that because that gives them a view into how long that car might last for them down the road because it was well taken care of before they got involved with it. We go out and we get that service data. We don't just add vehicle service. We actually provide the deep detail, and we use our intelligence to tell you exactly what was done and now more often, what even was declined. So you have a really good understanding of that. Nobody else can do that. Nobody else is following us. Our lead in that kind of data continues to expand.

Joe, maybe on your side, too.

Yes, just real quick on the Polk side. You mentioned the state data. And there certainly are barriers to that. A lot of organizations have tried to come in over the years and acquire that data. It's very complicated. There's trust issues at play. There's legislation issues at play. But it's not really just that. It's what we wrap around it. We're really driving a multisource strategy. So we're bringing in other data records that are validating it and confirming the information we have in there. So there's a ton of time being spent on that. And there's a lot of nuances to the way that data gets processed.

And we've had decades of experience understanding when it's coming from this particular state with this particular setup, like we got to treat it a different way. And it's really hard to take a very complex set of data that's supposed to mean the same thing, but showing up in so many different ways across 50 different variations when you talk about states that we've learned how to knit that together in a way that creates the best quality. And that quality shows up in the marketplace. Our customers use us. We are providing those core services to like over 90% of the volume in the U.S. market because we are the premium provider in that space because of applying those decades of intelligence to process that data.

Alex Kramm, UBS. Pretty big picture question on the growth algorithm. You didn't really talk about pricing and retention. I think retention, you mentioned very high, but maybe you can be a little bit more specific and in particular, talk about the different businesses and why you may have or have not lost clients. And then on the pricing side, same thing, right, maybe on a combined business basis, but also what areas do you have more pricing power, less? Maybe what areas have you not used pricing as much as a lever as you could and actually have very -- a lot of pricing power that you haven't used so far.

Sure. You'll start? I'll start. So I'll start with pricing. I understand the need and the desire for sort of P times Q, right? I mean we're not a software company, right? We're selling a lot of different solutions to a lot of different customers. It is both a business with a lot of commonality, but a lot of heterogeneity as well, right, when you sort of think about the solution customer intersection. So there's not an easy answer to that question.

Stepping back, I'll wrap it into the retention discussion. We actually had an NRR number in the presentation early on. We pulled it. It's a great number. We just want to make sure that we're comfortable with it and that it's replicable given how important it is. But you can imagine it's meaningfully north of 100% given our exposure to our current customer base -- you don't grow at these kind of rates if you're not both retaining customers and continuing to upsell them. I think some of the nuance around the price question in particular is, as you've seen, we're bringing extraordinary value to our customers every year, right?

So how we think about it is how much more value are we adding to customer A, right? How much is that worth? And then does that drive your subscription -- the cost of our subscription base up over time? And I know, Scott, you're doing a lot of thinking on the CARFAX side, Joe similarly on the B2B side about sort of how we optimize that. But again, this is not as simple as saying, we've got this very static product and every year, we're going to increase price by 3%, 4%, 5%. That's not actually how it works in reality.

But Scott, if you want to jump in?

Yes. I mean we are constantly adding more value. I talk about the vehicle history report for a second, right? And we are the leading provider of that information, and we continue to extend the value on it. We're now going to be putting future reliability on it. So now it's the past, the present and the future. And we can capture that in the form of taking value capture from dealers because the dealers are seeing overwhelming value in using that tool to help build confidence with the consumer at the time that they're ready to purchase a vehicle or that they want to maintain that vehicle. So it's designed to do that. And we're an ever smaller part of the total price of the car. So in the grand scheme of things, it is a no-brainer for a dealer to want to get on and stay on that program for a long time.

I want to talk about overseas, if we could. In your more mature markets overseas, if you will, like in Europe, just talk about the market dynamics there in terms of -- are you guys the only player in town there? Is there any other competitors there? But talk about Europe and then talk about your India and China aspirations, if you would, your growth aspirations there?

Yes. I'll take that and I'll talk about both sides of the business. So as I think of Scott bringing the CARFAX business to Europe, we've got a great position. I'll have him talk about it. And then you mentioned India or, say, China, both great markets. And Joe can talk about the business that we already have there and the teams that we have there and what we're seeing and what that opportunity is.

So maybe first, Scott, talk a little bit about our -- the CARFAX business in Europe and then Joe, maybe what we're doing with the OEMs and suppliers in China. I think that would be a good base of the 2.

So we've taken CARFAX into Europe. We've been there for several years. We're in a few countries there right now. Later this year, we're going to open up Germany, which is the largest market. There are no big, scaled incumbents there, but there are different players in different parts of the ecosystem as we go around that life cycle. But what we found is we continue to use our formula, which is go acquire the best information, combine it with our trusted brand and then connect it to the dealers and the consumers there. And we are building that model out that has worked here in the United States in more markets in Europe.

And then on a question on China and India. So we've been in China for decades working with them. That market has obviously transformed over those decades, and we have a great understanding of that market. Now it was maturing itself, a lot of players, I would say, early on, much less sophistication. As we've seen what's happened kind of post-COVID, the advancement in that market has gone significantly higher. We're seeing a little bit of consolidation on a number of players in that market. And now that need for data is accelerating a bit.

We also see the Chinese manufacturers now looking outside of China to get volume. And that's where we think we have a tremendous opportunity to serve them even beyond their domestic market there as they're reaching out and trying to get into other markets where we have the depth of data they need.

In India, we just acquired some core assets there to help us build out that business. That's, again, a maturing business. It's large, but it's still a maturing industry there, and we're on the ground. We have a huge team there that is eager to apply the things that we've done around the rest of the world into that market.

Manav Patnaik with Barclays. First, just to follow up on Alex's question, the 5% to 7% you've attributed to the core, which is value plus -- I forgot what you phrased it, value plus volume. So maybe if you can help break that out, how much is the volume in that component? And also just the structure of your subscription contracts? Like how long do you have price escalators in there?

And then maybe just one quick question on the international follow-up. It sounds like it's more of an organic build. So maybe just perspective with AI and these new tools like relative to what you did in the U.S., how fast can we expect you guys to scale there?

Sure. So do you want to start with the international question?

Yes. Why don't we start with that last one. I'll have Scott talk about -- he mentioned we're moving into some new countries there. And our -- we're taking the foundation that we have, but maybe Scott can talk about how we're taking that and changing the approach.

Yes. So in Europe, we are going into Germany, for example, we're opening that up later this year. We have large partnerships in order to distribute our data to some of the big marketplaces that are in Germany. And we have unique data available. The market has changed in Germany, and the VIN is no longer considered PII. And so that has enabled us. And again, because we are trusted, we are able to get access to the data in Germany in order to provide a vehicle history product there, for example. And so those changes have been a big change for us. But we are building on the same formula that we've taken from the United States into other parts of Europe, and we are going to continue to expand that. Consumers have those same questions. Dealers want to provide confidence and CARFAX helps them do that with the data and the brand that we bring to the market.

The growth algorithm question, you're right, it's value plus volume in the 5% to 7%. I think you see we're relatively well penetrated, right? So the majority of that is in value. But again, I wouldn't say it's exactly P times Q, right? Because as Scott mentioned, even inside the CARFAX business, the average dealer is only using 1.5 of our 3, soon to be 4 or 5 products, right? So we see significant upside there, plus when you add in the opportunity for cross-selling through One Mobility. I mean Joe, how many dealers is automotiveMastermind in right now? 3,200, right? And Scott, you sell on the...

40,000.

40,000, right? So meaningful opportunities there. Now is it in the core? Is that in the growth? Which one of those buckets is that in? You can argue that. But all this, we think, adds up to 7.5% to 10% over the medium term.

Great. We're going to take one more question from the room and then take one from online. Go for it.

Jason Haas with Wells Fargo. Can you talk about how you think the rise in autonomous vehicles will impact your business?

Yes. Great question. And pretty exciting stuff. I think it highlights the amazing industry that we're in. There's been a couple of articles that got a lot of attention in the last couple of weeks on the robotaxis and how they're growing. And I think they're going to play an important role. I think that people will ride in them a couple of times and get very comfortable with it. I think the numbers I saw were that there could be upwards of 6 million of them on the road by '35.

And the amazing thing about this industry, and I commented on it earlier, is that it's so big. There's 1.5 billion on the road today. It will be 1.6 billion 5 years from now and grow from there. So you're talking about 6 million vehicles in a fleet of 1.6 billion. And I think that we're seeing shifts in how people use Mobility. That change is great for our business. As I mentioned before, change drives demand for data and data is what we sell. So really, we love to see the innovation. We love to see these new things coming. So it's great.

Great. And the last question is a double header. It starts with the white space in the U.S. for both CARFAX and for B2B. And then it goes into with One Mobility Global, what are the data and revenue synergies that you're thinking about over the medium term?

So why don't we start with Joe and Scott, both talking maybe Joe first, Scott second on the white space that we have here in the U.S. and then we can...

Yes. We have quite a bit of white space. And like we do have a core set of flagship products, but we've created a number of products that branch off of that. And this is where Bill had talked about like less than 50% penetrated with the things that we have with the customers that we're working with today.

And then when we think about the cross-sell opportunities, there's 2 things I'll talk about here. One, Bill talked about bringing 2 businesses -- 5 businesses together. Well, 2 of them came together to create what we have in B2B, and that was automotiveMastermind and the legacy IHS, Polk business. And there's a tremendous amount of data just in that B2B business that's never gotten pushed into the dealer community as strongly as it could. And there's market analysis and other things that we know we can distribute through the Mastermind platform.

So we have a couple of products in the queue right now that will be connected into Mastermind and distributed out to that. And then same with CARFAX, that same data that we're talking about the dealers are interested in can flow through that as well. So as soon as we establish that and get that momentum built, we'll start pushing it through those other channels.

Yes. And then for CARFAX, the white space opportunity in the States is really huge. We have a lot of dealers that maybe use only 1 or 1.5 of our products. And so there are many more products that we have to offer those dealers, and we want to get them fully committed, have them become those Lifetime Dealers that we spoke of. And we've already gotten 1,600 dealers, but there's a big runway of growth opportunity to get the large base of dealers here in the States to get on to more products that we have to offer them.

One Mobility? What do you want to talk about, One Mobility synergies or...

Yes, I'm happy to. I mean we are bringing 5 businesses together. I talked about it in the presentation. And it's exciting to see where we had 5 teams doing very similar work where we're able to kind of bring that together and really streamline what we're doing. And we're also able, as we pull our data assets and some of the other assets together, see where the different parts of the business can use the assets from the other parts of the business. And we're seeing it both ways. I commented to somebody that there's a conference room outside my office. I saw 3 or 4 people from automotiveMastermind, 3 or 4 people from CARFAX coming out of it 3 weeks ago, and they were just so excited about the stuff they were going to be able to do together. And Mastermind knowing that consumer so well, CARFAX knowing that VIN so well and being able to kind of bring those assets to each other is really a great thing. So...

We're just going to hand it back to Bill for some closing remarks.

And I promise to keep it brief. I know I'm between us and lunch and us in the demo stands. So I did want to mention, we've had a number of us up here today, but we have our entire leadership team here today. They're here in the front row. I really want to encourage everyone to get to know them. It's been great. We've been working together the last 6 months and pulling this together, some of us for 20 years, some of us for 6 months, but it really has been amazing. And I want to leave you with just one parting thought outside of thank you.

Thank you for your interest in our business. Thank you for the questions. We do have demo stations set up outside. We want you to get to know our products. We want you to get to know our people. I started off today with a comment on 3 things that I wanted you to take away from today, and I'll end on them as well. First, the amazing enormous market, that $8 trillion automotive market that's going through massive change and creating massive amounts of demand for data.

Two, our unmatched assets. And I hope today, you started to get a feel for them and over time, you'll learn them more and more. And then three, the clear opportunity. I think we have the right team. We have the right strategy. We've put together the right assets, and we're going to go after that opportunity. So thank you for listening to our story today. We appreciate it, and we'll be around for the next hour or 2 for you to get your questions answered and see our products. Once again, thank you for joining us today. Take care.

All right. Good morning, everybody. I'll just keep this on time. Thank you for being here. For those of you who don't know me, my name is Manav Patnaik. I cover business information professional services for Barclays. I'm pleased to have back with us again this year, Martina Cheung, who's the CEO of S&P. So Martina, thank you for being here.

Thank you.

Martina, maybe the first place to start, I mean, it's been about 1.5 years since you took over as CEO. You've been at the company obviously much longer. But maybe just reflecting over this last 18-plus months, what has surprised you overall since you took over? A lot has happened in the market, of course, but maybe just from your position.

Yes. Well, I think the last 18 months has been phenomenal in the sense that we've been able to see, I think, more and more the importance of what we do in the market. And whether that is massive geopolitical disruption and the importance of our information, our benchmarks and our expertise to our clients. And you saw that, for example, with the record numbers that turned out at CERAWeek this year to be able to participate in dialogue around the future of the energy markets and the commodity markets at large, all the way to the importance of our unique and proprietary content in the conversations that we're having with our customers around how they get the best use out of some of the AI tools they're actually implementing themselves.

And so for me, it's -- it is general excitement, I would say, about the growing importance of the role that we play. And of course, the plan that we put out in November at our Investor Day is all the ways in which we will look at leveraging the set of capabilities that we have to grow our business sustainably over time.

Got it. One of the topics, obviously, that I'm sure you get a lot is around AI. And you guys were early with the concept when you acquired Kensho in 2018, people didn't really pay attention. Then last year, there was an aspect of AI is going to be good for everybody and then suddenly, it went to it's a disruptor. So what is your overall take, when you focus on the portfolio you have at S&P, what are the pros and cons of AI that you would talk about on a high level?

Yes. Well, I think, obviously, we framed it from the perspective of how we actually integrate AI with our products and how we create a great experience for our customers so that they're getting the benefit out of AI as well. And then obviously, we also have our own internal opportunities to integrate AI to generate productivity, to increase speed to market and to be able to create things that we don't create today.

And so I think on the top line for us, the advantages there are really persisting with the model that we've had for many years now around flexible distribution. So if our clients want to receive through Snowflake, through Databricks, through any number of third-party channels and now through these LLM providers, we're enabling that and the technology is giving us ways to enable that so that the customer experience is a lot better.

And so our ability to, for example, deliver our LLM-ready content through now the S&P Global plug-ins in Anthropic Claude for Financial Services, that's generating some very interesting conversations with some of our more sophisticated clients. And actually, we just did in Q1, we had a competitive displacement on that where the conversation for our data sets available through our plug-ins in Claude for Financial Services. This conversation was led by the Kensho team who demonstrated really the value of the combination of our plug-ins with our LLM-ready data, and that actually enabled us to displace an incumbent for the data set sales. And so we think there's a lot of additional value here, and it gets back to how we actually generate that value for customers.

Now I think if we go with pros and cons, there's been a lot of narrative around, well, these LLM players and some of these other sort of native AI start-ups could displace some S&P products and how do you think about that? And I start first with the customer. We always look at the customers and how those customers are going to evolve. And we have a very diverse array of customers, as you know. The adoption within that customer base is going to be lumpy and uneven.

We will have customers who are at the bleeding edge, and that is a very small number today of customers that are looking at how we would actually interact with them and build with them and within their internal environments that they're creating, all the way to customers who we have to actually help find the AI capabilities who don't use them today and many in between who will rely on the AI capabilities that we're actually building into our products like Document Intelligence, for example, in Cap IQ Pro or like how we are integrating ChatIQ into our Platts Connect product, for example.

And so I think for us, the -- we're certainly looking at this as a very strong net positive to the customer experience, whether that's by giving access into new channels or improving the experience on existing products. And all of those experiences, those new use cases, growth in usage, et cetera, all of that features into our price negotiation for Enterprise licensing come renewal. And so there -- that's where we see real tangible value for our customers.

And then I would say internally, think of it right now as -- we'll call it sort of like basic integration of AI across various different functions. For example, within our Enterprise Data Organization, we've seen really accelerated adoption of the capabilities. That's been happening for some period of time. They've been using some of the Kensho capabilities as well over a period of time within the Enterprise Data Organization.

And now we see opportunities to be more transformational in other areas of the business as well. And so I think there's some really great opportunities there to generate productivity will always be balanced. Some of that can go to additional product development or additional reinvestment and a lot of it will go to improving margins as we go forward. So I'm excited. This is a -- many people will say, of course, this is a massive step change or paradigm shift in our end markets and in how S&P operates, and I see that as an enormous opportunity for us going forward.

Got it. I want to come back to the revenue side, but you talked about margins being a big benefit. Is there any way to think about how long this takes? Like are you running duplicate systems? And when you shut off the old systems before you see the margins? How should we think about that kind of productivity showing up in the numbers?

Yes. So the -- it would be more about how we actually transform the roles across the organization. So our people expenses are our largest expenses. I can tell you the first example, we tried to be -- to lean into this, I would say, over the last 2 quarters. So we've -- obviously, we've said that in the Enterprise Data Organization, we'd expect to see about $100 million of run rate benefit in 2027 from the integration of AI. That's a combination of creating the Enterprise Data Organization and reducing redundancy and more classic productivity as well as what we would see around the integration of the capabilities and actually automation of stuff that may have been done manually before. And so that's a good tangible example. That's on a base of about $450 million in terms of run rate.

Lots more to be done overall, I would say. I think the thing that's very important right now, and you may see this in your own organizations as well. But if you think about an area that's a classic opportunity for AI productivity, that would be in engineering, right? Now much of what we do, we're not selling toilet paper. Much of what we do is actually running critical workflows for our clients. And we are essentially, in many cases, trying to change the wheels while the car is actually running, right? So it's really important that we do this in a very systematic stepwise way.

This isn't just the integration of the tooling. It's the actual complete change of jobs and roles, right? So we think of it as agentic software development life cycle and how a classic software development life cycle would work with various different, very predictable roles, whether it's quality assurance, engineering, the user story generation and all that sort of stuff. All that's going to change in that life cycle. There will be new roles. People will need to transition into those new roles. The agents will then need to pick up the stuff that's been left by the people. And so that requires time.

And we have a lot of activity happening there. We have one agentic SDLC project happening across the organization right now with 3 divisions actively engaged and then the fourth will come on board. And as we run these very thoughtful and careful POCs, then we'll learn a lot and be able to accelerate into it.

And so this bigger transformation, and I would characterize that as really transformational. Those opportunities were not factored into the guidance that we gave at our Investor Day in terms of our medium-term plan, and we would expect to see that generate some incremental margin over a period of time, I would say, a longer period of time.

Got it. And maybe just one follow-up to that. I think people underappreciate the value of Kensho at your organization. You guys talk about it a lot, but maybe a few recent tangible examples on how having them has been an advantage in today's period of rapid change with all the technologies out there.

Yes, absolutely. So Kensho Labs, which is essentially just the term that we're giving for Kensho is almost like a forward deployed engineering team helping our clients. This team is really -- it's getting down to helping our clients actually extract the value from the tools that we're offering. And so they're talking, as we said during our earnings call last week, they're working with about 25% of our CCO accounts right now.

We have several examples, a couple of the ones that we thought were interesting signaling. And I say this, it's important because it's still very early days for many of our clients on this, and they're testing things out. And I say that even the most sophisticated of our clients are testing a lot of this stuff out and trying to figure out how to get the value from it.

And so we have one large, extremely sophisticated global bank that has leaned into AI very heavily. And the Kensho team worked with the Market Intelligence team on a recent very large renewal. What they were able to do was to demonstrate the value of our data in this particular client's internal AI tool that they've created themselves. And as a result of that work and part of the renewal, the client basically standardized on our data for all of the content that they needed for those data sets essentially within their own internal AI tool, but they also expanded the Cap IQ contract.

And so it's an interesting example of what we're seeing, which is even with the most sophisticated of our clients, you're going to find areas in the organization where tools like a Cap IQ with our own embedded AI content will persist and grow even while they are using and standardizing to our AI-ready data for other use cases in their own tools. And so I found that to be very, very interesting because they're so sophisticated and a good and interesting signal for us going forward on this.

So Kensho is really key to some of these conversations. They're key to unlocking another opportunity, which is that clients just have an increased appetite for other data sets and the Kensho team is very quick to be able to show the clients how some of these additional data sets can actually generate value for them as well. And so exciting times. They're very, very busy right now, I would say.

Okay. Got it. That's helpful. Talking about Cap IQ, let's focus on the Market Intelligence business. That's your largest segment. It's also where most of the debate is on the stock in terms of the AI topic. But before we get into that, maybe just to help the audience appreciate MI has a lot of different businesses or subcomponents in there. So just how you would break out that mix between the Ratings resale, desktop, et cetera?

Yes, absolutely. Well, I will start with -- and acknowledging your point around MI having generated so much of the dialogue, I do want investors to remember that our benchmark divisions generate over 2/3 of our revenue and about 3/4 of our profit. And so it's easy to forget that with all of the furor around AI and software and all that sort of thing.

Within MI specifically, what we were at pains to do over the last couple of quarters is to really help all of our stakeholders understand the value of what we have there. So there's one way to look at it, of course, which is that we have the Cap IQ solutions, including the desktop and data sets. We have the Ratings and some of the related credit products. And then we have the third group within there, which is Enterprise Solutions, which is comprised of many workflow tools and critical platforms used not just by our clients, but by entire industry groups and networks.

And so the other thing that we wanted to be able to do for all of you as we went into our earnings call last week was to help understand how we think about the intellectual property, the uniqueness, et cetera, of what we offer within Market Intelligence. And so you'll see from the additional disclosures that we made that about 12% of Market Intelligence revenues, what we would think about as perhaps undifferentiated. And undifferentiated is important, too, in the sense that oftentimes it's expected as part of the package. And so for example, we have a third-party redistribution news content piece that we would include in undifferentiated, and we've assigned other pieces of data to that as well. I would argue maybe a little bit conservatively.

The rest of what we offer is really broken down. So we have benchmark, which is essentially we are the distributor of S&P Global Ratings content, both the research reports as well as the data. That's roughly -- I think it's 23% of what we do. And then just over 1/4 of -- or rather over 1/3 of what we have in there is also workflows. And those workflows are comprised of many of these industry standard tools like Wall Street Office, iLEVEL serving private markets. A lot of those tools and critical workflows are not just critical for an individual client, but actually function as a standard for an industry group. So ClearPar, WSO, these are good examples of these tools.

And many of them will work with our own proprietary content as well. So for example, our pricing and reference data for loans is pumped through WSO. In iLEVEL, we offer increasingly unique data, including the first tranche of data offerings from our partnership with Cambridge Associates and Mercer. So that's the benchmarks piece, the workflow piece.

And then we have advisory and events piece, and that piece of it is very unique to us as well. Here, we would see, for example, some of the With Intelligence events with what we acquired there through the With Intelligence acquisition at the end of last year. And those events are incredibly important for us because they actually generate our data sets as well. So we have intentions and preferences data sets that are created from the actual feedback that we get from participants during the With Intelligence events that really are unique in the private market space.

And then last but not least, let's get to data. And we have 3 different sorts of data that we wanted to highlight last week. The first is curated, the second is contributed and the third is reference data. And the third one is very easy to explain in the sense that it is the -- it's what I think of as the glue. So it's our unique classifiers that when we use one of them, everything else links to it, and it becomes very easy for clients and entire industry networks to use that, whether it's GICS or LoanX IDs and other reference data.

The first 2 have their own unique attributes. So on the curated front, this is data that we've been collecting for decades. Oftentimes, because we've been collecting it for so long, it is actually not available publicly in a digitized format. And it's not the sort of thing where a startup, for example, could go out and scrape and collect, et cetera. And so good examples there would be Compustat financials or the SNL financials, Panjiva data.

And then the second -- the other piece of it there is contributed data. And so Visible Alpha is probably, I think, a really good example of that. We have contributed data in With Intelligence as well. And so those would be highly unique. The data that we are launching with the Cambridge Associates and Mercer partnership is also contributed data.

And so you look at all of this, this is all the way -- this is all the data that forms the basis and the foundation for the unique IP that we have in Market Intelligence. And we wanted to really provide as much information and transparency into that as we could last week because we think it's important that shareholders understand that just over 12% -- or just over 10% rather of our MI revenues are what we would consider to be undifferentiated.

Got it. Yes, I think that disclosure last week was helpful. I think just to double-click on the workflow piece of that business, I think one of the other things you did last week was also sell your software workflow of the energy upstream and focus just on the data. So one of the questions we obviously got was like, is that something you would consider on the MI side? Or maybe just help us differentiate why the MI workflows are different than the energy workflows you sold?

Yes. So the energy software portfolio is a group of software products that are highly specialized with very, very specific use cases. And I would contrast that to what we have in Market Intelligence, where a lot of the platforms that we have actually serve entire industries that have standardized around the actual platforms themselves. And so we run what I would characterize as industry standard workflows with ClearPar, Notice Manager, corporate actions, Debtdomain and then industry networked platforms. In other words, it works because an entire industry group is pumping information and volume through there like WSO, iLEVEL and others. And so these are large-scale products that are performing critical actions for our clients that are also embedded into compliance systems for our clients and in many cases, are supported by managed services that we provide through the Enterprise Solutions business as well. And so that, I think, is where I would kind of lay the differentiation there.

Got it. And then on the data side, I think, one, would be interested in your perspective, like a lot of people are thinking about the data desktop side, unbundling kind of like the media world had done. But there's another case to be made that there's a power of the bundle, to your point, even some of that undifferentiated data has value to it. So it sounded like from your Investor Day, this was a customer-by-customer decision, but I don't know if there's any views you would have on that today.

I would say we're leading very much with enterprise pricing on this. And we -- I think I might have shared at Investor Day or even in the last quarter, we've actually only had one customer ask us about unbundling and doing something different like consumption-based or things like that. And I think it comes back to really where customers are in their own journeys on this. Over a period of time, could we see maybe some tiering or something like that? Possibly. But we're not going to move away from the primary mechanism for pricing, which is the enterprise value that we generate for our customers. And because of that, we are letting our customers access our data through MCP.

We are distributing through third parties like Anthropic and OpenAI and others. And this is all essentially contributing to the conversations that we have come renewal that you'll see come up over a period of time as we actually renew with customers. And we're starting to get those really good indicators now and signals of value, and we began to give you some of those in last week in the earnings call where we saw, for example, API calls double just from February to March of this year. And those are the types of things that we're going to be tracking very closely over time so that we can actually have that value-based conversation with customers.

Got it. And then just on the MCP partnerships you talked about earlier, yourself and a lot of the competitors have obviously started throwing out how many partnerships and MCP feeds, et cetera, that they have. Maybe you can remind us of the stats, but the question is more around what exactly is the revenue model there? Or how does that partnership work? Like I think there's a confusion around what's being shared, what the model is, et cetera.

Yes, sure. So I'd separate it between the frontier models like an OpenAI and Claude for Financial Services or Claude otherwise. That and we'll call sort of like the AI-native start-ups, which are sort of like a different subset of partner. With the first category, which is the larger one, Claude for Financial Services and ChatGPT, there the principal -- and this is true actually for all of our distribution through these third parties is, a, the model player does not get to train the model on our IP. So it sits on our servers. And b, the relationship from a commercial perspective is with us. It is not with the third-party player. And so that's going to be true for everything that we do here.

I think that maybe the one difference that I would call out with the smaller AI-native players is that we have had a stream of inbounds from them because they have some tooling, but they have no data. And so they have been asking us for data. And because we partner with hundreds of redistribution partners, we've also been partnering with them. And there, we charge subscription fees for them to carry the data as a kind of a base cost, but our customers who want to access the data still have to contract with us. And so that's been interesting. I think for that, those start-ups, honestly, my expectation would be that we'll see some consolidation there just because of the capabilities that we've seen with the larger players.

Got it. And then just one more on MI on the -- in terms of the competitive dynamic, a lot of your traditional competitors are seeing similar things as you are. I think everyone is growing in that 6% to 7% range. At the same time, a lot of the start-ups are getting -- raising money at crazy valuations. So what's really going on in that marketplace? What are you seeing? Who's winning? Who's losing? What's going on there?

And this would be for the...

For the MI, for the desktop data.

Yes, yes. Look, I mean, candidly, on some of these smaller providers, again, I come back to the sophistication in Claude Cowork and Opus and other models that we're seeing. I think it's just going to be really hard if you don't have IP and differentiated data. And we have seen -- we've gotten inbounds from some players who are interested in us taking stakes in them. So I think that says a lot.

Okay. Fair enough. All right. Let's move on to the Ratings business. Maybe let's just start off with just current trends from what you saw last quarter and beyond. What is the current pipeline and mix of issuance categories look like?

Yes. So for us, I think the guidance that we've given for this year essentially calls for several maybe underlying assumptions. The first, obviously, we always start with the refinancing wall. That was 12% up year-over-year as of the end of Q4. We've seen a little bit of pull forward, but we're not assuming any massive pull forward from out years, for example, as you go throughout the rest of this year.

When we look at the non-refi piece of the transaction revenue line, there's a couple of sort of interesting assumptions here. So the first was of the $650 billion plus in announced CapEx from the hyperscalers this year, we had a couple of key assumptions. The first was not all of it would be debt financed. And the second was that not all of it will materialize this year. And so relative to our full year expectation on that, we basically saw some pull forward of hyperscaler issuance into Q1, again, relative to our expectation.

If we were to assume a more even spread of hyperscale issuance such as it was last year, which we're not assuming right now, it's possible we could see a little bit more on the transaction line for the full year. But we're sticking with our views. We think it's just too early in the year right now to adjust otherwise, particularly with some of the uncertainty around the rest of the market with the continued geopolitical strife in the Middle East and when that could end, we're assuming in Q2, every day, it's like you see something that says it could and something that says it might not. And so those are some of the pieces. But generally, a stable mix of IG, high yield. We'd expect to continue to see IG play a key function throughout the rest of the year as well. So that's -- those are some of the puts and takes there.

And maybe just one more on M&A. What are your assumptions there? What have you seen?

Yes. Look, we've been thoughtful on M&A. I mean, interestingly, M&A was very healthy because of some very chunky large deals in Q1. And even without the hyperscale issuance because of M&A, IG would have grown in Q1. So pretty healthy quarter for that. I think we've taken what I'd characterize as a prudent outlook for M&A for the year.

Got it. Private Credit, obviously, a big topic out there as well. Maybe first, high level, are you -- from what you guys rate, from what you guys see, is Private Credit a systemic issue? Is it just narrow pockets? Like what are you seeing there?

I'd say the first thing that's important to, as a sort of a frame of reference for my answer is that when I talk about Private Credit, it's the Private Credit that we rate at S&P, and we don't rate everything. And there's good reason for that because we have methodologies that some issuers may not find suitable for their objectives.

And so from our perspective, as our analytical teams look at the overall landscape, they're seeing some elevated risk, but nothing that we would consider as systemic. And there have been some couple of high-profile things over the last 6 months or so. And the view from the team is that these are idiosyncratic examples of fraud, et cetera. Now clearly, there would be some sectors from time to time that would show different stresses, but that's going to be specific to that sector basically. So by sector, I mean, it could be something like retail or that kind of thing.

So I would say, as a general statement, the team doesn't necessarily see what perhaps in some media would be characterized as catastrophic. Again, that's our portfolio that we're looking at, right? Generally, the private markets continue to be a really good opportunity for us. I mean, obviously, we exited last year well north of $600 million. And in Ratings in Q1, we saw about a 25% growth in the Private Credit revenue. So it continues to be a very healthy contributor.

Got it. And maybe talking about margins and adding index to the question here. But I think people would agree Ratings and index benchmark is probably not disruptable. But to your point in using AI for a lot of internal efficiencies, productivity, like the already impressive margins in these segments, are there more opportunities with the use of AI?

I think we would definitely see the potential for what I would characterize as more differentiation in what we do. And that's how our Ratings team, for example, is thinking about this. So they were very early adopters of the AI tools. I think, in fact, they were the first group to get the Spark -- internal Spark product that we launched. And they've been using that, I think, to great effect. We've been using it actually in parallel with kind of a modernization of the underlying workflow within the Ratings analytical workspace.

And I think what we're seeing here is an opportunity to augment what we can do with our analysts, whether it's more high-quality and really differentiated research, putting even more content in front of them as a result of being able to sort of like synthesize and get that into their hands more quickly as well. And so there, we'd expect to see this as an augmentation in their capabilities and augmentation in timeliness and relevance and quality and things like that. And that's really the objective we're looking for.

We have taken advantage already of the early AI capabilities within Ratings in the non-analytical functions. But it's the analysts really there, we look to preserve that and improve and get as much as possible out of that capacity.

Got it. And if we just try and touch a little bit on the Indices business. What are some of the incremental opportunities you see being possible, thanks to the use of these technologies?

Yes. So our new CEO of S&P Dow Jones, Cathy Clay, is excited about the potential there for AI across -- again, across, I would say, sort of the internal functional areas, whether it's the product areas and otherwise. And so I'd expect to be able to perhaps move more quickly on product innovation, for example, particularly when it comes to ways in which we can be thoughtful about the types of things we can do with data.

And from the subscription line, I think there's some good opportunities there from a product development perspective. We're also being really thoughtful in Ratings and index on blockchain and how we think about both the external opportunity and the internal opportunity to deploy that. So I think it's sort of like a tale of 2 cities there with blockchain as well as with AI for both of those divisions.

Got it. Maybe we can just take a few minutes to touch on energy. We talked about, obviously, you're selling the upstream software businesses. So maybe with what you're left with, I know you lowered the growth this year because of obviously what's going on in the Middle East. But long term, how do you see that as a strategic part of your portfolio?

Yes. Look, there is absolutely no question that the energy portfolio is of critical importance to the world, really. And the reason why I say that is because of the 270-plus benchmarks and price assessments that we conduct, 15,000 daily price assessments that we do and you pair that with massive growth in energy demand that we see over the next several decades. That energy demand in and of itself creates demand for additional refined products. It creates demand for commodities. It creates demand for any number of downstream products that we look at as well. And so we are perfectly positioned with the stable of assessments that we have and the unique data that we have to really unlock additional value for our customers.

CERA Titan, which we launched at CERAWeek for our Upstream content, is one great example of that. But we're seeing massive uptick right now in the use of our chat functionality and Platts Connect. So when the war started, everybody turned to Platts Connect. Let me see what else I can find, et cetera. And the best way to find that is to use the AI chat feature, which has really seen a massive volume increase.

And so our goal here is to continue to play this central role that we play, thanks to this incredible franchise. You look at what we were able to cover at CERAWeek, we had 2,300-plus customers from over 90 countries, 11,000-plus participants. We had policymakers. We had hyperscalers come in and announce where they're providing their own power and as part of that dialogue. And as the convener of this important conversation and the provider of the independent insights to inform the conversation, I think we are just ideally positioned for this market as it grows going forward.

Got it. Maybe in the last 5 minutes, if we can touch on capital allocation and maybe use Mobility as a lead into it. Maybe just a quick update on the spin there and how that would change the capital allocation priorities once that's completed, if at all?

Well, the spin will not change our capital allocation priorities. We did announce that we'd expect this year to return over 100% of adjusted free cash flow, and then we expect it to return to our normal 85% framework going forward. The spin itself is going very well. I'm sure many of you, if not all of you are aware that, that team's Investor Day is coming up on May 12. And I wouldn't want to get in front of the management team on what their message is going to be. So I encourage you to listen in there as well next week.

Got it. And maybe just to focus in on the M&A aspect of your capital allocation. Obviously, you guys have shown us with the buybacks, the dividend. But how are you thinking about what are the areas of M&A that would attract you to doing some deals? It sounds like you have a lot of what you need, but just help us with what the white spaces or scale areas might be.

Yes. Look, our priority is always going to be on organic growth. And we laid out areas during Investor Day like private markets, energy addition, DeFi, supply chain. And these areas, in many ways, are areas where we can grow with little incremental investment. We have an incredible stable of supply chain capabilities and assets and the ability to sort of bring them together more effectively from a go-to-market perspective is a real opportunity for us to connect those dots. And the CCO is helping us think through that go-to-market. For example, we also, from an energy perspective, in Q1, we launched a massive swath of energy content on the Cap IQ Pro desktop. And so these are ways to get the energy insights that we have to our financial end users where we see a lot of opportunity there as well.

And so we're very focused on the organic opportunities. Obviously, the integration of With Intelligence is top of mind, and I'm pretty excited by the pace at which the team has been able to move there. And I would say going forward, look, the lens and the criteria through which we might look at opportunities, tuck-in, et cetera, is -- I'd say the bar is raised because the premium -- I shouldn't use the word premium, but the value that we would ascribe to the uniqueness of IP is that's basically it, right? So it's got to be something that is unique, hard to get, not anywhere else for it to really qualify, I think, as we go forward. And that's where we're putting a very, very fine-tuned lens on everything that we might look at. But I would reiterate, like I always do, no transformational M&A, absolutely not. We're very confident in the business as it is.

Got it. Perfect. All right. We're just about out of time, so we'll leave it there. Thank you so much, Martina, and thank you, everybody.

Okay, thank you.

Appreciate it. Thank you.

Good morning, and welcome to S&P Global's First Quarter 2026 Earnings Conference Call. I'd like to inform you that this call is being recorded for broadcast. [Operator Instructions] To access the webcast and slides, go to investor.spglobal.com. [Operator Instructions] I would now like to introduce Mr. Mark Grant, Senior Vice President of Investor Relations and Treasurer for S&P Global. Sir, you may begin.

Good morning, and thank you for joining today's S&P Global First Quarter 2026 Earnings Call. Presenting on today's call are Martina Cheung, President and Chief Executive Officer; and Eric Aboaf, Chief Financial Officer.

We issued a press release with our results earlier today. In addition, we have posted a supplemental slide deck with additional information on our results and guidance. If you need a copy of the release and financial schedules or the supplemental deck, they can be downloaded at investor.spglobal.com. The matters discussed in today's conference call may contain forward-looking statements within the meaning of the Private Securities Litigation Reform Act of 1995, including projections, estimates and descriptions of future events. Any such statements are based on current expectations and current conditions and are subject to risks and uncertainties that may cause actual results to differ materially from results anticipated in these forward-looking statements.

Additional information concerning these risks and uncertainties can be found in our Forms 10-K and 10-Q filed with the U.S. Securities and Exchange Commission.

In today's earnings release and during the conference call, we are providing non-GAAP adjusted financial information. This information is provided to enable investors to make meaningful comparisons of the company's operating performance between periods and to view the company's business from the same perspective as management. The earnings release contains financial measures calculated in accordance with GAAP that corresponds to the non-GAAP measures we are providing and the press release and the supplemental deck contain reconciliations of such GAAP and non-GAAP measures. The financial metrics we'll be discussing today refer to non-GAAP adjusted metrics unless explicitly noted otherwise.

As noted in the press release and slide, financial guidance provided today assumes contributions from Mobility for the full year and excludes any impact from anticipated stranded costs. The company expects to update adjusted guidance to exclude Mobility and institute GAAP guidance upon completion of the spin.

I would also like to call your attention to certain European regulations. Any investor who has or expects to obtain ownership of 5% or more of S&P Global should contact Investor Relations to better understand the potential impact of this legislation on the investor and the company. At this time, I would like to turn the call over to Martina Cheung. Martina?

Thank you, Mark. We are pleased with the results that we achieved in the first quarter. Revenue increased 10% year-over-year or 9% on an organic constant currency basis. Revenue from our subscription products increased 6% year-over-year. We saw even stronger growth in our market-driven businesses this quarter with Ratings and Indices both showing remarkable resilience. On a trailing 12-month basis, we delivered 140 basis points of margin expansion, and increased adjusted diluted EPS by 14% year-over-year in the quarter. We demonstrated a continued commitment to disciplined capital allocation returning $1 billion to shareholders through share repurchases in addition to our cash dividends in the quarter. We delivered these results in an incredibly volatile and dynamic operating environment, making clear progress in each of the 3 pillars of the strategic vision we outlined at our Investor Day.

While we're pleased with the innovation, execution and results that we delivered in the first quarter, we acknowledge the macro uncertainty that has increased in recent months. Even if conflicts are resolved quickly from this point, we expect it to take some time for supply chains to return to normal. In recent months, the geopolitical and economic backdrop has shifted and become substantially more challenging for many of our customers. The conflict in Iran has shocked energy markets and supply chains. This has led to much higher energy and commodity prices while also elevating volatility. The longer the duration of this conflict, the broader and more severe the impact on global supply chains and markets across sectors.

This quarter, we also saw private credit navigate increased scrutiny, wider spreads and elevated redemptions. We expect strong growth in private markets over the medium term, but this growth will require increased transparency from data and benchmarks, which is an important area of focus for S&P Global. Throughout all of this, the pace of technology innovation has only accelerated. Clearly, the markets are reacting quite aggressively to new AI frontier model headlines, shifts in diplomatic initiatives and the unpredictability of the current environment. That manifests in volatility across the global markets. We've seen broad dispersion in the performance of different sectors of the equity markets, elevated volatility in equity and commodity markets and shifting expectations for central bank actions.

Despite the turmoil in the macro environment, issuance was resilient. Billed issuance increased 14% year-over-year in the first quarter, primarily driven by strength in investment grade. Investment grade benefited from hyperscaler investments in AI infrastructure. Notably, even without the hyperscaler issuance, investment grade delivered healthy growth in part benefiting from several large M&A transactions. Growth was partly offset by a high-teen decline in bank loan volumes as we lapped a very difficult compare in the first quarter of 2025. We saw spreads widen slightly in the quarter as a reaction to uncertainty around AI, private credit and geopolitical conflicts. Over spreads are still below historical norms.

While first quarter billed issuance was above our initial expectations, Much of the outperformance was driven by hyperscaler issuance that our original guidance assumed would be spread more throughout the year. Our full year expectations for the debt markets are largely unchanged. Everything we see reinforces our vision for the company, and our priority remains on executing our strategy. We are committed to our mission to advance essential intelligence by advancing our market leadership, expanding into high-growth adjacencies and amplifying enterprise capabilities and AI.

Customers are coming to S&P Global with increased urgency for our differentiated data and benchmarks. Insights and tools to make timely and informed decisions in this rapidly evolving operating end market environment. For instance, we saw record revenue and attendance at CERAWeek, the premier global conference addressing the intersection of energy, finance, technology and geopolitics. This year's conference hosted a record 11,000 attendees and more than 2,300 companies from over 90 countries. We are helping our clients make sense of and manage the spike in volatility. We posted record-setting revenue in Global Trading Services and Energy and record quarterly average daily volumes for the S&P 500 Indices.

We are also advancing our leadership as we help our customers unlock the potential of AI. As we discussed at our Investor Day, we are deploying AI native solutions and tools like ChatAI and Document Intelligence for those seeking speed and scale on our platform. For those who want to build their own AI-enabled or Agentic solutions, we are increasingly making our data accessible via standard protocols like MCP. We've seen meaningful enhancement to the value that our products are creating for customers. More than 1/3 of our CapIQ Pro users engage with the AI features we've launched, including ChatIQ and Document Intelligence. We also saw tremendous growth in the usage of S&P Global data in the quarter. In March, we shared that nearly 150 customers across the Market Intelligence and Energy divisions, were interacting with our data through AI applications like Claude and Copilot. We now have more than 300 customers under contract or in trial periods for Kensho-LLM-ready APIs.

In addition to the rapid growth in customers, we are seeing large increases in the volume of data that's consumed directly via API calls from customers and through these platforms. For instance, in the first quarter, the volume of API calls made by our customers was more than 5x the volume that we saw just 1 quarter ago. Volumes doubled month-over-month just from February to March. We can see early indications of this translating into economic benefits. ACV growth among customers who use our AI solutions is outpacing growth from other customers by a wide margin. Growth in Market Intelligence is 30% higher among AI customers compared to others and growth among AI customers and Energy is double the growth rate among other customers. Chief Client Office customers are also actively seeking the deep expertise of our in-house Kensho team. 25% of these clients are engaged with our Kensho Labs Technologies to explore opportunities to leverage our technology and data to help solve their most challenging problems.

All in, our approach to leveraging AI in S&P Global Products and S&P Global data in AI platforms is resonating with customers in a meaningful way. While it will take some time to see exactly how this manifests in our financial results, we are confident that the value we create for our customers is increasing and the economics will reflect that over time.

At our Investor Day, we provided a breakdown of the revenue that S&P Global generates based on different categories of our data, benchmarks and workflow tools. We noted that less than 5% of total revenue comes from undifferentiated data. Even within Market Intelligence, undifferentiated data contributes only 12% of revenue, but we wanted to share the full breakdown of the division here. Advisory, Consulting and Events constitute about 11% of Market Intelligence revenue and our workflow tools, which include a portion of Capital IQ and all of Enterprise Solutions constitute about 37%.

Our proprietary and curated data includes proprietary data based on our intellectual property as well as curated contributory and reference data. For our curated data, perhaps the biggest challenge in replicating some of these data sets like Compustat and SNL is the means by which we aggregated these data sets to begin with. Often, employees would have to physically scan and paper documents in local offices. While some of that data may be publicly available, many of these types of data sets are only available in digital formats from S&P Global. Importantly, Market Intelligence is also the distribution platform for our Ratings content through RatingsDirect on Capital IQ Pro and RatingsXpress. Contributory data sets include products and data like Visible Alpha and With Intelligence. We also have reference data in this bucket, which is based on intellectual property owned or co-owned by S&P Global like the Global Industry Classification Standard, or GICS, and LoanXID or LXIDs. We also generate unique proprietary data from our events, including our private market events. With Intelligence team collects insights through engagement with LPs that help GPs target more accurately based on fund, strategy, sector and regional capital commitments. This unique insight is available through our intentions and preferences data set.

One important point is that we have attributed the revenue from Capital IQ across 3 categories: benchmarks, workflow tools and undifferentiated data. While many of our customers would likely attribute less value to the undifferentiated data, we wanted to take a conservative approach to this analysis. That breakdown is important because it highlights the multifaceted value proposition for Capital IQ Pro. When we talk about Capital IQ Pro, many investors often focus on our core platform or desktop offering. However, CapIQ Pro's value to our customers extends far beyond the desktop to the data, business logic and tools that are housed within the platform. As I mentioned earlier, we are deploying AI native solutions and tools for those seeking speed and scale on CapIQ Pro, including ChatIQ and Chart Explainer. These features are already driving customer engagement, and we expect many of our customers will continue to consume our content and data primarily through an integrated desktop solution. Other customers will have an interest in interacting with our content in their own AI environments and in third-party productivity tools like Claude and ChatGPT. Much of our data is accessible via model context protocol or MCP, and other standard protocols to customers in these environments. Our branded custom business logic and calculation engines as well as many of the tools that exist in Cap IQ Pro will integrate with platforms like Copilot and Claude.

Our customers are on their own AI journeys, and adopting these new platforms in different ways, depending on urgency, comfort level and regulatory sensitivity. We will continue to invest in new ways to create value for our customers, including delivery through MCP and agent agent protocol, to ensure that customers can access our data and tools where they need it. And as usage increases and use cases expand, we expect to align the economics with the value we create through price.

In the first quarter, we saw a great deal of innovation, including new products, new features and new services for our customers. Within Market Intelligence, we continue to make progress in the private markets with our partnership with Cambridge Associates and Mercer. In our Energy division, we just wrapped up the best CERAweek we've ever had. We unveiled our new AI native Upstream product for data and insights called CERA Titan. As we've discussed with you previously, we are in the process of completely revamping the Upstream business within our Energy division. 70 customers were able to demo the new platform and feedback was overwhelmingly positive. We immediately saw an increase in leads and sales pipeline for Upstream Data & Insights. And one large strategic customer was so pleased with the new platform that we were able to close a large renewal with a meaningful increase in contract value.

In addition to improving our Data & Insights solutions, we also announced in a separate press release that we have signed an agreement to divest the software portfolio in our Upstream business, and we expect that to close in the second half of 2026 or early 2027. This allows us to more tightly focus our efforts on the proprietary Data & Insights within Upstream, and we believe this will allow us to make faster progress towards returning Upstream to sustained positive growth.

We continue to innovate within S&P Dow Jones Indices with the launch of iBoxx U.S. Treasuries Index, as the first major index available as a native digital asset on a blockchain. We also launched an additional tokenized S&P 500 Index on blockchain in partnership with Centrifuge, and we launched S&P Link in U.S. and Europe senior debt indices. We continue to focus on decentralized finance and fixed income as strategic initiatives and are excited about the slate of new products coming to In Ratings, we raised the first esoteric ABS issuance backed by Bitcoin as we continue the innovation leadership in digital asset finance that we started in 2018.

As we continue to execute our strategy, we are pleased with the results we're delivering for our shareholders with strong revenue growth and margin expansion in every division. With that, I'll hand it over to Eric to walk through the quarter's financial results and the guidance.

Thank you, Martina, and good morning, everyone. Starting with Slide 16. We delivered strong first quarter financial results with 10% reported revenue growth, 9% organic constant currency revenue growth and 14% growth in adjusted diluted EPS. This performance underscores the durability and resilience of our business even amid a period of elevated geopolitical and economic disruption. Reported revenue growth of 10% includes the acquisition of With Intelligence, which closed in the fourth quarter, offset by the divestitures of EDM and thinkFolio in January as well as modest tailwind from FX. Adjusted expenses increased 8%.

As Martina mentioned, we began to see volatility in macro risk increase in late February and continue through March. We reacted quickly to make sure we were measuring expenses effectively allowing for better first quarter margins in every division than we had anticipated when we gave initial guidance. Strong growth and disciplined expense management combined to deliver 100 basis points of year-on-year margin expansion to 51.8% and 12% growth in adjusted operating profit. Excluding OSTTRA from the prior year period, our first quarter 2026 margin expansion would have been 160 basis points.

Turning to our divisions on Slide 17. Market Intelligence revenue grew 8% and organic constant currency revenue grew 6% in the first quarter. Subscription revenue increased a solid 6%, both on a reported and organic basis, driven by strong renewals and net sales across the franchise. Subscription growth included a 50 basis point headwind from the timing of revenue recognition that we expect to reverse in the back half of the year. Onetime revenue and volume-driven revenue grew 18% in aggregate in the quarter. This was partly driven by the acquisition of With Intelligence and partly by the rebound of volume-driven activity. Data Analytics & Insights reported revenue increased by 11%, driven by our first full quarter of revenue from the With Intelligence acquisition worth 6 percentage points as well as solid 5% organic growth driven by market data and valuations, Cap IQ Pro and Visible Alpha. Enterprise Solutions reported revenue grew 3%, reflecting the divestiture of EDM and thinkFolio in mid-January. The business has delivered very strong organic growth of 14%, with double-digit growth across all major product lines.

We've also included an additional slide in our supplemental deck to provide a breakdown of the workflow tools in our Enterprise Solutions segment, most of which benefit heavily from S&P Global data and strong external networks. Credit and Risk Solutions revenue grew 6%, driven by strong subscription sales of RatingsXpress and RatingsDirect. Market Intelligence's adjusted expenses increased 7% year-over-year driven by a full quarter of expenses from the With Intelligence acquisition as well as an unfavorable FX impact, higher compensation expense and long-term strategic investments, partially offset by the impact from the recent divestitures, including the sale of EDM and thinkFolio. Market Intelligence delivered 80 basis points of operating margin expansion to 33.6% in the quarter.

Now turning to Ratings on Slide 18. Ratings revenue increased 13% year-over-year, exceeding our internal expectations for the quarter. Growth was strong across both transactional and non-transactional revenue streams. Transactional revenue increased 15%, driven by strength in investment grade, supported by a number of large hyperscaler or M&A transactions in the first quarter. Transaction revenue from governance, high-yield and structured finance also grew in the quarter but was more than offset by the weakness in bank loans due to a high teens decline in billed issuance. Private markets revenues were up over 25%.

Non-transactional revenue grew 11%, driven primarily by higher annual fee revenue. We were also pleased by our growth in issuer credit ratings or ICRs, and Rating Evaluation Services or RES in the quarter. adjusted expenses rose 8%, reflecting higher compensation costs and continued strategic investments in our people, technology and product development. This contributed to the division's 160 basis points of margin expansion to 67.8%.

Now turning to S&P Global Energy on Slide 19. The conflict in Iran has brought considerable volatility and uncertainty to the Energy markets that has persisted into the second quarter. Some of the Energy customers in the Middle East have experienced a direct impact to their facilities and many are facing supply chain and/or distribution disruptions. Even in this environment, Energy revenue grew 7% this quarter as we benefited from very strong events revenue, and we saw a spike in value-driven transactional activity. At the same time, the conflict weighed on other parts of our Energy division, including our subscription revenue. Sanctions continue to be a headwind as well as we've called out in recent quarters, but the conflict in the Middle East is pressuring clients and could lead to slower growth in the coming quarters.

As Martina noted earlier, amid this uncertainty, our customers are turning to S&P Global for Data & Insights only we can provide. CERAWeek in Houston hit new records and online, the number of user queries in our Energy platforms, ChatAI feature more than doubled quarter-over-quarter. Energy & Resources, Data & Insights and Price Assessments grew 7% and 6%, respectively, driven by strength in petroleum gas, power and renewables. The sanctions we discussed last year drove a 100 basis point headwind to Energy & Resources and 140 basis points headwind to Price Assessments.

Advisory & Transactional Services revenue increased 15%, driven by strong growth in conference and training revenue as CERAweek delivered record-setting attendance and revenue. We also posted close to 30% growth in Global Trading Services or GTS amid elevated energy market volatility.

Upstream Data and Insights revenue declined 5% in the quarter. driven by the absence of a prior year onetime fee. We continue to streamline this business line and refocus on the areas of proprietary Data & Insights, as Martina mentioned. Our transformation is on track, including the realignment of the sales teams and the debut of our upgraded client platform at CERAWeek, which already has sparked strong customer interest. We're pleased with the team's progress, but given heightened Energy market volatility and uncertainty, we still think it could take several quarters before these management actions drive growth in Upstream.

Adjusted expenses grew 4%. Our teams in Energy did a particularly good job moving quickly to keep expense growth low to preserve margins during a volatile period. The expense growth we did see was driven by higher compensation costs and unfavorable FX impact as well as ongoing investments in growth initiatives. First quarter margin expanded by 120 basis points to 49.3%.

Now turning to S&P Dow Jones Indices on Slide 20. Revenue grew by 17% with double-digit growth across all business lines. Revenue associated with asset-linked fees grew 18% in the first quarter. This was driven by year-over-year equity market appreciation and net inflows into products based on S&P Dow Jones Indices. As we've noted before, in periods of heightened volatility, we often see slower flows and higher priced indices like sector, factor and thematics and higher flows in lower price indices like the S&P 500. That was the case in the first quarter as well, and that mix shift drove a modest decline in average realized price year-over-year in our asset-linked fees business.

Exchange-Traded Derivatives revenue was up 18%, driven by strong volumes, particularly in SPX, which continues to demonstrate the natural hedge we have in this business during times of geopolitical and macroeconomic disruptions. Data and custom subscriptions continued to benefit from our focused commercial efforts over the last several quarters posting its third consecutive quarter of double-digit growth. Revenue increased 12%, largely driven by new business growth and end-of-day contracts. Adjusted expenses were up 13% year-over-year, driven by higher compensation costs and investments in growth initiatives. Indices operating profit grew 18% and and operating margin expanded 90 basis points to 73.8%.

Now turning to Mobility on Slide 21. Revenue grew 8% in the first quarter, underscoring the mission-critical nature of the division's products with high single-digit growth in both dealer and financials and other and a modest tailwind from FX. Customers continue to rely on CARFAX's unique data and solutions, driving strong subscription growth despite a complicated environment for automotive OEMs. Dealer revenue increased 9%, benefiting from momentum in new customer growth at CARFAX and automotiveMastermind. Manufacturing revenue grew 5%, driven by subscription growth and increased discretionary spending. Growth was partially offset by softness in recalls and OEM marketing related products. Financials & Other grew 8% as the business line continues to benefit from underwriting volumes and commercial momentum. Adjusted expenses grew 5%, driven by advertising and promotional investments. Mobility's operating margin expanded 150 basis points year-over-year to 40%.

Looking forward, we remain on track for our planned separation of the Mobility business, including completion of the spin mid-2026. We will file our Form 10 publicly this quarter, and the Mobility Global team is excited to be hosting their Investor Day in New York City on May 12, ahead of the launch of its equity roadshow. We also plan to launch a public debt offering for Mobility at some point this quarter, targeting an investment-grade rating. As a reminder, from a financial reporting and guidance perspective, S&P Global will continue to fully consolidate Mobility Global in our financial statements and 2026 guidance until the separation is complete. Upon completion of the spin, we intend to provide recast financials for the 4 quarters of 2025 and any 2026 periods reported adjusted to exclude Mobility's contributions along with other relevant adjustments as outlined at our Investor Day. We also expect to issue updated 2026 guidance at that time, excluding Mobility.

Now shifting to our outlook, starting with Slide 22. I'd like to review the key macroeconomic assumptions that underpin our guidance, which takes into account the current geopolitical environment. The conflict in Iran has led to the largest energy shock since the 1970s and counterbalance what was previously a broadly favorable economic environment for business. Our current outlook assumes the situation stabilizes by the end of the second quarter, but we acknowledge the risk of a protracted conflict. We assume 3.2% global GDP growth, including 2.2% growth in the U.S. We also assumed 3.2% CPI growth in the U.S. We expect near-term energy client demand to remain suppressed given our expectation for ongoing market uncertainty. Should the conflict persist longer or escalate, we could see more significant direct headwinds, particularly in our Energy business and significant indirect headwinds in our market-sensitive businesses depending on equity market reaction and credit market conditions.

We continue to see favorable market conditions for issuance in 2026 even though we now only expect 1 rate cut in the U.S. We also entered the year with encouraging maturity walls as we discussed on our fourth quarter call, and we are encouraged by the growth of announced M&A. As Martina mentioned, some of the strength in issuance in the first quarter was driven by front-end loading of hyperscaler issuance relative to our initial expectations. Given both the outperformance in the first quarter and the more modest expectations for Q2, we do not expect to see acceleration in Ratings revenue growth in the second quarter. We continue to expect Ratings growth to moderate in the third quarter before turning negative in the fourth quarter as we lap prior year highs.

This leads us to our updated guidance for the Enterprise on Slide 23. At the consolidated level, we are reiterating our guidance for organic constant currency revenue growth in the range of 6% to 8%. We're also reiterating our guidance for 50 to 75 basis points of margin expansion in 2026 excluding the impact of OSTTRA. Our adjusted EPS guidance is also unchanged at slightly higher expected interest expenses offset by lower share count due to the additional repurchases we now expect.

As you can see on Slide 24, our division guidance is also unchanged with the exception of our Energy division. Given the external environment, particularly the impact of the Iran conflict and the energy disruption on both the demand and supply side, we currently expect to deliver organic constant currency revenue growth in the range of 4.5% to 6%, 1 percentage point lower than the previous guidance. Importantly, our guidance assumes that the current elevated level of disruption in the energy market persists through the second quarter. The supply chain disruptions would not fully be resolved until later this year.

For our Indices business, our full year guidance is unchanged. However, the underlying assumptions have been adjusted to reflect the current market dynamic. Our guidance now assumes equity markets roughly flat from current levels and low double-digit growth year-over-year in ETD volumes.

We also wanted to provide some directional color for the second quarter. In Market Intelligence, we expect some acceleration in subscription revenue, given what we're seeing in customer traction and sales pipeline. We expect that to be offset somewhat as growth in nonsubscription revenue normalizes. In Ratings, we will be lapping the disruption caused after Liberation Day last year, which creates a favorable compare. We expect growth to remain strong, but we do not expect acceleration in 2Q. We do expect investment grade to continue to represent a higher mix of issuance compared to historical averages, particularly if we continue to see elevated hyperscale CapEx driving large volumes in the second quarter.

For Energy, the macro disruption has a concentrated impact in the second quarter, and we have already seen that impacting our near-term sales pipeline. We expect revenue growth in the second quarter to fall slightly below the guidance range for the full year before reaccelerating in the second half. We will be monitoring the sales motion, customer health and macro environment closely and managing expenses throughout the year to ensure we are preserving margin. For Indices, we expect continued robust growth in the second quarter before growth decelerates in the second half given the tougher compares in 3Q and 4Q.

For Mobility, we expect growth to accelerate slightly from the first quarter levels with stronger growth expected in the second half. On second quarter margins, we expect margin expansion to be above the enterprise full year range for Ratings and Indices, slightly below the range for Mobility and Energy and within the range for Market Intelligence. This is largely due to the timing and quarterly phasing of expense recognition as we were very disciplined in our approach in the first quarter. Our full year expectations in each of these divisions are unchanged.

Lastly, we want to provide an update on our capital plans for the rest of the year. As you know, we have a target gross leverage range of 2 to 2.5x trailing 12-month EBITDA. Given the expected loss of Mobility EBITDA, our current leverage of 2.3x will naturally increase to 2.4x at the end of the year. However, we expect to issue approximately $2 billion in debt at Mobility in conjunction with the spin. Proceeds are expected to fund a cash payment to S&P Global, which we would expect to use for a combination of incremental share repurchases and some debt reduction.

Given the strength and resilience of our business and our confidence in its long-term profitable growth, we believe the current share price reflects an attractive opportunity to increase our repurchases from the expected 85% of adjusted free cash flow to at least 100% or to roughly $4.5 billion for the year. With that, let me turn the call back over to Mark for your questions.

Thank you, Eric. [Operator Instructions] Operator, we'll now take the first question.

Our first question comes from Toni Kaplan with Morgan Stanley.

Martina, thanks for the color on what you're doing with regard to the AI distribution channels. I was hoping that you could expand on how you're thinking about the partnership strategy with the large AI players? Are you building SMP, MCP apps on the platforms? Or you just plan to continue to provide the data through the MCP integrations and the APIs? And maybe if you could just talk about the monetization model and directional economics between the different distribution channels.

Toni, thanks for the question. And the quick answer to the first part of that around MCP applications is, yes, that is our intention. I think we're going to be very thoughtful around how we build those applications and for what, particularly. This is one of the reasons why we wanted to highlight the value that exists in the workflows in Cap IQ Pro today, for example, it's not just the data. It is the standards, the business logic as well as the tools and all 3 of those will be part of that strategy. The first step to doing that has actually been the announcement of the S&P Global plug-in, which was announced in line with the Claude for Financial Services announcement in the first quarter. And that's essentially a series of agents that teach AI agents within the platform, how to actually conduct specific tasks for data, AI-ready data that the client might be licensed to. So maybe to give you an example, one of our buy-side clients working with Kensho was looking at our financial data via at AI-ready API and Kensho helped them to understand how to use the plug-in to perform tasks like creating tearsheets or creating earnings calls previews. And as a result, the clients liked it so much that they actually canceled their existing provider and went with our data and plug-in even though it was about 20% more expensive. Now look, it's early days. Obviously, we just launched that in Q1, but I think it's an interesting signal for how clients are testing the value of our IP, whether it's our logic, our standards as well as our data in the context of these providers.

Now the point I would make on monetization is that we are really thinking about monetization through the lens of enterprise value. So as you know, we don't do seat-based licensing. We don't do usage only. We track usage, channels, the value we create and a number of other metrics as part of the discussions that we have with our clients on value and price accordingly. And that's going to be true for plug-in. It's going to be true for MCP. It's going to be true for AI-ready data as well. And we're seeing clients who are quite interested in the value that we bring through all of that. Perhaps maybe one other example I would provide is in the quarter two financial clients who are just subscribing to our data at renewal, were opting to get that data available in an AI-ready format. And were willing to pay in the range of 35% to 45% on the renewal increase to get the AI access. So again, early days, but some very strong signal here around the monetization from an enterprise value standpoint. Thanks for the question.

Our next question comes from Faiza Alwy with Deutsche Bank.

Martina, I wanted to follow up on the same topic. On Slide 11, where you talk about Market Intelligence data differentiation. I'm curious how would you -- when we look at workflow solutions, how would you attribute sort of the value of the proprietary data versus sort of the software component of the workflow tools here.

Thanks for the question. So with regards to workflow, you'll see a lot of these products embedded in our Enterprise Solutions business. And there, we operate many mission-critical software and workflows for our customers. These would be workflows that are scaled, require robust controls, risk management, and compliance layers and really require a lot of intervention through our managed services to make sure that they're continuing to deliver. And so there's very much a mission-critical nature to many of these. There are several of them that actually function as networks for industry groups, not just for an individual client. And so there, we would see perhaps the Wall Street office, for example, or ClearPar in that category, and again, serving not just a client, but the benefit of it being derived because it is actually informing a whole ecosystem. And in many cases, the value that our clients get from these tools is a function of some of the proprietary content that we embed in the tools. A good example there would be the loan reference data that is provided through Wall Street Office. And so we think of it more as the value that we are bringing to the clients through the workflow tools and the importance and criticality of those systems to clients very, very critical processes. And that's one of the reasons why we continue to see good growth in these tools across Enterprise Solutions as well. Thanks for the question.

Our next question comes from Ashish Sabadra with RBC Capital Markets.

In regards to MI, the subscription growth is expected to accelerate in 2Q. I was just wondering if you could unpack that some more what's driving it? How much of it is driven by AI products, key client office or any other color that you've been providing? .

Ashish, it's Eric. We've seen very good performance in the first quarter as we've started the year in MI. And we just expect that to continue to build. Subscription revenue growth was in the 6% range. We feel good that, that will continue to build. But we had very good performance that augurs well for the coming couple of quarters. Net renewal rates are up 100 basis points or so. Pipeline has been building January to February to March. Our average deal size is up, our net sales are up. So we see good underlying indicators across that franchise in a number of ways. And we think that will just build during the course of 2Q, 3Q and 4Q and deliver the full year guidance that we expect in a nice way. Thank you for the question.

Our next question comes from Scott Wurtzel with Wolfe Research.

On the Market Intelligence margin, just wondering if you can maybe help contextualize how much of the margin expansion that you're seeing is being driven by efficiency gains associated with AI.

Scott, it's Eric. Margin expansion has come in nicely in MI in particular, in first quarter. We were careful with the external environment. Starting late February, we -- the Iran conflict started. We're careful about our discretionary spending. And so you saw particularly strong performance in MI as well as our other 4 divisions as we just carefully thought about pacing expenses through the year. More broadly, if you think about margin expansion in MI and other divisions, it's really a combination of factors. There's certainly a set of AI benefits that we're getting as we think about our data operations, which is a big part of MI. We see emerging progress or I think I'd say good progress in software development activities that are AI-driven with all the new tools available to it. And then we see the continued kind of classic productivity tools being effectuated in MI as the team there is really driving a combination of top line and bottom line. So we're feeling comfortable about the margin expansion for the full year. We feel like we got off to a good start. And we just see with AI, a set of tools that become stronger and stronger and more and more valuable to us as we continue to deliver margin and earnings growth quarter after quarter.

Our next question comes from Curtis Nagle with Bank of America. .

Just a really quick one for me. Just if we go through, I guess, how to think about the balance of transaction, non-transaction growth within the Ratings business for the rest of the year? And I guess just for the first quarter, what drove a pretty notable spike in the non-transaction numbers. You have to get answer that.

Curtis, maybe I'll start on nontransaction. We had good growth in annual fees as the franchise continues to to be viewed very favorably by our clients around the world. And then our CRISIL revenues, which are booked there, which have a mix of different factors, performed very, very well in the first quarter, which we were pleased with. So a couple of good tailwinds, and we expect some of that to to generally moderate in the coming quarters, but we think it will help contribute to our full year revenue guide.

And Curtis, I would maybe just add that we -- you may recall when we gave our guidance back in February that we mentioned we had prudent and moderate expectations for hyperscaler issuance within the year. And a good part of that was that we didn't assume that all of the announced CapEx was going to be debt financed. And as we looked at the amount of hyperscale issuance in Q1, we believe that there was some pull forward there relative to our expectations for hyperscale issuance. And this is one of the reasons why we are continuing to maintain our expectations for billed issuance for the full year. Thanks for the question.

Our next question comes from Manav Patnaik with Barclays.

I was hoping just going back to the workflow conversation, you could help us just appreciate the strategy in Energy where you're selling the workflow businesses and focusing in data, like how would those workflow brands different than the ones you were talking about in MI? And as a quick follow-up, just I think there were like 7 or 8 different brands, I think you're selling in Energy. I was just hoping you could help us size that for our models? Like how much are you getting selling to SLB.

Manav, thanks for the question. Maybe to start, the size of that is about 25% of Upstream revenues. And that software portfolio, as you mentioned, is actually quite varied and quite distinct. And so one of the reasons that really informed our decision there is that we think SLB is a very good partner on that. And as part of that decision to divest, we also have a new distribution partnership with SLB that we are quite excited about as we close that. And so what I would focus on maybe is the 75%, which is highly differentiated and unique proprietary content. Maybe just to give you a sense for what is here we cover from basin to reservoir subsurface and geoscience data, including seismic surveys as well as in logs and spatial data. Some of the stuff that is particularly useful for our clients is Vantage asset valuation data that covers over 17,000 global upstream and gas assets. And we also have very, very unique benchmarking performance content that is based on contributory data and it allows operators to actually do peer-to-peer performance data, and is highly valued. This data actually goes back over 30 years, covering about 80,000 wells globally. There's a lot more to that. And one of the things that we're super excited about is actually creating Titan that we talked about in the prepared remarks that sits on top of all of that data and provides the workflow for our clients to really interact with that data more seamlessly. This is something that our clients have been asking us for, for many years. And the overwhelmingly positive feedback that we got when we use CERAWeek for that soft launch was just really very encouraging. And we were able to close one client already just on the demo of the new tool because those clients are very, very aware that our data is the highest quality and most unique out there. And so Upstream more broadly, I would say, we look to our broader revenue transformation there. We look to the full hard launch of Titan later this year. and are very excited about the progress that we're making there as well. Thanks for the question.

Our next question comes from Alex Kramm with UBS.

Just I think -- I don't know if I missed this, but one of the things you changed in your guidance was also the I guess, acquisition and divestiture contribution on Market Intelligence. It's a small change, but just wondering if I missed it, what changed there? And maybe related to that, With Intelligence, now that you've owned the business for a little over a full quarter. Just wondering what kind of underlying growth rates you're seeing and any on how that asset is performing?

Alex, it's Eric. Let me just summarize. As you noticed, the organic versus reported revenue contribution really has 5 deals, 3 of which are quite large, both divestitures and acquisitions. You've got EDM and thinkFolio being sold, you got With Intelligence coming in and 2 other small ones. And so what we just did was updated the contribution from the net effect of those 5. It's primarily driven by a modest change in revenue recognition. But as we step back, we're quite pleased in particular With Intelligence. As we said in our last call, we closed that early and even more quickly than we had thought. The team has really been digging in deeply and beginning to focus on all the synergies, both expenses and revenue in particular. And as we've said when we announced the deal, we expect high teens revenue growth in With Intelligence with some upside as we go 1 year to the next just because there are so many opportunities to redistribute that content across our franchise and really leverage the depth of the proprietary and the contributory data that Martina referenced earlier. Thanks for the question.

Our next question comes from Owen Lau with Clear Street.

So following up on the AI Upstream data platform Titan, it's still in beta testing version. But could you please talk about your go-to-market strategy and the revenue model of this product? Is it going to be a subscription-based model or consumption-based or a combination of the two?

Owen, it's Martina. Thanks so much for the question. It's going to be a subscription-based model. And in terms of the broader go-to-market strategy, I think the team was able to really effectively leverage CERAWeek because we have so many clients in town to be able to do our launch and get this into the minds of so many of our customers. And so we're excited about this. And the official hard launch for the product is going to be a little bit later this year. And as I mentioned, just to say again, the experience there is very comprehensive, bringing together so many of these unique data sets that we have, and it's powerful enough that one of our clients renewed with a very large uptick just on seeing the demo.

Our next question comes from Jeff Silber with BMO Capital Markets.

You highlighted the wars impact on the energy sector. I'm just curious, hopefully, this war is going to end soon. What do you think the impact would be on the other businesses? When should we start to see a rebound there?

Jeff, it's Eric. The impacts on the energy business, as we described, are quite direct, right, because customers are affected that slows down decision-making. And obviously, we need to help customers focus on their core business. In the other divisions, it's really a question about how expectations around the conflict evolve, what sort of macroeconomic and, I'll say, economic disruption we see globally and also region by region because that's going to affect equity price levels, which have an impact on our asset under our asset-linked fees. It's going to affect potentially credit markets and the flow of issuances in different market segments. So I think the indirect effects for the time being has been relatively small. The question is, does the conflict resolve itself in the coming months? Or does it drag on? Because the longer drags, it create more uncertainty and a wider range of outcomes. So in general, there's a range of factors. We're trying to be careful and prudent. You saw some of that in our patterning of our expense spend that we feathered in carefully in the first quarter to create some additional margin expansion. And we're just being vigilant about the effects and staying close with our clients and making sure we support them across our various divisions.

Our next question comes from Andrew Steinerman with JPMorgan.

Eric, it's Andrew. What was the organic ACV growth in the first quarter for MI? And then also remind us on the Ratings side, if S&P includes bank loan repricing transaction and billed issuance or not and how it impacted first quarter.

Andrew, it's Eric. Thanks for the question. On MI, we saw good ACV growth in the first quarter. It was right around the level of subscription growth, which we showed at 6%. And I think in line with the last couple of quarters. And then in terms of repricing for bank loans, that's not included in that line.

Our next question comes from George Tong with Goldman Sachs.

Can you talk a little bit more about the latest trends you're seeing in the private credit markets and how much S&P Ratings revenue you expect to come from private credit?

George, it's Martina. Thanks for the question. Well, this is an area that we've seen very strong growth in over several years now. And in fact, we ended full year 2025 at the enterprise level was north of $600 million in revenues in private markets. As I mentioned in my own prepared remarks, Ratings Private Credit grew 25% off a decently substantial base. Remember, we've been investing in this area for several years, and we made sure that we have the analytical capacity expertise and the appropriate methodologies here. So it's an area that we are, I would say, cautiously optimistic about over the very immediate time frame just given some of the stresses on the sector that we mentioned. But we started this year with those potential stresses in mind. We didn't necessarily assume there was going to be huge growth in middle market CLOs, for example, we assumed that there would be some softness in BDCs. And so far, we're seeing the trends play out as expected. And then, of course, if you take a step back and you look at what we're doing in the broader Market Intelligence and Index strategies around private markets, all of what we're doing is geared towards giving LPs and GPs performance data and benchmarks and data and analytics to assess how these investments are trending as well as how LPs are thinking about shifting allocations, et cetera. And we are seeing a lot of demand for that data. Maybe just to give you two additional examples. During the quarter, we launched one of the first -- we launched the first tranche of the data from our Cambridge Associates and Mercer partnership focused on private credit and infrastructure. And there's a lot of interest in that data because of its contributory nature. And we also integrated With Intelligence, the first tranche of With Intelligence documents into Cap IQ Pro, which again has stimulated quite a bit of interest because it enables GPs to really look at and target LPs based on their allocation strategies. So overall, I think, look, at this point, whether it's our Ratings, our performance data at the fund level, deal level, et cetera, and the analytics, there is a really big need and a lot of interest in what we're providing here. Thanks for the question.

Our next question comes from Craig Huber with Huber Research Partners.

I wanted to ask about AI efficiencies at your company. To the extent that you can give us some more examples of how AI internally is helping you guys be more efficient across your various sectors, including outside of the MI division? And also, Eric, I wanted to ask your 50 to 75 basis points expected improvement, excluding OSTTRA, how much ballpark do you think AI efficiencies is actually helping that number?

Craig, thanks for the question. Let me start, and then I'll hand over to Eric. I would say that we have been tackling AI by looking at some of our largest strategic processes across the company. And so at our IR Day, for example, we mentioned four particular areas that we were focused on, including our Ratings analytic workflows, our research workflows in Energy and in Market Intelligence as well as our technology and data workflows. And these comprise roughly around half of the resources that we have at the company. And so if you want to think about areas outside of maybe some of the more obvious areas like the data organization, we can see tremendous capacity expansion within Ratings, for example, where they have been a very early adopter of AI as part of augmenting analytical capacity and making sure that our analysts can do more high-value things like thought leadership and additional research. And so we're really leaning into this. We have announced you will see the joining of Firdaus Bhathena as our Chief Technology and Transformation Officer. And Firdaus really as part of that is looking at how we will scale AI and other technologies like quantum and blockchain so that we can actually get the full benefit around the Enterprise. And he will also look at this transformation program that has started with these four strategic processes and make sure we're scaling it out to the rest of the organization over time. Eric, I'll hand over to you.

Craig, I'd just add, AI is just beginning to have some positive impact on margin. I'd say beginning because, remember, AI is just a continuation of machine learning tools and a wide range of capabilities that we've used and leveraged across our processes. I've talked at length about the enterprise data office and what we do in data operations. And so I'll say the predicate to the the new LLM tools have aided the margin expansion over the last year, some into this year. But I think the upside from the broad adoption of Frontier models is just beginning. And really will have an impact in '27, '28 and in the future years as they get expanded into a wide range of these strategic and important processes that we operate and will be helpful in that regard. Thanks for the question.

Our next question comes from David Motemaden with Evercore.

Just a quick one on how clients are accessing your content maybe a little bit to Slide 12. You talked about usage through your own solutions like ChatIQ and then also through the Frontier large language models. Are you seeing any meaningful differences in usage patterns or engagement with your data across those two broad channels today? And I guess I'm wondering, as adoption scales, where do you see the balance between direct delivery through your own solutions and third-party large language models ultimately settling out?

David, it's Martina. Let me start, and then I'll hand over to Eric as well. This is something, obviously, that we're spending quite a bit of time thinking about. And I would start with our customers and what they're telling us and basically the types of deals that we are signing with our customers. So if we start from that perspective, there's a spectrum, if you like, along the very large number of users of our products in this area in Capital IQ Pro. It ranges from customers who will persist in using the integrated desktop over a period of time. And this is for a variety of reasons. It can be because they prefer to have us do the hard work for them in terms of integrating the AI capabilities and it can also be because they may look over time at the cost of adopting some of these models and prefer to have us manage that for them at scale, which can provide efficiencies rather than having them do that bespoke work themselves. We will also have clients who will do both. And so we see that already. We have one large global bank that signed an extended contract with us in the first quarter. It included expanding the usage of the Desktop Capital IQ Pro to additional users around the organization. And it also included increasing licensing for AI use of several of our data sets. And the bank actually made our data sets the standard on their own internal LLM, and so this is an example of where Capital IQ Pro will continue to be used alongside LLM model consumption within our clients. And I would say that, that is the majority of the conversations that we are having.

Now will clients look to just use their in-house LLMs? That's potentially a scenario that we could see play out over a period of time. We're ready for that. And in that case, we think our data becomes even more valuable because our data is required to really get the full benefit of using these channels. As I mentioned earlier, we will use the plug-in option, and we will also use MCP applications to make sure that we can continue to improve the user experience for clients that want to use these third parties. And all of this really is very consistent with how we have thought about partnering with third-party channels for many years now, and it's why we talked a lot about flexible distribution back in our IR Day. Maybe Eric, do you want to talk a little bit about how we're seeing the usage evolves?

Yes. Let me just give you some examples. On the direct usage side, right, where clients are using our platforms and within our platforms, usage continues to build very substantially. I described in our Energy core platform, AI queries are up 2x in iLEVEL, the automated data ingestion through AI is up 2x. And so seeing very significant increases, which we're monitoring in our minds, that's the way clients are gaining value. At the same time, in the -- through the LM channels, the frontier models, the models that our clients have. As we said earlier, call volume is up very significantly, literally 2x from February to March, 5x from December to March. And so again, we're seeing the value that clients are seeking in our data and proprietary offerings that they're looking for. And then what we find is where there's more usage, there's more value over time, that will create economic benefits and opportunities for us. In the clients that have been using our AI tools and availing themselves of those in MI, we're seeing a couple of hundred basis points higher retention rates. In Energy, over 500 basis points of higher retention rates because, again, usage is value for clients. They get more benefits, and that helps us drive the overall economics of each of our businesses across the range of channels that we provide.

Our next question comes from Jason Haas with Wells Fargo.

Can you just clarify on the ACV growth? I think you said that it was 6% in the quarter. I believe the past couple of quarters is 6.5% to 7%. So did it decelerate? And if so, what drove that? Because the commentary on revenue side optimistic for the rest of the year. So I just wanted to follow up on the ACV point.

Jason, it's Eric. I said the ACV growth was in line with subscription revenue growth, which was around 6%. I think we've quoted over the last 5 quarters, 6% to 6.5%, 6.5% to upper 6s percent. So it's in the range. There's always going to be a little bit of volatility. But what we see is that the underlying drivers are moving in the right direction. We're feeling good about net sales, net renewals and so forth across MI. And so we see this as a good outcome for the first quarter and expect that to build momentum into 2Q, 3Q and 4Q.

Our next question comes from Shlomo Rosenbaum with Stifel.

I just want to get a better sense as to how you are thinking about the Ratings revenue through the year? I know you gave the cadence, but in aggregate, from the change in the geopolitical environment, like is there an aggregate any change over -- in the way that you're thinking about Ratings revenue for the year? Or is there would you say there's more risk to what you're -- what you've been assessing. And then also, if you don't mind just quantifying the Ratings evaluation services, what was the growth you said it was healthy. I think you quantified it somewhat before in other quarters in. Has that changed at all in terms of the growth rate of that business, it's usually a precursor to additional issuance?

It's Martina. I'll take the question here. I think the -- ultimately, as you know, obviously, we didn't change our guidance for the full year for billed issuance and for Ratings. And I think the -- look, the thing that we're watching is this kind of end-of-2Q resolution, right? So we haven't necessarily seen any direct impact on Ratings revenue. But if we were to see GDP growth coming down, much broader sector shocks around the world, that's a scenario where we could see some weakness in the environment. And I think maybe to your question on RES, we had a good quarter in RES. A lot of that was driven by M&A assessments from issuers, but strong performance there overall. Thanks for the question.

We will now take our final question with Jeff Meuler from Baird.

Just looking out past the Iranian conflict thinking about your Energy business, how do you expect it to be impacted by the energy complex build-out associated with the data center and AI infrastructure build-out. Just any specific products that you'd expect to benefit any new customer type opportunities. That's it.

Jeff, thanks so much for the question. I think this goes back to 1 of the things that we really highlighted at our Investor Day around Energy expansion. There's a tremendous amount of additional growth that will be projected in demand for energy as well as demand for critical minerals. And our data is really quite unique across these various different areas and gives us a true opportunity to work with clients around the world to help them understand forecasts for renewables, forecast for hydrocarbons, the trade-offs between both as demand increases, et cetera. And so we're seeing great opportunities, not just in the -- some of the ones that we've been talking about within Ratings, for example, on data center issuances, but we also saw increased issuances from utilities. In the power sector in Ratings. We see demand for additional scenario planning around power and utilities in the Energy team, and we've seen particular demand in the Energy team's unique insights and data on critical minerals. And so these are all areas where we would expect to see additional demand over time. Thanks for that question.

And in closing, I'd like to thank our people for delivering such a strong quarter. Our mission of advancing essential intelligence is now more relevant than ever as we help our clients navigate the uncertainties in this environment. And we're making really great progress against our strategy and are exceptionally well positioned and excited about our opportunity to drive value this year and beyond. We really appreciate you joining the call today. Thank you.

That concludes this morning's call. A PDF version of the presenter slides is available for downloading from investor.spglobal.com. The replays of the entire call will be available in about 2 hours. The webcast with audio and slides will be maintained on S&P Global's website for 1 year. The audio-only telephone replay will be maintained for 1 month. On behalf of S&P Global, we thank you for participating and wish you a good day.

Capital IQ Pro is being reinvented through the addition of new content, expanded analytical capabilities and modern GenAI access points.

Welcome to Capital IQ: Reinvented in New York City.

Today, we're excited to share some of those recent innovations with you. Let me now preview some of what you'll see today. We'll start with our deep sector data, which has long been a hallmark for Capital IQ Pro through our SNL content. Rodney Pedersen, who leads our Visible Alpha business, will demonstrate how we aggregate and standardize detailed models at scale from over 6,000 sell-side analysts.

Next, Private Markets. Victor Eng will showcase our expanded capabilities, including With Intelligence, which we acquired at the end of 2025. Then cross-asset coverage. Rose Dezenzo will walk through our significant expansion in fixed income securities.

Finally, GenAI in action. Dean Oligino will demonstrate how we're bringing our data to life through capabilities, many award-winning capabilities like Document Intelligence, ChatIQ, Chart Explainer and Kensho, along with our MCP-enabled architecture, unlocking new ways to interact with our platform and new ways that Capital IQ Pro can serve you better. Each presentation will highlight powerful stand-alone capabilities, but the real value comes from how those capabilities work together to elevate your analysis and decision-making.

My name is Rodney Pedersen. I lead the Visible Alpha business at S&P Global. We started Visible Alpha about 10 years ago to address what we saw as a really significant issue in the marketplace. And that is that consensus estimates were always available at a very high level, so you could look at revenue or EPS. But really, the investment debate was always about much more granular issues. And the sell-side, in fact, put out forecasts on those issues, they were just never captured at scale and that's what we've done with Visible Alpha.

So today, I'm going to walk you through 3 different companies in 3 different industries. And my goal is to show you the level of granularity and specificity that we capture within each company in those industries. So we'll start with a name that we're all fairly familiar with, which is Apple. And as I mentioned before, you could always pretty easily get access to revenue and EPS estimates for Apple, but the debate is always about something more. It's about iPhone unit sales or about revenue expectations in Greater China. Those are the types of details that we're capturing within Visible Alpha.

So from the data that we're sourcing from the sell-side, for Apple, if you follow my mouse on the left-hand side, you'll see a revenue model; a product segment model, geographic segment model; and as you might expect, an income statement, balance sheet and statement of cash flow.

So we'll start with the revenue model. And in this case, very specific to Apple, what you're going to find is we will give the net sales expectations for every product in their portfolio, along with unit sales and average selling price assumptions from the sell-side. So you can see a great deal of granularity here that ultimately builds up to the total revenue estimate at the bottom of the page. I mentioned earlier the Greater China example with Apple. So we could take a look at net sales in Greater China, look at the forecast for that particular segment of their business and we can actually start interrogating this data in more detail.

So what we can see here is that Apple has been in a decelerating growth phase in Greater China over the last 4 years. You can see it bottomed in fiscal 2025, which we would certainly attribute, in some degree, to the tariff activity. The market has a really significant bet on Apple's Greater China business coming back in a very big way over the next 4 years. So this is an example of the importance of tracking this type of granularity within the Visible Alpha platform. It can give you so much more insight into the market level of thinking on a business like Apple.

So let's switch gears and go to a different company. We'll take a look at Shell within integrated oil and gas. I mentioned the revenue and segment models from Apple a moment ago. You'll see a very different set of reports for Shell because it's a very different business. We'll take a look at their upstream business specifically, which will be an income statement showing revenue expectations for upstream, different expense lines such as depreciation, amortization and exploration costs and then getting into EBITDA and net income on both a GAAP and operating basis.

Interestingly, we also provide you with some of the input assumptions that go into those revenue estimates. So for example, we can look at the volume projections on a production per day basis and we can also look at the pricing assumptions for the commodities that they have exposure to in their upstream business. So let's take a look at the Q2 estimate. And to no surprise, with the conflict in the Middle East, you see a large increase in the expectation for pricing over the last 1 month to 1.5 months. That should be no surprise to anyone. But we can interrogate this a little bit further and gain an understanding of when the market expects liquid pricing for Shell to return to pre-war levels. And in this case, we can see that deceleration happening over FQ3, FQ4 into FQ1. Now of course, this will continue to change as new information comes to market and we help our users capture this on a point-in-time basis so they can keep a very close eye on market expectations with respect to these very important issues with a business like Shell.

Finally, we'll go to one more industry, which is the pharmaceutical industry. We'll take a look at Eli Lilly. And as you might expect by now, if we were to look at the models that we've created for Eli Lilly, it's very specific to their business and the different areas of disease that they treat. So we'll look at the revenue model, and you will see all of the drugs that Eli Lilly is producing or has in pipeline with projections well out into the future. We're actually tracking projections into the 2040s in this case.

And so I'd like to take a look at Mounjaro, but to do so, I'm going to take us into the Visible Alpha BioPharma platform. This is a new product that we released recently. And what we did was we took all of the drugs from all the companies that we cover, so Pfizer, Eli Lilly, GSK in Europe and extracted all of those drugs into 1 platform, allowing our users to screen by indication. For example, they could find all drugs associated with ovarian cancer, mechanism of action, the clinical phase that the drug is in and really start to do a really effective screening exercise.

So let's take a close look at Mounjaro. This is the leading drug in the GLP-1 category. It's been very popular in the marketplace. So here, first and foremost, we can see the revenue projections, again, going well into the future. We're displaying to 2033 and noting that peak sales happens in 2041. And as we did with Apple and Shell, we'll give you a complete decomposition of how the market is arriving at its revenue forecast between U.S. and international, where the drug is treating type 2 diabetes versus obesity.

And then finally, some really important related metrics like the number of patients on GLP-1, the capture rate for Mounjaro and so on and so forth, leading to total revenue. So I hope that was a helpful example going through a few companies in a few different industries. And I will turn it over to my colleague, Victor Eng, for an overview of private markets. Thank you very much.

Thanks, Rodney, and good afternoon, everyone. My name is Victor Eng, and I'm excited to be here today to share what we're doing on the private markets side of things. As you're all well aware, the private markets are famously known for being opaque, fragmented and lacking when it comes to transparency and having a common set of standards.

At S&P, we're focused on bringing transparency to the private markets by tracking the flow of capital at each stage of the fund life cycle. And it's really the combination of S&P's current coverage, our recent acquisition of With Intelligence and our linking capabilities that really put us in a great position to connect the dots across the private markets landscape. And this allows us to answer questions related to capital formation like what have fundraising trends looked like in recent years, but then also give our users the ability to break that down into any combination of asset class, strategies, regions and/or sectors. Rodney shared earlier how we can deep dive into specific sectors like pharma to analyze KPIs on specific drugs.

So let's continue with the health care theme and look at PE/VC fundraising trends for health care, and then ultimately be able to see which funds are in market, what's their fundraising status and are they under or oversubscribed? Taking that one step further, let's look at the historical performance and see what that's looked like from a benchmarking perspective. What were the median and the quartile returns for each vintage year and then take that even further and look at fund level returns so that we can see which GPs had the top performing funds.

And also for those funds, who are the top investors based on the capital commitments? When it comes to investor targeting, we want to help GPs find the right LPs faster and then help them understand which types of investors have committed capital to health care funds, in which geographies and then which ones are looking to increase their allocations?

And this, in particular, is where With Intelligence's coverage of investor intentions and preferences is highly differentiated since they collect this insight from direct engagement with key market players. And it's also highly actionable from a fundraising perspective, given they can offer the context behind those investment decisions. We can also help arm our users with details around which GPs have the strongest relationships with each of those investors and then which ones have strong track records for delivering outsized returns? We can then take that one step further and pull up the profile for a specific investor and look at AUM over time, review the time line for their intentions and preferences, look at their investment allocations by asset class and then compare those current allocations against the target ranges.

We can also identify who the key decision-makers are in when it comes to making allocation decisions and then, of course, what's their contact information? We can also look at their capital commitments and the funds that are in their roster or in their portfolio and much, much more. So the takeaway is simple. S&P is focused on bringing transparency to the private markets by connecting fundraising activity, LP commitments, performance context and then investor intent. So ultimately, GP teams can move faster, they can prioritize their outreach with confidence and tell a stronger story in the market.

With that, I'm going to hand over to Rose Dezenzo to take you through the latest developments in our fixed income offering.

Thank you, Victor. My name is Rose Dezenzo, and I am the team lead for market data delivery on our desktop offerings. As part of the expansion effort, we achieved broad coverage across the fixed income universe, adding over 30 million government, sovereign, agency, corporate, municipal loans and CD securities, enabling you to efficiently review the entire debt and equity capital structure of an issuer.

As you can see, we have a heat map here at the top as well as a ratings distribution chart. The heat map will be present on the corporate's page and then you'll also be able to toggle to a government and agency and sovereign page to view a heat map based off of the world map. Both of these views allow you to get a perspective or a comprehensive view of market dynamics across sector and region. You can also use these heat maps to filter. I'll select the health care industry. And once I do that, you'll see that it has expanded to the entire industry tree. As you scroll down, you'll also notice that the information has expanded to also filter the bottom grid. And you'll note that by identifying under the industry tab, the health care information.

You can select any of those items and be directed to a security detail page. Here, you'll see the full depth and breadth of the offering. The various tabs here at the top allow you to navigate through the content. You will land on the pricing and analytics page, which provides a comprehensive view of pricing over time, and included in that would be the price and analytics information as well as liquidity scores. Scrolling back up, you'll notice that the reference data tab now includes comprehensive coverage of all of our deep and rich terms and conditions information for any of the fixed income securities, including scheduled information as well as regulatory information, which you'll find here at the bottom.

Fixed income ownership reveals who holds each security, concentration levels and institutional ownership, including owner type, portfolio turnover and debt emphasis. The AI-driven comparison tool found under the Similar Securities tab allows you to quickly compare similar securities by rating, debt type, currency and maturity, helping you spot outliers as well as portfolio opportunities.

How can these enhancements help you? First, it enables faster, more confident decisions by quickly accessing the data you need for risk and analytical workflows. It will reduce reconciliation time through the use of integrated tools to streamline your processes. It offers comprehensive coverage to analyze the full capital structure and market landscape with ease. And finally, it provides actionable insights. You instantly visualize market trends and liquidity and assess risk with advanced ownership and comparison insights.

Now I'm going to turn it over to my colleague, Dean Oligino, who will take you through our GenAI offerings. Thank you.

Thanks, Rose. My name is Dean Oligino, and I'm excited to close the demo portion of today's session by sharing how AI is transforming Capital IQ Pro. First, it's important to recognize that AI isn't new to Capital IQ Pro. We've been using it for years for entity tagging, topic classifications, table extraction, sentiment analysis and audio transcriptions for our live transcripts. Last year, we took a big step forward in launching major new capabilities, leveraging generative AI and LLM technology.

I'm going to show Document Intelligence; Chart Explainer, very briefly; and then deep dive into how ChatIQ is evolving. So with Document Intelligence, users can sift through millions of documents in our platform and extract insights using GenAI. Here, I'm going to select some filings, some transcripts and a whole bunch of S&P authored articles to get insights into an M&A transaction. Since this is an M&A deal, I'm going to ask for a deal memo. And very quickly, you can gain insights into the deal terms, the financial metrics, the strategic rationale and the time line of the deal. All of that is backed by the underlying source documents, so a user can validate the information and gain more context.

Now I mentioned millions of documents, but we're always expanding. For instance, the 20,000 documents from With Intelligence, that powers much of what Victor showed earlier, will be coming soon. Also, later this year, we'll be adding the ability for users to upload their own proprietary documents, so they can co-mingle chats with their documents and ours.

Next, I'm going to look at Chart Explainer. Who here has ever looked at a chart and wondered, "Huh, I wonder what happened there?" Well now, with Chart Explainer, you can visually inspect peaks and valleys and see all the news and key events that happened behind the chart. That provides the user context you cannot get simply from a visual.

Moving over to ChatIQ. We are moving in a direction of a workflow partner, not just a chatbot. And let me show how this works. First, ChatIQ has access to the whole repository of data within the Capital IQ Pro platform. If you want to ask a complex business question that is quite open-ended such as what's the outlook for weight loss drugs? Well, Cap IQ Pro can access the really deep and rich data from Visible Alpha that Rodney showed earlier, but we can also supplement it with broker research, news, filings, transcripts to bring a comprehensive and robust view of this kind of question to our users.

You can ask what are the current implied deal multiples in the health care sector, combining analytics and screening. We even have macro data. So how has tariff policy impacted retail pharmacy sales. So these are open-ended questions that a user may ask. But we also know that there are tasks that our users do day in and day out, and we're building skills to help them on those tasks. For instance, if you are looking at monitoring the market, if you're sourcing a deal or if you're doing a financial analysis plus many others, we have the information in the system and the workflow skills to be able to support those.

Here, I'm going to generate a company valuation. Now what ChatIQ is doing is not just pulling data or presenting you a view, it's actually doing all the tasks necessary to produce a valuation. It's finding the comps, it's pulling the multiples, it's finding the precedent transactions, it's creating the DCF. So all of these tasks that a user would have to go manually do, it's pulling together on the user's behalf. And then it's assembling it all into the actual analysis that a user needs to consume. Now this isn't just a chat response, this is fully interactive and editable. So if a user wants to change a metric or add a peer to this valuation, they can do that very easily and see the whole analysis update.

Now in the journey of our users, this is not the last step, but oftentimes, they want to go create a deck. So I'm going to go ahead and ask ChatIQ to create me a PowerPoint. And now since we were looking at a valuation analysis, ChatIQ knows that typically in these types of analysis, there might be an overview. We're going to feature the visual. We're going to have some backup exhibits, maybe a SWOT analysis. All of this applied in the client's own proprietary brand. Now the best part about all of this is every exhibit is backed by an Excel file linked to our Excel add-in, which is fully refreshable. That gives the users full transparency, full auditability and full control.

Now with our GenAI initiatives, it's not just in the browser. We've introduced ChatIQ into mobile. And with our recent acquisition of Drift AI, we are now bringing modeling into Office directly. So in a simple prompt, I can ask for a DCF model. And this is creating the inputs, the SPG formulas, the ifs, the sums, all the dependencies, all the things that make a model work are being created in the background. Everything I've shown here today is built on top of MCP.

And what does that mean? Well, simply, it means all the investment that we are doing in Capital IQ Pro's GenAI capabilities are now available for clients and partners to build their own agentic solutions. An example of this live today is in Claude. Claude can access Cap IQ data through the Kensho LLM-ready API and produce analysis. And if you're in Claude, you can specify, I want Cap IQ, knowing that it's trusted, accurate and verified data. So for us, we're building GenAI tools in the browser, in office, in mobile, but also in any of our partners such as Claude and ChatGPT. We want to be wherever our users are.

Hello, everyone, and welcome to today's webinar. My name is Justine Iverson, and I look after the Corporate segment as well as the AI strategy for Data and Research within Market Intelligence. I'm thrilled for you to all join us today for our webinar, Reinventing AI Strategy for 2026.

Before I introduce or let our esteemed guests introduce themselves, I quickly just want to go through a couple of housekeeping items. The objective of today's session is for this to be interactive. You'll see there's no slides in this presentation. This is an open conversation amongst experts within the AI space to help you as you're thinking about your AI strategy. But at the bottom of your screen, you'll see some widgets where you can gain access to some blogs and some other resources as well as the ability to ask questions. We want to hear from you. We want your questions. So please enter those throughout the session. And we'll do our best to answer them all. We probably won't get to them all, but we will do our very, very best.

With that, I'm going to quickly introduce myself and then pass it to my -- like I said, esteemed guests to introduce themselves. Like I said, I lead Corporates and AI for Data and Research. So very simply put, that is Cap IQ and the data feed delivery of all of that great content. So I have had the pleasure of working with the 3 on this call, Francis, Jesse and Alaina in various different roles. And also get to spend a ton of time with clients and some of our partners in the space as it relates to AI. So I'm excited to talk about that today. But before we do that, Francis, I will pass it over to you for an intro.

Hello Justine, thank you for welcoming me. I'm Francis Hintermann. I'm the Global Lead of Research at Accenture, working from New York City in a team, which is growth in strategy in charge of supporting the development and the implementation of the strategy of Accenture.

Fantastic. Thank you. Jesse, over to you.

Awesome. Thanks, Justine. I'm Jesse Kramer. I look after M&A and investments at S&P Global for the company as a whole. So supporting Justine and team thinking about inorganic growth, but also our ratings, energy, addressable MI division, our Index division as we think about how to grow the company. We spent a lot of time with emerging companies in the space, thinking about how they're applying new technologies to our clients' workflows and our workflows. And so I'm excited to be here today.

Awesome. Thank you. And Alaina, last, but of course, not least, to you.

Thanks, Justine, and really excited to be here for this discussion today with you and Francis and Jesse. My name is Alaina Tosatti. I lead our -- what is the Strategy and Business Transformation team in S&P Global Market Intelligence. Market Intelligence is one of the business divisions of S&P. It's about a $5 billion business, and it houses, as Justine talked about, brands like Cap IQ and our unique data and IP, along with other offerings in software and services, really focused on serving into our -- into the capital markets. So looking forward to the discussion today. I spend a lot of my day and time thinking about growth opportunities, how we can be more efficient and how we balance that with risk across our portfolio in Market Intelligence.

Awesome. Thank you all so much. I promised everyone I wouldn't make them give a fun factor up themselves on their intros. So sorry, you all missed that portion. With that, the basis of this webinar really came out of the hundreds of client and partnership engagements that I mentioned earlier on. Candidly, it's the favorite part of my job is to be able to be in the market, see what's happening. It's such a fun space. I say this all the time. I've never worked in something moving so quickly, particularly as we think about you all on this call, right? You all work for banks, investment managers, corporations and I think you probably all are feeling the same that we are. It's moving quickly, and we're doing our best to meet you and serve you where you are and make sure you're getting the most out of our content and our offerings in this space.

So the blog that I offered was really based around kind of a couple of key trends that I saw. So I'll hit on a couple of those and just to get the conversation started and then get some thoughts from Francis and team. So I would say a couple of the key trends, I'm not going to go through them all, but the biggest trend, I will say that I'm seeing to be completely candid, is organizations are still figuring out their AI strategy. So if you feel like it's evolving or there's something new happening every day, you are not alone. That is the #1 trend I'm seeing no matter the size, sophistication, the market cap of the organization.

And I think following that, there's a real push today more than ever to really determine and measure the ROI and the impact of that Gen AI initiative, right? I think we shifted from a time of a lot of POCs and a lot of experimentation to now a real push for understanding that top bottom line impact that organizations are seeing. I was hearing this in my client conversations and working with our partners. And so I actually did a little research based on our earnings call transcripts that we have. I went and looked from Q3 -- Q4 2023 to the end of last year just to see how mentions evolved across earnings calls. Again, this is for our whole corpus of earnings calls. So very broad swath of global companies. And super interestingly, over that time, AI mentions, right, just the mentions of AI in these earnings calls was pretty steady, about 4.5% increase over that time. So nothing totally drastic there.

But what we noticed is over that same time frame, there was a 57% increase in mentions of AI cost savings and positive sentiment around cost savings related to AI. So you can see how that trend and that management expectation and Street expectation of ROI on this investment is really starting to play out across all industries, all sectors, all geographies. So that's one trend that I really started to see evolve over the past 12 months that I think will continue into 2026.

Another quick one. I think there's a bit of speculation or where is this all going to go? But at the end of the day, money talks and money is still flowing. In 2025 alone, according to Cap IQ, there was a $95 billion raised across 143 funding rounds. And that's for AI-specific firms. This takes out chip manufacturers. This takes out data center providers, right? This talks solely about that, nearly tripling from 2024. So money is still flowing. There's still investment. There's still a lot of interest in this. Jesse, I know we'll talk about this a little bit later from your perspective.

The other thing I'll say that I've seen a big evolution over the past 12 months is the partnership ecosystem continues to evolve. We do a ton of partnerships at S&P Global. The AI firms are partnering with each other in different ways. We'll talk a bit more about that later. So that continues to be a big trend.

Two last points I'll make before I open it up, I'll say, is that the risk tolerance has really evolved. I would say when I first started meeting with a lot of clients, there was probably 2 big camps. One camp of we're all in, we're opening it up. We're letting our employees or our organization use AI, use whatever tool they want. Obviously, you can imagine some of that is tightened as there's concerns around IP and data protection of internal information, et cetera. But on the other side, we've seen firms that were a bit more slow to adopt or a bit more conservative, really evolve to really change their posture and figure out how to bring that into their organization safely, soundly, securely to really help their employees.

And last but not least, I have to say this, but it's true, it's all about the data. Data is the foundation, whether it's our data using data like S&P Global's data, proprietary data on the client side or other data, it's all about how you are utilizing that data to get the most out of it.

So those are a couple of key trends I've seen. Before I pass it to you, Francis, I'd love to ask the audience if my first hypothesis or my first observation plays out. So how many AI tools has your team trialed or adopted in the past 12 to 18 months? Would love to see, is it 1 to 2, 2 to 4, 5 plus? Or are you guys still early on your journey? And I would say, I won't scoop the audience because you all put in perspective. But from my view, we've seen a ton of optionality in this space, right? There's the hyperscalers such as [ Claude ] and OpenAI really investing in this space all the way to these last mile solutions that do something really, really well. And that's creating a lot of optionality across organizations. So let's see what you all said.

So let's move to the next. All right. So pretty well versed here. No surprise. Most are between the 1 and 4 points. That's actually probably what I've seen, right? And 1 to 4 could be maybe one's homegrown or something internal, mixed with a third-party application or even using Gen AI tooling in a solution or tool that you already have adopted and used for many, many years. A great example of that might be Cap IQ. 5 plus, interesting to see almost 90% of that. That's still a lot of different tools to trial and experiment. So definitely what we're seeing. But with that, enough for me.

Francis, what have I missed? What are you seeing? What do you think is also happening in the market?

Yes. I don't know -- I didn't know if I could answer the survey just since I did not. But just in full transparency, I would have been in the 5-plus category, so the 19%. So because we're testing tools, new tools every day. And I think it's part of what is fascinating right today is that we've got new options coming nearly every day. So it's interesting to see where your participants are.

Thank you for asking me this question. I read you on a regular basis. I read your top 10 trends with interest. And out of what you mentioned earlier on, I'd like to pick up the one on ROI because, of course, as part of my remit at Accenture, I oversee all the thought leadership that we develop and we publish and we share with our clients. And ROI of investment in AI has been a source of questions for the past 3 years. So it's definitely one that we are extremely interested in. I agree with what you mentioned around cost saving, around use cases that you call administrative that we would call horizontal ones, right? Think about customer service, think about knowledge management, think about IT and the tech organization itself. Absolutely, yes. I think what's interesting though, in last year and even more this year is that we can see the verticalization, what we said about verticalization happening, meaning development of AI as part of what is really specific to industries, part of a core value chain. And that means that beyond the cost savings, there are opportunities as well for revenue growth for companies. And actually, we survey our clients and our partners on a regular basis at Accenture, and we published just our latest survey of CXOs at Davos, so 2 months ago. And we were asking some of the CXOs whether they are -- they have a choice to make, is AI more an opportunity to grow the revenue or more an opportunity to reduce the cost. And actually, 78% should be emphasis on revenue growth in the coming years.

And to us, that's an illustration of the fact that some of the AI implementation is moving to the core value chain of companies where they can actually create more value, create more opportunities to grow. We published some of these examples in a PhotoSheet that we published actually yesterday with the World Economic Forum on the organizational transformation in the edge of AI. And you will see there lots of case studies in different industries. If I just got to mention one to make it tangible to your audience, it's about the pharmaceutical industry, life sciences. And we can see there that in the drug discovery in R&D, which is very, very specific to life science, AI can actually help not only to accelerate the discovery, but actually change the discovery process itself. So for me, it's just one example. I could add more. But in the interest of time, I will stop here. Justine, I could react on other trends as well. I keep that for later on. But I like your point on data. So maybe we can come back to that later on if that's of interest to the audience later.

Yes. No, thank you. I always -- I think everyone wants to hear real examples. So the life science example makes complete sense. Obviously, in our world, we service kind of the range from life sciences all the way to financial institutions. So we see, obviously, a ton of our use cases really around that financial services use case. So Alaina, I'm curious from your view, like what are you seeing from your seat based on this? How is this impacting how a company like us, a major financial institution that services a vast array of clients? How are we thinking about our strategy and how we evolve that over this time as well?

Sure. Happy to jump in. Francis, really like your point about the shift to the focus on revenue growth and opportunity. I think that's something we're living and seeing kind of firsthand. Maybe taking a step back first, just thinking about the market and what have we been seeing, right? The pace is just the thing that stands out the most with this landscape, right? What we've seen from a development perspective has been incredible, frenetic is a word that gets used quite often, just to add to that piece. You think to the launch of Claude Cowork earlier this year, and that's really furthering this expansion into enterprise use cases, right? So it's clear now that Agentic workflows can and are being applied today to real work for our customers within our teams and Market Intelligence, and they're capable of completing these really kind of complicated tasks autonomously. So this is real. It's happening right now, and the pace is just an unbelievable adoption level.

And for businesses like ours, I think that really shifts that expectation of how we're going to use AI, whether a year or 2 ago, when you were talking about efficiency gains and optimization, now it's all about business transformation. What are we going to look like in this new age and how will we remain relevant and how will we pursue growth with this new paradigm. When we thought about it within Market Intelligence, we really leaned on 2 perspectives. First is really how the customers themselves for Market Intelligence are going to be using or are already using AI to transform their own work. And this will vary by use case, right? We giving a specific example, thinking about the buy-side customers, right, asset managers and hedge funds that we may work with, they're leveraging AI to kind of better ingest and synthesize and make sense of really large volumes of data that they're getting from multiple sources, including their own proprietary data that they want to keep quite safe and protected. And that will really help them with alpha generation, which is the ultimate end goal. So again, as you talked about data, that really resonates because certainly, one of the core tenets of what we offer into the market as a data partner is that providing of differentiated data to these firms and making sure that our data is ready and fit for purpose for whatever new tooling we may see within the customer segments.

And then the second lens that we've spent a lot of time thinking about, of course, has been sort of transforming within our own 4 walls. How do we rethink our workflows within Market Intelligence to leverage AI better. And we could talk about examples here within customer support teams, so better enabling some of those teams to get requests done quickly and efficiently so we can focus on the higher value and more of a white glove with customers or whether that be in our data operations groups who are automating a lot of the repetitive tasks and focusing on data ingestion and linking and normalization, which again speaks to how valuable that data will be once we can deliver it back to our customers.

So the real call to action there has been just embracing AI across everything that we do, thinking about not only how it will drive efficiencies, but how it can really drive value as we go forward. And maybe just one last point to add, and I think we can dive into this later if we need to. But really, the other element that we've thought a lot about and continues to remain critical is trust. And so again, as customers are adopting these tools, as we're using them more frequently, it's really critical to have the trust and the governance mechanisms in place to ensure that we keep that high quality and really what has defined from an S&P perspective, our brand in the market for decades.

So I'll stop there for now. Same with Francis, we could probably go for a long time on each and every one of these, but we'll stop there for now.

No, I love it. And you mentioned Claude Cowork and how quickly some of these tools have come to market and how quickly clients are interested in exploring. So with that, I'm actually going to go to my second poll question because I would love to see on this out of our group, what is your firm adopted internally? Are they using Claude, ChatGPT, a workflow-specific tool, right? There's a ton of these in the market that do a specific workflow very, very well. They're obsessed with solving that specific workflow, whether that's a Rogo in investment banking, a Harvey in the legal space. Are you using a homebuilt internal solution? Or are you not using anything yet? You're still kind of in this experimentation phase. So I would love to see what's been adopted on the side of all of our attendees.

All right. I think we should be able to see results now. And again, I think this plays to our previous one. There's a bit of a mix, right? I've seen a ton where there's actually a bit of a mix of tooling. So okay, interesting. ChatGPT, no surprise. I think we're seeing a lot of that. What I've seen candidly in my engagements across our corporate base, so think technology firms, consulting firms, we see ChatGPT as one of the early emerging winners there with [ Claude ] really making a lot of adoption within that investment banking financial services space. But again, these workflow-specific tools, we're seeing it. And I think a big point that we talked about, and we'll talk about this a little bit more, I'm seeing some questions come in that play to this is there's a lot of homebuilt solutions that are fantastic as well.

One of the big questions that came in and that we talked about a little bit was around organizing internal data. That is not a new challenge for organizations, right? That's one that we've seen in the market forever. I think AI just shines a light on that more than ever. And so something we've done at S&P is we've really tried to lend our expertise to help organizations with that. That's something we do, right? We're a data company. We take messy data, we make it organized and valuable. So that's something we spent a lot of time on is just thinking about how you do that. A great example, if you try to take tabular structured data and just put it into a large language model, you're not going to get great results. But if you do some technical work such as some python wrapping with -- you apply some business logic to understand, you can start to get really, really powerful results out of that. How you mentioned, Alaina, getting information out of vast amounts of textual data, for example, very, very quickly is a great example of that.

So with that, Jesse, I want to take a little bit of a pivot here. I know you spend a ton of time observing the market, trying to see who's going to be a winner, who's not. So I'm going to ask a little bit of a cheeky question. What's your prediction for the IPO market in 2026? And then we'll put up our fun poll question that might spur a bit more conversation from you, too.

Awesome. Well, Justine, I love a cheeky question on some of this. I think heading into '26, I think people all thought it was going to be a pretty robust IPO market. I think what's happened is in patches, there's been maybe less confidence in that market and MA markets in general because kind of what is valuable about companies is starting to change, and it's changing because of the fast pace of innovation and the thought that AI sort of can do everything or at least can do a number of very important tasks in our economy. And I think that probably is true to some extent, perhaps not as true as every kind of equity research analyst believes or worries for the companies in their portfolio, but particularly around kind of more traditional client software companies, even data analytics companies like ours, I think valuations have been a little bit more uncertain.

And I think for parties who can't sort of show real kind of AI traction, there's been sort of weakening of valuations. I think it will make it harder for companies like that to go public. Some of those, I think, were in kind of the queue to potentially IPO. At the same time, there's a set of companies that are only stronger because of this. The large sort of frontier labs, I think, are kind of queuing up to try to go public at the end of the year. And there are companies that are sitting on the data that powers AI, sitting on the kind of data warehousing and cleansing that really supports this a set of companies that are building that last mile of potential application layers on the AI models.

And I think they will be kind of a robust sort of set of potential IPO candidates. Whether that happens this year or happens in the next couple of years, I think, is an open debate. But I think we will start to see a few of those companies go public and that will require a strengthening, I think, of governance, sort of a change around some of the kind of circular economy phenomenon that's happening and probably a little bit more of a shift towards profitability in those businesses. But if one does, these things tend to come in trends. And so you can see a number of others kind of flowing from that.

I love it. And I'm going to ask my last polling question for the audience and based on your response. So of the audience, who do you believe will IPO first? Anthropic, OpenAI or you don't think either will? I know those were -- we see a lot of -- there's a lot of headlines about this. So curious what the audience thinks about this one. Give it another second or 2.

All right. Let's see what everyone thinks. Oh, mix bet. All right. This is probably how I feel about it. It's pretty mixed. So about 27% think Anthropic, 39% think OpenAI and then 1/3 also think it's neither. So I guess time will tell. If we had a magic ball here, it would be great, but we will see what happens throughout 2026 on this front. Awesome.

I think, Francis, I'd love to come back to you. What surprised you the most over the past 12 months? Or what's changed the most from your perspective on the AI front from your view?

Well, many things. But if I had to pick up one, I would pick up the one on work. I mean Alaina was mentioning some of it within your own company and what you do for clients. Definitely, we see a lot happening in the market. If we just start with a question of usage of AI tools as you were pulling the audience, Justine, we can see some shadow AI in place in companies, right? We've got executives sometimes telling us, well, employees are not so enthusiastic about it. That's not what we see. Again and again, as we pull employees of large companies during the year, 3 or 4 times a year, what we can see is lots of interest from employees to the point that when they have not access to the enterprise version of some of these tools, they actually use their own personal account to use these AI tools at home and then feed that back in the work, which obviously what we call shadow AI, which obviously is not good in terms of everything you can think of, of intellectual property of responsibility of ethics and so on and so forth. And so for us, that's really the imperative for executives to actually answer to the needs of their employees and understand where it's going on in terms of the job market and how they can help their employees in terms of upskilling and reskilling.

And in more general terms, we see an evolution towards what we call a skill-based economy, more and more defining the needs depending on the skill of employees. And there is a big mismatch there. We actually built an index with Wharton University for all of you, if you're interested, it's out there. It's on knowledge at Wharton. And you can look at your own skills compared to the market trends and what is asked by employers. And even we attempted to put a monetary value on some specific skills to measure the current mismatch.

And broadly speaking, what we can see is that this mismatch is at the core of AI adoption at scale and will impact the ROI that we were mentioning earlier on. So for us, that talent reinvention is really what we started to see in the past year and what we envision as being one of the major trends over the coming months and the coming years because it will take years, but that talent reinvention, making sure that employees have got the relevant skills to perform in this AI economy is going to be the critical factor to make it a success eventually.

I couldn't agree with that more, and I have a funny, maybe not funny story from just this week is a bunch of us internally were talking about some of our future AI work that we're doing, a ton of excitement around it, and we're taking notes. And halfway through the meeting, we're like, why didn't we turn on Copilot to take notes for us, right? Like it's a very -- and someone on the call said, yes, my son would have not even thought twice about this. It would have already been on, it would have been part of the workflow. And that's just funny because, to your point, there's a change management in the current workforce that needs to happen. We have these tools, but we need to start adopting them. We've worked a certain way for so long. There's human inertia in how you do your job. So there's that.

But then to your point, there's the next generation that this is inherent. This is part of their day-to-day. They've never not lived without this very streamlined experience. So I also believe change management and talent management is an area we're seeing a lot of focus on that, that needs to happen. How do we upskill our current employees, how do we prepare for the future? And what does the future look like? I've asked CCOs at banks, the junior banker, what does that look like to you? And it's hard to predict what that's going to look like because not only do they do certain jobs that can become more efficient with AI, but we're also the bench for the next job. So how do you balance what needs to be done today, how we can be more efficient today with building the bench to continue to grow that business overall. So I completely agree on the change management point. We've gotten some questions on that. So I think one of the biggest challenges, that was one of the questions as it relates to people is change management and integrating it into workflows, really understanding how that evolves the day-to-day. With that, we'll do a couple more questions, and then we'll go to Q&A because we have a ton coming in. Alaina, what do you think will change the most in the next 12 months? I know that's a tough question, but what do you think?

As we were saying, it's the one on everyone's mind. So I'll take a stab at, at least my perspectives. And in fact, picking up Francis perspective on one of the points you were raising about shadow AI and the idea that today, if we aren't moving fast enough in enterprises, it is on the consumer side, just, again, a pace of adoption that we have not seen in any other technology of late, and it will only kind of increase in sort of complexity and speed. So that was one of the points.

As I think about the next 12 months, I think consumer AI tools will continue to move even faster. And what does that mean on our side? Well, that just raises the expectations and the strong bottoms-up pressure that enterprises are feeling to keep pace, right? We have to be able to provide these tools in a safe and controlled and risk -- our own risk environment in order to better serve our own employees, but also ultimately into the end customers. I mean you think of the recent launch actually with Google Maps, right, and how they've now integrated Gemini AI into their maps application, and that's going to transform how we interact there with new recommendations and suggestions in this Immersive 3D experience, right? So we're seeing it rapidly and now and it's getting ahead of us on that consumer side. And so that is creating the right flywheel, I think, for the enterprise as well.

Maybe one other point then for the next 12 months is I think that high-impact enterprise use cases will continue to scale as we think about this next year, right? We think about investment banks who are already leveraging AI for step changes in how they generate pitch decks or investment memos and again, aggregate all this input and take things from days to minutes. That will continue. And again, in that poll and survey that talked about homegrown solutions that may be one of those unlock enablers, especially within some of the more regulated industries and intensive areas like banks that we work with.

And then I think back to the question on some of those LLM providers and where those are going, I think they'll continue to evolve. I mean when we've seen releases of new models that sweeps and bounds each time. So again, this will continue, and we're going to need to continue to kind of keep up. And I'd also expect a lot of them to -- and this is something we've obviously embraced and you've led for many of the discussions Justine on our side, but these continued partnerships between some of the more -- the data as well as the vertical solutions alongside these incredible models and the capabilities there just to better unlock very specific use cases for the customers.

I love it. We're going to do a quick lightning round, then we're going to open it up because we have received so many inbound questions. I would love to open it up to the audience to answer some of those. But a quick lightning round. And while I'm getting to it, feel free to answer the question on the screen here. What is one prediction or outlook you have for the AI market? And who -- or who do you think is going to be the winner? And again, don't worry, we're not holding anyone to your opinion today, but we would love to see what you're thinking today. Francis, why don't we start with you?

Yes, I'm not in the business of identifying winners directly. But what I can tell you is what we can see growing. And what we can see growing is the focus on what we call sovereign AI. I mean, what is happening in geopolitics. Obviously, we see it every day in the news. And it is impacting our clients. We, at Accenture work predominantly with large companies around the world. And this question of sovereign AI about what part of the stack has got to be localized, where you operate, how you develop the interoperability between the different layers and the different regions and still keep some agency in your strategic moves. For us, that's definitely a winning topic, if I can say it this way, Justine.

Love it. Jesse, what about you?

I think the status quo is probably likely to continue with kind of different providers being good at different things and continuing to sort of leapfrog each other. I think that's going to happen for a while. It seems unlikely to me that things will meaningfully converge to one provider, my read.

Alaina, I know you answered this a little bit, but if there's anything you want to add, your welcome.

I was going to say I crept into it a little bit in my last one, so apologies. But maybe I just double down on the point. I think we're in this -- as they kind of called it an industry era of specialization, right? No more general purpose AI. We're seeing specialized models, agent skills being developed. These are solving very specific domain challenges for industries. And so I guess my prediction around this is that we just continue to see the rise of some of these more specialized models, they also offer the economic benefit and the right fit for a lot of the use cases that need to be deployed against and ultimately can help us deliver more trusted outcomes. So a little bit on that.

Love it. My answer actually plays a little bit into one of the questions we got. One of the questions we got, so I'll answer it with my prediction. One of the questions we got is there's a lot of hype, right? There's a lot of press releases. There's a lot of noise out there. Like how do we know it's real. And I do think throughout the year, we're going to continue to see some of that kind of rubber hit the road, that realness, right? There's -- again, it's kind of how I started. There's a push to really start to see the ROI, whether that's top line growth, bottom line impact. And so there's, I think, going to be a bit more challenging from clients of all these tools, like we need to see that impact. We want to see that. So I think there's going to be a continued push for that. I think I believe that there is a spot for both, for all different types of solutions, whether that's a hyperscaler like Claude Code doing something, whether that's a last mile provider doing something really well. I think the market is vast, and I think there's going to be room for them in 2026, at least we'll see how that continues to evolve into the future from there.

So with that, we're going to open it up to the audience. So I'm going to go through some questions. We've had almost 100 questions already come in. So we probably will not get to all of them, but we will do our best to answer some of these out of the gate. So I think one of the first ones I have and Jesse, maybe we'll direct this one to you. Let me just scroll to it, sorry, we have lots in here. How -- this kind of plays to what you were saying earlier on the markets, but how does the amount of debt taken on by these companies impact their IPO chances? OpenAI is heavily levered. So does that mean they would need to IPO soon to continue the funds? What are your thoughts on this?

So I guess a couple of thoughts. The first is, I think the debt markets and private markets will continue to fund these businesses as long as they keep innovating and growing. I think in order to become a public company, these businesses will need to go through sort of a more rigorous audit and SEC process. A lot of the debt, at least as I understand it, that OpenAI has taken out has been sponsoring pieces of infrastructure projects. And there is a question as to how much of that they've guaranteed and how much of it rolls up into their obligations. And in that world, I think really unpicking how much they're responsible for, are they kind of marketable from a public company perspective is a really good question. There's also sort of a related question of how much of their revenue today relates to related party transactions. So I think that's sort of an important piece as well. But getting clean financials for these businesses is going to be one of the big hurdles, I think, of taking them public.

And then if they are responsible for all the debt they've taken on to build these data center projects and sort of the infrastructure that the models need, I think there's a real question as to whether they can be public this year or whether they have to kind of grow revenue into that to kind of get to some kind of leverage ratio. I mean, today, that almost makes no sense, right, because they're not profitable. But to get to some kind of leverage ratio that starts to make sense.

There's another question that said, what is that going to mean for all of us? And it's hard to see that not eventually meaning that the price of compute and these offerings will go up, particularly for enterprises. And like we're in this moment now of the economics have been made so attractive for everybody that we can just use these tools for kind of everything. I don't think that's the world we'll be in forever. And particularly as these companies look to drive profitability because eventually they'll have to, the use of AI may become a little bit different, and you'll need to be hyper focused on efficiency to use it in a profitable way for your businesses.

I love it. Thank you. Francis, I'm going to pass this next one to you. I think it's a great question given your role. What do you foresee as the future of management and strategic consulting firms in the era of AI? And how do you see that evolving?

It's a great question, of course. And when we look back, 12 years ago, some of you may remember, not all of you, I guess, but that's a privilege of having gray hair is that I was already there 12 years ago. When cloud started to expand greatly, some -- if you were there, you may remember the prediction that we made at the time by some that the consulting industry was going to go down because there would be no need of consultants anymore in the era of cloud. Fast -- and even you had some prediction made by some researchers at Oxford University, which were saying that overall, 47% of the jobs will be automated, and that would be certainly true in the consulting industry even to a larger extent. But if you fast forward then 12 years, you can see that the consulting industry is today actually larger than it was 12 years ago. And I believe that's something of that kind, which is going to happen with that current transformation. If I believe what analysts are saying about that current transformation is that there is a need for companies to get the help of consultants to go through that transformation.

I love it. Yes, agreed. I think it goes back to what we were talking about earlier with change management, right? That's a great area where there's so much support and necessary need from that industry.

I'll answer a couple. We've gotten a couple of questions on guardrails and how to avoid hallucinations. I always joke, I never said the word hallucination at work until the past 18 months, and now it comes up in almost every client meeting. So not a word I thought I would say at work very often. And I can talk about what we've done here at S&P because I think, again, we know our clients, you all make million, billion dollar market moving decisions on the back of our data and on the back of your own expertise and analysis. So the way we really think about that is when you're using an LLM, right, you have your guardrails that you can instill on those. And the way I always explain this very simply is we turn that knob all the way up, right? So we turn those guardrails up. We'd rather tell you we can't answer that than give you a bad answer and answer that's not accurate. And all of our answers are grounded in our leading data. At the end of the day, it's about data. It's about accuracy, quality, completeness of our data, and that remains core to all that we do and what we've always done, what we're founded on. But I think that's an important lever. So one, it's that foundational data layer being accurate, clean, complete.

And then two, it's really about turning up those guardrails as you're implementing that with LLMs and other tools. So that's something that we've done here that has really helped us. And like I said, we are happy to say we can't answer that or we can't do that for you versus giving you an incorrect answer. And then we always ground those answers in those results so that someone can check it. And I think that is something really important as we talk about training and upskilling workforce is teaching that validation step, right, not taking maybe the answer that you're getting as truth without kind of digging into it. We've all seen it. We've all seen the headlines of a fake court case that makes its way into some work or things like that. And so I think as you think about how to avoid that risk, it's also a human element of checking that, auditing those responses as you are taking those answers from AI. So there's a couple of questions on that throughout. Alaina I'll pass...

Can I say?

Oh, go ahead. Sorry, jump in.

Yes. Maybe just one word on that, Justine, because I was listening to you with interest and totally concur with what you were saying. And our own CEO, Julie Sweet, said that it's not about human in the loop, it's about human in the lead. And that has a meaning because everything you said was about the responsibility stays with human in terms of setting the direction, setting the boundaries, making sure that the discipline is actually executed as it should be. So it requires more leadership rather than less leadership. And that's why Julie has been coining that time and again and again of human in the lead. And I think what you were saying, Justine, is a very good illustration of that.

I'm going to adopt that. Human in the lead is going to be my new catch phrases of human loop. I think that's spot on.

Alaina, we're going to -- I'll pass this on to you just because I know you spend a lot of time with our CFO and our team members. What is your view? Are CFOs now being asked to understand AI and the need for strategic framework? Like how does that change how you think about strategic roles and the role of someone like a CFO at an organization?

Yes. I mean, short answer, absolutely. I think as you can imagine, this is so critical from different lenses for companies. As we've talked about, it is -- has been for a long time, been talked about from an efficiency perspective and how can we optimize what we are doing today, how can we free up resources, how can we reinvest that in other places and higher value in new services for customers and new growth opportunities. And again, increasingly, we're pivoting into this new growth paradigm. And so that, of course, those 2 things are what CFOs are constantly thinking about. And so understanding what we are doing in AI and challenging us to continue to do that is definitely a big part of that piece. There's also, of course, an element about how just CFOs and really any teams within organizations, but just picking on that as part of this question, are using it within their own teams today, right? And so again, I think not only from both the role as in representing and thinking about where we're going from a financial profile for our business, but also thinking how we can really improve efficiencies across a lot of the team members that we have today and whether that be in finance or any other supporting team in the organizations. We talked earlier about this incredible need for change management. And it has to be in every team, and we do see that actually today. We see a lot of interest from colleagues across the organization. So we want to embrace that and actually encourage everybody to be innovating a bit in what they're doing. How could -- you take one tool tomorrow and just optimize a little bit of what you've been doing for several years? How can you improve that going forward? So there's some very basic building block and incremental elements that we can all be thinking about. And also, of course, at the bigger picture for the organizations, CFOs and strategy teams are hyper focused on this area.

Jesse, this question kind of plays off that a little bit because these are things the CFO thinks about out of an organization. But what is your thought on the current AI bubble conversation and how companies -- they're accelerating it, but CapEx expense is also increasing where maybe they're not seeing that return. There was an MIT study that said companies are chasing this AI, but they're not seeing that. What are your thoughts on that? How do you see it from your perspective?

Look, I think it's hard not to think there's going to be some correction at some point just because there's so much hype. And eventually, I think we'll see one or more of sort of the big named companies make sort of missteps that will make people question the value of all of this. But I think the kind of overall kind of efficiency gains from the technology and the tools feel real to me. They feel real to me in sort of the -- just use of it in sort of our daily lives. And that is the underpinning of something that's not a bubble impact. It's sort of more economic output that sort of underlies all of this. And so I think it's probably at a specific company level, there's going to be stuff that's kind of overhyped. But at an overall economy level, I think probably grow into a lot of the valuations that we've seen over time. And that makes it kind of tough to invest in the space right now. But it's definitely one that's sort of on my mind pretty consistently.

Yes. I think we've had a lot of conversation on this ourselves between the 2 of us. So I think a big topic that we'll just kind of have to see how it evolves and how valuations continue.

Francis, I'm going to come back to a bit different question or a different type of question goes to it. What's your advice or what have you seen successful as it relates to AI training internally, right? All of these hyperscalers have tools in training. There's internal firms creating it. You talked about firms like your supporting on this. What have you seen work in this space? And what's your advice for the audience?

Try it. That's the advice is that we should all try it. I don't think there is one silver bullet. I think there is an enormous appetite to actually get to some learning, and that learning comes by trying it. We call that the era of co-intelligence. We actually presenting a new research at the NVIDIA event, GTC this week on that. And we say co-intelligence because it's a complete change in the sense that we all can build AI agents. These AI agents are going to learn from you about how to best serve you and you're going to learn from the agent as well. So that's what we call co-intelligence because it's learning from the agent and educating the agent at the same time. And I think for all of us, you mentioned different tools earlier on. That's an opportunity to enhance our own job. And to the point that at Accenture, we created a line of service dedicated to training executives in this area of AI that we didn't have before. We even bought a company called Udacity doing courses because we saw that the appetite of executives across the board was enormous, and we wanted to be there to serve them. But so for me, at the individual level, it's about that. If you don't have your agent yet, build it and you will have fun. Some of it will be extremely helpful in your job.

I agree. I think one of the biggest advice I give is the same. Like you got to start somewhere. I think where we've seen the most advanced adoption is where people really think through their workflow. And instead of just trying to pick anything, they find one spot and really focus on that and then build from there. So I think that's other advice I'd give is really think about your day-to-day or your team's day-to-day or your organization's day-to-day, where is there that constant bottleneck of time and then try it. So I think that's great advice there.

Another question we got and one, candidly, I've answered a lot amongst our client base, et cetera, the question we got was specifically around maybe some of the more traditional legal providers such as LexisNexis, et cetera, and how that will be impacted. I'm not going to speak specifically to them, but I'll speak to traditional offerings or offerings that have been around. Maybe Cap IQ is a great example of that. What does that mean? What does the future look like?

And I'll give my honest view on this. I think it's evolve or die. We have to continue to evolve and meet our users where they are and how they want to work. So the example I always give with Cap IQ, for example, it was built on the foundation of making it easier for people to do their job. I think a marketing slogan early on was get you out at 10 instead of 2 a.m. okay? Maybe our marketing slogan now is get you out at 6 instead of 10. So I think that evolves the foundational basis of what these organizations do has not changed, right? It's to make it easier for our end clients or their end users do their job, but how that gets done has changed. So a big thing we've really focused on is bringing the best of that Gen AI technology to the tools you already rely on. I think we've talked about it today, governance, getting new tools in-house, like that's work, right? That's a lot of effort. You have to go through procurement. You have to go through testing and making sure these tools are accurate, et cetera. So great, let's help our users out by bringing the best to the tools that they've used in their workflows. And so I think it's all about evolution. It's all about meeting users where they are, et cetera. So that's an answer I'll see on one of those type of questions of how does it evolve.

And maybe I can add just one word on that, Justine, you didn't ask me the question, but let me just add one word on that because we've been on that journey of developing partnership with data providers ourselves for our own tools for 3 years now. And kudos to S&P, you were part of the very first companies to actually be out there to develop these new tools with us and to provide lots of data in our own tools through APIs. And we are heavy users, of course, of Capital IQ and SAP Trucost as well for ESG data and very thankful to your company to be there. And really, you were part of the early ones to be in that game.

I love it. I promise I did not plug Francis to say that, that was on his own accord. Alaina, I think you want to add something?

I was going to add because we almost made it through this webinar without using one of the most common things, MCP. And maybe just to put a point on one of the areas that you've that we've discussed and certainly has been a differentiator and as we go forward as part of the strategy as well. But as we think about unlocking, especially as a large -- a company that sits on a large and very differentiated data estate, MCP is one of the ways we're going to enable and are enabling customers today to interact with that data. And this will be key in really helping unlock those agentic workflows for the customers. So back to your point, wherever they are doing their work, whether that be Claude in the future, whether that be their own homegrown systems, as they evolve with that, we evolve and are there in advance, hopefully, and also alongside them to bring that journey together. So we're seeing that, obviously, increasingly from a demand perspective from the customer side and are meeting that too with that just as one example of a way that we're going to modernize from a distribution lens.

Yes. Thank you. We would have been pretty remiss to not mention one of our focus areas. And honestly, what we're hearing from the market, that was a point, right? MCP was something that wasn't a word in anyone's vocabulary 18 months ago, and now it's the biggest topic or one of the most innovative areas that we're seeing. And if I were to make another prediction, I suspect there'll be some new technology or word that comes out in the next 12 months that drives how we're all thinking about this and utilizing AI as well. I know we're almost at time. So I'm going to kind of wrap here. Sorry, we didn't get to everyone's questions. Like I said, we appreciate the engagement. There was more than we could have handled on this. So we'll work to get responses back to folks accordingly.

Is there any closing remarks from anyone? Anything anyone wants to say in departure before we wrap in the next couple of minutes. Francis, we can start with you if there's anything you want to add.

Well, one of the most exciting things right now for me is about AI simulation. And in the research world, for those who are interested in research, we're developing lots of AI simulation in very interested to continue the discussion for those who are interesting on Tech Stack, so we can interact there. And in terms of the business, we can see the emergence of agentic commerce. And for us, that's going to be a very interesting area to follow in the coming few months because we can see that its doubling up in that space.

Love it. Jesse, what about you?

Look, I'm going to echo something Francis said earlier, which is try it. And it kind of goes to the fact that we're in this moment of the adoption curve, which is to say that like it's kind of being subsidized by the big companies and by investors to try to increase adoption. And so it's a moment to experiment, a bit more than normal, try it yourself, get it for your teams. Obviously, the right governance has to be put around it. But even experimenting in your personal life is definitely sort of a needle mover, I think, and it helps you and those who work for you kind of learn about how to use the tools better. And I think that's a big boon right now.

Love it. Alaina?

I'll go back to just my original kind of sentiment around pace and taking a moment to reflect, again, over the last few years of what we have seen and how disruptive it has been and remembering that sometimes early disruption can look a little incomplete and inferior in some cases and make you question whether it's the right direction of travel. This is, as we have been talking about and we can all see now a few years into this, it's very real and very applicable to so many different parts of the industry. So the reference back to the cloud migration years ago, the disruption of BlackBerry with iPhone, many companies have underestimated the speed at which these kind of transitions can take place. So don't be in that camp. And as Jesse said and Francis referenced, try these tools and apply them to what you're doing today.

Awesome. And my closing, I don't have too much more to add other than what the 3 of you have seemed to have said and covered. I think I'll just hit on the last point of this space is moving so quickly, and there's such different knowledge gap -- knowledge areas with people, lean in, right? Find a partner. We're here to do that. Accenture is here to do that. There's so much going on out there that I think it really creates an interesting time just in the business world, in the markets on how you can rethink your business and rethink how you can partner and drive productivity for your firms. And again, at the end of the day, it's that top and bottom line growth. How can we do that? Well, not bottom line growth, top line growth. How can we drive that? How can we continue to push that forward? So reach out. We're here to help. And thank you all so much for joining today. Like I said, you will receive a recording of this. And if you are listening to the replay, thank you, and we look forward to continuing on the AI journey with you all.

Thank you, Justine.

Thank you, Justine.

[Audio Gap] of the business and information services team here at BofA. This session will be on S&P Global. And I'm pleased to have Mark Grant, Senior Vice President of Investor Relations and Treasurer. We're going to structure this session with a fireside chat, and then we'll field the questions towards the end if time permits.

So welcome, Mark. Appreciate for having us -- being here.

Thank you very much for hosting, Wahid. It's great to be here.

To start things off within the information services space, we're asking most of our companies roughly the same question. AI and proprietary data has a debate across the info services group, whether companies have a wall of proprietary data versus having an ecosystem of partner networks. Management has been pretty clear that S&P maintains strict control of its commercial relationships and does not allow LLM providers to train their foundational models on S&P data. As foundation models become increasingly commoditized, how do you ensure S&P's proprietary data remains a competitive moat? And how are you defending against the rise of synthetic financial data?

Yes. We -- this is a really important point, and we know it's top of mind for shareholders as well. When we look across the ecosystem at S&P Global, I think one of the things that brings us a great deal of comfort is just the understanding that so much of our business is really built on storied benchmarks that really don't exist outside of our walls, right? And we've talked about this a little bit publicly.

If you go back to our Investor Day, we put a slide up that kind of shows how much of our revenue is coming from various sources. And about 2/3 of that revenue is tied to our benchmarks business. So that's Ratings, Indices, Platts commodities prices in our Energy division and the distribution of that proprietary content. That's our owned intellectual property. There's no other source in the world for that data. And so while we've said that's about 2/3 of the revenue, it's actually more than 3/4 of our operating profit. And so that huge swath of value that we provide for the market is unique to S&P Global. There's no other source for that in the world.

When we look across the strategy that we have for businesses like Market Intelligence, one of the things we flagged at our Investor Day was that it's not enough to just assume that the world is going to continue operating the way that it always has, right? There will be an evolution of the way customers interact with our data, the way customers interact with our products. And we want to make sure that the strategy we're executing allows for S&P Global to create meaningful value for customers no matter how this winds up playing out, right? So we're embedding AI functionality in our products. You saw us do that with ChatIQ, Chart Explainer, Document Intelligence, all within the Cap IQ Pro ecosystem.

You've seen us do that with the launch of the automated data ingestion tool in iLEVEL, really bringing AI functionality into our products is certainly a big part of the strategy. But to your point as well, having that flexible delivery is also a really important part of the strategy where we can partner with and collaborate with these LLM providers, and you've seen us launch MCP Connectors with Quad for financial services, with OpenAI. We have collaborations with Microsoft Copilot with Gemini Enterprise from Google, right? We're very platform agnostic.

But I think for us, there are 2 very, very important restrictions on those collaborations that would essentially be deal breakers for us, right? One that you brought up is that we maintain strict control of the commercial conditions, right? Every customer that wants to access our data through these LLM providers has to have a contract with S&P Global on S&P Global paper, we control the pricing, the renewals, all of that. And so the disintermediation risk really isn't there.

The other piece of it is that we have to maintain complete control of the data. So our data stays on our servers. The MCP Connector allows these ecosystems to send prompts and queries over into our ecosystem. But because of the Kensho grounding agent, our proprietary data retrieval agents and our Kensho LLM-ready APIs, we actually have very, very strict control even over how many lines of data can cross over at any given time into an LLM ecosystem.

So not just protecting our data, but making sure that things are structured in a way that our data creates more meaningful value for our customers, whether they're accessing that through our platforms or through our collaborations with the LLM providers. And I think that puts us at a pretty significant advantage going forward where we have that flexible delivery and that massive trove of truly proprietary owned intellectual property.

Great. Then I just want to touch a little bit more on some of the MCP Connector comment that you made. Anthropic recently announced a suite of solutions and S&P Global came up with the plug-in. The collaboration with Anthropic has been something we've been aware of for some time now. Can you expand on how the collaboration with these frontier AI labs have changed the adoption of your data? What feedback has been from those who have been using it thus far?

Yes. So it's -- I'll start by saying it's very early in a lot of these. A lot of our customers have a great deal of interest in exploring this new functionality, these new platforms, but particularly in highly complex and regulated industries, there are a lot of hoops that people have to go through just from a compliance and an infrastructure cybersecurity standpoint just to get access to some of these tools. But we do have quite a few customers that are actively using them right now, right?

We mentioned this at a prior conference, but we've got about 80 customers right now leveraging the MCP Connectors, and we're seeing strong usage there. I think we're getting very positive feedback from our customers. We're also getting very positive feedback from our collaborators, right, the LLM providers of the world as well, where they see us as truly collaborative, where it's not enough to just say the data is available, it has to be readily available. The MCP Connectors have to work, right? You have to have the data coming over in a way where it's trusted, it's truly grounded. It's -- the sources are citable. And so these ecosystems function very, very well with S&P Global data because of all of the work that we've done through Kensho and through other avenues to get that data in a place where it's truly ingestible and functions well in these ecosystems.

When we look at the Energy business, where we've had the Copilot -- Microsoft Copilot integration a little bit longer. We launched that in April of last year. We've got 60 customers that are leveraging that. And we've seen revenue growth in those customers at twice the rate of the average energy customer, and we've seen retention rates 4 percentage points higher with those customers. So we know that when we make this data or our proprietary content available to our customers through these ecosystems, they get more value out of it, right? We're seeing that in the usage. We're seeing that in the feedback we get from customers. It's probably too early to really say how this plays out in the long run, but I think the early indicators that we're getting from customers are very positive.

Awesome. And then let's switch a little bit to the profitability component. Within the AI debate for infra services companies, investors are focused on the potential for profitability improvements related to labor, process and tech expenses. It's clear that AI is a powerful cost containment engine for S&P right now, and management has cited specific opportunities within the enterprise data office and software development over the next few years. Looking ahead, when do you think we hit the inflection point where net new AI product revenue overtakes cost savings as a driver for earnings growth?

Yes. I think that's a great question. I would start by saying I'm not sure that it does, right? When you look at the opportunities for AI-driven productivity, when we have roughly 2/3 of our cost base is people related, and we have huge populations of people that we can, by leveraging AI functionality, make these people significantly more productive, help them get engaged in higher order work, right, more fulfilling work, not only does that improve just the quality of life for our people, but it improves the productivity and efficiency of the company. So we did mention the enterprise data office. We actually expect to reduce expenses in the enterprise data office by about 20% by the end of next year through the application of -- partially that's through the application of AI tools, but also through just general spans and layers analysis and productivity work that we expect to do there, right?

But I do think that the opportunities span both sides of the P&L, right? As we leverage more AI functionality within our products, we think our competitive position improves, retention rates improve, pricing power improves, as we leverage more of our data through LLM providers like Quad for Financial Services or GPTs or others, those are opportunities for us to expand the addressable market, really allow our data to be consumable by customers that may not have been interested in some of the other products that we have, right? There are -- we know there are segments of the market where a full-blown Cap IQ license is going to be overkill for those individuals, but leveraging some of our content through Quad for Financial Services or OpenAI solutions or Microsoft Copilot, right, that may be a very attractive entry point for some of those customers. So we think this ultimately does expand our addressable market.

And so the revenue opportunities are there for sure. The expense opportunities are, too. I'm a little wary of some of the numbers that we've seen thrown around in the market, too, just because we know internally, there's a lot of judgment and flexibility around what you define as AI-related revenue, right? We have AI functionality in Cap IQ. That doesn't necessarily mean that 100% of Cap IQ revenue should be AI revenue. We have AI functionality in iLEVEL, right, in a lot of our tools and products across the ecosystem, right?

And so the idea of assigning the AI label to revenue streams, I think, is something that we're taking a very, very strict and prudent approach to. But on the expense side, it's pretty clear, right? It's very easy to see where we -- when we deploy standardized AI-developed tools, where we're able to pull millions of dollars of expense out of our software development community just by standardizing on tools, right? That's something we did in the back half of last year. It's a lot easier to acknowledge and very clearly allocate those cost savings to some of the AI functionality that we've embedded. So in the long run, I think you're going to see benefits on both sides of the P&L. Which side winds up being the bigger benefit, I think only time will tell.

Okay. And then there are debates on whether AI efficiency gains stick around or eventually get competed away. How confident is the team that AI-driven savings will drop to the bottom line for shareholders rather than being passed back to clients?

Yes. I think the areas where we're looking are really on margin expansion and then opportunity for reinvestment in product development and growth. And you can point to some of these very important brands and products that we operate. You look at the Ratings business, you look at the Index business, where we have incredible value that we create for our customers, but we also have very high margins in those businesses and very high incremental margins in those businesses.

So when we look at this, our view is improving the productivity and efficiency of our people, improving the productivity and efficiency of our workflows, our product development, our internal processes, that doesn't change how much value we're creating for our customers. When we price our products and services, it's always based on how much value we're creating for the customer. So in an ecosystem where it's easier for us to deliver that value, it doesn't necessarily change the value we're delivering. And so you've seen that materialize in the margin expansion over the last several decades within our Ratings business, within our Index business as well, where we've become more productive, more efficient, but you've also continued to see pricing and margin expansion in those businesses continue to flourish as well.

Awesome. Now shifting gears, going back to Investor Day, there was an overarching theme that advancing essential intelligence with a focus on expanding into high-growth adjacencies. Looking at the portfolio pending the Mobility spin-off, which specific verticals, whether it be private credit, energy transition, alternative data or anything else, do you see the most needle moving to help sustain your 7% to 9% medium-term organic growth?

Yes. I think that's an important question, too, Wahid. When we look across the portfolio of businesses that we have, right, in the 4 divisions that we're focused on post Mobility: Ratings, Market Intelligence, Energy division and Indices, the majority of our growth is likely always to come -- most likely to come from these major franchises that we have that continue to grow, continue to have significant runway for growth for several years, right?

The Ratings business will continue to grow very well. The Index business, we expect to grow 10% to 12% on average over the next 3 to 5 years. And these are huge global franchises with immense value, both to our customers, but also to the markets at large. And you look at something like the S&P 500 that has $13 trillion of AUM indexed to it and another $7 trillion of AUM benchmarked against it at the end of 2024, right? Like that's just the S&P 500.

And so when we look at the strategic initiatives that we have, there are incredibly attractive opportunities for growth, but just the sheer quantum of business that we're running through these major franchises means they will likely be the biggest driver of growth going forward. But when we look at private markets, we think there are incredible opportunities in private markets. We think we have arguably the most holistic set of solutions for the private markets in the world.

You look at energy expansion, where we have a leading global franchise and really anything that touches the energy industry, including the world's premier energy conference that will take place in Texas in just a few weeks, CERAWeek, right? We have these incredible opportunities in things like supply chain and decentralized finance and very high growth but nascent opportunities for us. We think all of those are incredibly attractive. And different ones will grow at different rates at different times, but we think all of those in the long run should be accretive to our overall growth rate.

Okay. Just switching to different segments here. In MI, you saw a medium-term outlook of 6% to 8% OCC growth. We've seen some scrutiny on financial services headcount and budgets. What is driving the durability of MI subscription growth despite broader Wall Street cost considerations?

Yes. I think a big part of this and a lot of credit, frankly, goes to Sally Moore and her team and the Chief Client Office as well as Saugata Saha and his team in Market Intelligence for just the execution that we've seen over the last year, 1.5 years, where we've been able to elevate the conversation with a lot of our customers outside of just the procurement office and really have much more broad, holistic strategic conversations with these customers. We hear over and over and over from these customers that they want to do more from us -- or more with us. They want to get more from us, and they want our help actually displacing some of these point solutions in the ecosystem because vendor consolidation at these customers is a very real thing, right? We've seen that trend over the last couple of years. That trend likely continues for several more years.

And our largest customers because of the strategic focus on both the Chief Client Office and the revenue transformation that we've talked about in Market Intelligence, really aligning with long-term strategic goals at these customers makes it easier for us to go in and help them understand just what it is that we bring to the table across the entire portfolio of products that we offer. And when our customers actually see what we could be doing with them, it's very clear that there's a huge opportunity.

So we are confident that the growth drivers that we pointed to at Investor Day absolutely exist, but the growth rate that we talked about at Investor Day on average over the next 3 to 5 years, we admitted very clearly at Investor Day that, that assumes some market share gains, right? And we expect that to continue. A lot of that is because these customers see what we can do as we engage more deeply with them, not just with their commercial and strategic teams, but even with their technology people, right?

You saw us launch Kensho Labs at our Investor Day last year, where we can actually leverage the incredible expertise that sits within Kensho and let these professionals work directly with customers to help co-develop solutions that leverage S&P Global's data and workflow tools and solutions in ways that solve some of the most sophisticated and challenging product problems for these customers, they want more of that, right? And because S&P Global just has such an incredible portfolio of products and such a broad suite of solutions that we can bring to the table, it's much easier for customers to consolidate into S&P Global and allow us to kind of further those market share gains over time.

Great. We talked about private markets a bit and we talked about MI. I just want to combine those 2 with your most recent acquisition of With Intelligence. It bolstered your position in private markets, an area that's notoriously opaque. It captures a growing share of global capital. How are you integrating With Intelligence data sets to the existing iLEVEL and Cap IQ Pro ecosystem to help to create a seamless workflow and beyond just cross-selling data feeds, how does the combined portfolio position S&P to become the connective tissue between private market fundraising and capital deployment?

Yes. I love the way you phrased that question. I think we would agree this is traditionally a very opaque market that is in need of transparency. And I love that language around connective tissue, right? I think that's the strategy for us. It's not just about taking data from With Intelligence and putting it into the Cap IQ and calling it done, right? These are incredibly valuable data sets that are largely contributory and proprietary data sets to With Intelligence and by extension now to S&P Global, but we can leverage those data sets and combine them with private company data that we have tens of millions of entities through Entity Insights, leveraging the tools that we have through Kensho to create very, very interesting combined data sets that can really lead to transparency in those private markets.

With Intelligence is actually a great case study for a couple of reasons. One, as you mentioned, because it furthers our strategic initiative around private markets, but it's not going to benefit just Market Intelligence, right? Market Intelligence is where that business sits and where the revenue gets recognized. But as we look for ways to combine data and we look for ways to leverage the other ecosystem of partnerships that we have like Cambridge Associates and Mercer and other solutions and data that we have access to through tools like iLEVEL, we actually have opportunities to create some very differentiated benchmarks, right? And that can benefit the Index business, too.

So we're really looking at With intelligence, the way we would look at all of our data assets and the way we look at really every tool we have, which is how does it benefit the enterprise as a whole rather than focusing on just how does it benefit the P&L for one specific division. How do we create true holistic customer value, right? And I think With Intelligence is going to be a huge part of that strategy for us in private markets.

The other piece that I think is important with With Intelligence is it is an excellent case study in just how quickly we can move with data integration and data processing. We actually put a case study in our earnings deck in this most recent quarter. I think it was Slide 10 of the earnings deck. You can actually look at With Intelligence and see we took within 25 days, we had integrated 75% of the data from With Intelligence in the Cap IQ platform, right? That's incredibly fast.

People don't realize how challenging that is if we didn't have tools like Kensho Link and Kensho Extract, right, and Kensho Nerd and these incredible tools that allow us to manage this data in very sophisticated ways and rapidly deploy data in new ecosystems like Cap IQ Pro. So With Intelligence is, as I mentioned, it's a key part of the private market strategy, but it is also a great example of just what we can do with data because of the functionality and the tools that we have internally.

That's amazing to hear. Now I'll touch a bit more on private markets later on, but I just want to switch really quickly to Ratings. The medium-term expectation of 6% to 9% organic growth predicated on the mountain refinancing wall, growth in global debt, along with the need for transparency in nontraditional markets, such as private markets and emerging assets. For 2026, organic growth is a bit lag from 4% to 7%. Now we saw a massive pull forward in debt during 2024 and 2025 as issuers try to run -- front-run expected rate cuts. What are your assumptions for global refinancing wall and baseline volumes in 2026? And how conservative are expectations given tougher comps?

Yes. So this is something that we obviously pay very close attention to. When we look out over the last couple of years, you're right, we did see a very significant pull forward, particularly in 2024. 2025 was actually less, right? So there was still pull forward. There's some pull forward every year, but the elevated levels that we saw in 2024 really didn't get replicated in '25. '25 kind of came back down to normal. And -- but importantly, even with that pull forward in '24, we saw meaningful growth in 2025 because the size of the maturity walls are so much bigger.

And we've talked about this a little bit on the earnings call as well. The 2026 maturity wall is up something like 12% over where the '25 wall was last year. Over the next 3 years, that cumulative maturity that's going to be coming to market is 9% higher than it was at this point last year. So we know there are huge opportunities here. It's very difficult to time that refinancing activity. So that's why you see us take a position like we did with our financial guidance for 2026, that 4% to 7% revenue growth is really tied to low to mid-single-digit growth in billed issuance for us, which the assumptions underlying that are really important.

So we're really only looking at modest pull forward out of the '27 maturity walls, very little, if any, out of the 2028 maturity wall, right? We're looking at modest growth in M&A activity. We're looking at the hyperscaler CapEx environment, which is certainly top of mind for a lot of folks. We've got about $650 billion of announced CapEx from the hyperscalers for 2026. That's up significantly over what we saw from them in 2025. Our guidance assumes only modest growth in data center and CapEx-related debt financing. And so if we do see a meaningful portion of that $650 billion coming to the market and that's financed by debt, we've said that would drive a couple of percentage points of upside to our build issuance forecast for 2026. So we want to make sure that we're taking a prudent approach to how we view the year when we're this early. And as we've said before, our tendency is to refine that guidance as we progress through the year and we get more data available.

Great. And then just switching to private credit ratings. How do you view the long-term economics and margins of covering private credit compared to traditional public credit? And how will it impact the division's growth trajectory?

Yes. I think in the very long term, you're going to see us fairly ambivalent as to whether the debt is issued in the public markets or the private markets. I think our opportunity to rate that debt is very strong in both of those situations, particularly the type of debt that we ordinarily rate. We're not going to rate everything in the private markets. We haven't. We don't necessarily want to rate everything in the private markets. But what we do rate in the private markets, we leverage the exact same methodologies, the same risk factors, the same criteria and the same economics. So the pricing is the same in the private markets.

And I think that's a really important dynamic for us because as we see the public and private markets become more fluid with each other, where we see refinancing activity going from private to public or public to private over time, the fact that our methodologies are the same means that our rating can travel, right? If somebody issues debt in the private markets and wants to take advantage of a dislocation in spreads or take advantage of favorable market conditions and refinance that debt in the public markets, if we've rated that debt in the private markets, they can very comfortably do that because it's the same methodology that we're going to use to rate that debt in the public markets. And so the perceived risk associated with that debt doesn't necessarily change, right?

So I think that's a very, very important point for us that when somebody sees a rating from S&P Global, right, our customers count on us because they know they can, right? They know that the methodologies are sound, the discipline that we have when we create these methodologies and how rigorous we are in analyzing any potential change to these methodologies, that's critical for the entire debt ecosystem. The fact that we don't employ different methodologies public to private is a big part of why issuers, fixed income investors, really the entire market ecosystem views S&P Global so favorably as part of that global market.

Got it. And then before we end our conversation, at our conference this year, we're asking companies that present to do a quick word association. So tell me the first thing that comes to your mind when I say the following.

All right. So just so everybody knows, he did not give me these in advance.

So the first one would be [ data mode ].

Huge.

Okay. Issuance.

Strong.

Capital allocation.

Disciplined.

And the last one, which I'm just thinking of right now since you're here, Martina.

Brilliant.

Okay. Awesome. So I'll pause there, and I'll field some questions from the floor. I guess I asked some good questions, but I didn't address anything.

No, I think you've done a fantastic job.

I'll throw a question. I didn't talk about the Indices division. It has delivered double-digit growth over the past 2 years, led by growth in equity markets and the medium-term guide exceeds the overall company guide. Beyond pure market appreciation, what is driving the core net inflows into products linked to your indices? How much runway is left in the secular shift from active to passive management? And how does a broadening of performance in the U.S. equity markets impact S&P?

Yes, great question. I think the index franchise that we've built is one of the most beautiful businesses I've ever seen in my career. I absolutely love that business, really because the interests of our business are tied so intrinsically to the interests of our customers, right? They're very tightly aligned. When they do well, we do well, right? When they struggle, we struggle along with them. And so the market appreciation certainly matters, but we've built global franchises in this Index business that really have facilitated some of the most liquid ecosystems in the world.

And when you look at the S&P 500, for example, it's not just that it's an intuitive index, it's not just that you have the calculation engine on our side and you've got incredible reliability and the brand awareness is there, right, but the fact that it's the definition of the U.S. equities market, right? And investors know that they can get in, they can move out. They have that liquidity in that ecosystem, frankly, because of some of the partners that we have, right, and some of the incredible customers that have built phenomenal products on top of our intellectual property, it's really created this fantastic ecosystem in the U.S. equities piece of it.

And then we have opportunities to expand beyond that, right? You've seen us talk about commodities indices. You've seen us talk about fixed income and cross-asset, right? We're in a very unique position at S&P Global, where S&P Dow Jones Indices is really the only organization in the world that has a top global franchise in equities and a leading global franchise in fixed income, and we've got great commodities indices. So we can pursue opportunities with our asset management partners and with asset owners to create new indices that can target things like target date opportunities, right, target opportunities. We can look at leveraging cross-asset indices to an extent and a scale that very few in the world could do. And so that really is a fantastic franchise. I think we're very, very fortunate to have Cathy Clay coming in and leading that organization for us. She's a fantastic leader and an incredible operator of visionary strategists. So I think we've got a lot of confidence in the growth rates that we put out there at Investor Day.

That's great. I think that's all the time we have. But Mark, I appreciate the time. Thank you for coming. Thank you all for joining in.

Thank you, Wahid.

I'm Patrick O'Shaughnessy, the capital markets technology analyst here at Raymond James. And up next, we have S&P Global. And on their behalf, we have CEO, Martina Cheung; and CFO, Eric Aboaf. Thank you guys very much for joining us today.

Thank you.

So to kick it off, and as you might expect, I have several questions that pertain to AI to get us started. I think almost everybody would agree that your benchmark businesses, S&P Ratings, S&P Dow Jones Indices, Platts, they're not really at risk definitionally from competitive disruption. But I do think a very active debate currently does exist around some of your workflow tools with some argument that AI can cheaply replicate those tools that sit on top of client data or nonproprietary third-party data. How do you respond to those concerns as they would apply to S&P solutions?

Yes. Thanks, Patrick, and it's great to be here. As you said, we have an incredible breadth and depth of our proprietary content, whether it's benchmarks, unique IP and workflows. And if you take just the benchmark businesses that we have, so index, ratings, our price assessments and you add in the revenue that we get from the redistribution of our Ratings IP that's in Market Intelligence, just that alone makes up about 3/4 of our operating income at S&P Global. So really the vast majority of what we do very, very tied to these areas.

In terms of the workflows that we have, and we mentioned during IR Day that about 13% of our revenue comes from these workflows and many of them are incredibly sticky and very unique and perform critical tasks for our customers. I would differentiate what we do in a couple of different ways. So the first I would say is when we're actually running these workflows, many of them are what we would characterize as enterprise-grade critical systems of record.

So think WSO, Debtdomain, ClearPar, iLEVEL, Cap IQ Pro, Platts Connect, et cetera, these services in many ways are actually moving our clients' decision-making. Oftentimes, they're actually facilitating the flow of capital and supporting critical decision-making on asset allocation, for example. And so we also see that many of these workflows are actually, I would say, in many ways, performing regulatory tasks for our customers. So for example, we will -- as part of some of our managed services contracts, we will also make sure that our customers are in a position to comply with very complex regulations like the DORA regulation in Europe, for example. And so I think that's the way to sort of think about these particular platforms.

We also have a couple of things that are quite unique amongst these platforms. The first is that many of them are part of ecosystem. So they're not just supporting one client and one client's systems. They're also supporting an entire industry sector, think WSO, for example, or iLEVEL. And many times, you can't really realize the full benefit of the actual product without our unique data that comes with it. Sometimes that data is generated by the flow of work in the product. And other times, it is the data that actually triggers the value of the product for our customers. So think loan reference data in WSO.

And so these things are, I think, a little bit -- we'll put it this way, not all software is the same in terms of the level of criticality that it represents for our customers. And when I think about what our customers are telling us because at the end of the day, that is the best barometer for the need and demand and value that these products will create over a period of time. They're essentially saying, "Look, we want fewer vendors, not more." They're saying that our unique IP is incredibly important to them, including the software that we run as part of that value proposition. And they're asking us to co-create with them in the case of our larger clients with Kensho, for example, to create additional value.

And you know that we've been integrating generative AI across these platforms, including using generative AI ourselves. And so we have a very informed view around how we can continue to create value for our customers through that. So maybe just as -- we'll throw that out as a starting point. I know you have a lot more questions on AI.

Yes. I think at the same time as, okay, your workflow tools, they're more moated than people might expect. But you also have argued in the past that you think AI will only increase the value of your proprietary data. What are some of the early examples of that playing out?

Yes. Well, we're very excited about it. And I would say that we've seen this play out in a few different areas. So think about perhaps the ways in which we've deployed the actual capabilities ourselves. So we've been in the market now for around about a year with Claude for Financial Services. If you remember, last year, we were one of the first to announce our MCP Connector in Claude for Financial Services. We also were very early in the market, again, around about a year ago with providing our energy content through Microsoft Copilot. So between those 2, we see about -- we have about 140 customers between those 2. Around 80 of them are actively using the MCP Connector, largely Market Intelligence. And we've got a chunk of those who are either paying for it, some of them who are on pilot time lines and actually converting to paying as well. So about 80 customers using our MCP connector, largely MI.

And then with the Energy division, where we were very early in the partnership with Microsoft Copilot, we have around 60 customers who are using Microsoft Copilot and have paid to use our content in Microsoft Copilot as an add-on. And so this begins to give you a sense for the value that we're generating for our customers by actually providing these different channels.

When we talk about the value of our data, every time our customers use these products, whether it is a partner product or it is our product specifically like a Document Intelligence or a ChatAI on Platts Connect, they're essentially pulling in more of the data that they're licensed to every time they use it. We track all that telemetry because the usage of our content, the frequency and the volume and coverage of usage, that all forms part of the conversation around value creation for the customer when we're renegotiating.

And it also gives us an opportunity to position new data. So our CCO was really the tip of the spear with some of our more sophisticated clients who recognize that they can actually scale these capabilities to use more data and get more signals, get more real-time insights and we're having a lot of conversations with them around new potential data sales as well.

The other point that I would make is I made the point earlier that we're making our products smarter and integrating generative AI into our own solutions. And we know that clients are willing to pay for that as well. We mentioned during Investor Day that almost 20% of our clients have signed up for automated data ingestion and iLEVEL. That is an additional entitlement that they're paying for. So again, speaks to the value that we have here.

And then maybe one other point that I would make is if you look at the Energy customers who have signed up for receiving our Energy content through Microsoft Copilot, the growth rate for ARR for those customers is about 2x the rest of our Energy base. And the retention for those customers is about 4% better than the rest of our Energy bases. So we're really seeing a lot of value in the beginnings of it, particularly where we have about a year now of experience with customers going through these channels and using our content more and more.

As your content gets distributed through LLMs like Claude Anthropic, like you mentioned, how confident are you that you're going to be able to defend your intellectual property indefinitely?

Patrick, let me take that because it's an area that we've always worked on, right? We've had proprietary data and benchmarks and price assessments and so forth for decades and decades. And so this is just a new area to expand our capabilities. First, I'd remind you and everyone that our relationships are intrinsically with the client, the asset manager, the bank, the corporate, the energy company. We have a direct relationship with them in terms of what's the data that they're procuring from us, what platform are they using, what are the reuse rights, what are the pricing schedules and so on and so forth. That's a bilateral relationship. And that one is one that we retain under all circumstances.

When a client goes and says, look, we're going to start to take advantage of some of the feature functionality, the AI feature functionality that Martina described within our ecosystem, then they continue with those relationships. When -- in addition, they may go to one of the vertical AI providers or one of the LLMs, right, those end users need to actually -- before they can access S&P data, actually get us to turn on, right, so basically permission them. And that's done through the MCP Connector, through the grounding agent and so forth. So there's a whole set of technical tools for commissioning, accessing and then for us to monitor, right, the volume of data, what they're using, how they're using it, who's using it on the other side. And in fact, that's actually the core protective feature.

Finally, we -- our data is for our clients to use sometimes directly with us, sometimes with the LLM. Our data is not available for training, right? That's not the purpose of our data. Our data is there as a proprietary data set that clients can use for their purposes. Training is at a different place. Training is done by the LLMs, and that's up to them. But we're not going to let the unknown behind our paywall.

And I would maybe add that, obviously, we have clients whose appetite for data has been increasing. And the combination of our capabilities, whether it's the MCP Connector, our grounding agent and our AI-ready data, we actually have the ability to essentially throttle the number of rows that actually cross over between our databases and that show up in the clients' queries. And so in other words, if you're querying multiple of our data sets, you don't get the whole data set back, right? You get -- our data continues to sit on our servers and you get through the grounding agent just the data needed to answer the query that you're getting. And so that throttling really helps with the IP protection as well.

And then going back to your November Investor Day presentation, there was a slide that kind of categorized your different revenue buckets. And there was a top bar that said like less than 5% of your revenues was undifferentiated nonproprietary data. And yet it's not all that material. But I'm just curious like how do you go about protecting even that sort of content?

Yes. I mean, look, this is sort of table stakes expected as part of the customer experience. And so our customers really do just expect to get that. We don't charge separately for it. I mean I'm not aware of any customer that pays separately for any of these more commoditized data sets. And so essentially, they're priced as part of the enterprise license. The only point I would make in addition to that is we did say that we'd expect the 95% to grow over time relative to the rest. And so over time, as a proportion, you'd see that 5% decrease.

Very helpful. And then another angle to the discussion is the impact that AI can potentially have on your profit margins. I think the bear case is that maybe new competition is going to force increased investment. The bull case is that AI structurally improves your incremental margin profile of many businesses. How do you think it all nets out?

In our minds, and we described this at Investor Day, this is a net positive for us in a number of ways. First, you've seen us invest early in AI. So this is not new, right? We bought Kensho back in 2018 and have been systematically building out their capability. And what's important, we have always been in the AI ecosystem, which is what makes our partnerships with Microsoft Copilot or OpenAI or Anthropic natural for us to secure and to secure it in in-depth ways.

Secondly, we've been rolling out AI area by area and not just from like a generalized usage perspective because that's not enough, right? What we've done is gone deep. And so we've tackled 4 or 5 areas where there are large swaths of activity and staff in our ecosystem and said, "How do you do those fundamentally differently?" A good example that we shared at the last earnings was around our Enterprise Data Office, or EDO, covers about 9,000 of our 40,000 people. It's about $0.5 billion of expense spend on a $7.5 billion base. And we see by the end of 2027, a 20% save in expenses there. From what, it's really a combination of end-to-end process reengineering, right? Because for 9,000 folks, it's not about giving them an LLM. It's actually dividing up what their processes, subprocesses are and so forth, thinking about how to simplify, standardize, tool them differently. We've been doing that for years with a set of analytic models and machine learning models and neural networks.

And now we have a new set of large language models that we can leverage as well. And so that's an example. But that's one of several examples, probably one that's furthest along, but we're taking -- we're working with our software developers. It's another pool of about 7,000 staff. And in truth, you've all seen the benefits you can get from software coding. We're already at benefits of 10% plus in terms of productivity. But we see ways to double, triple that amount of productivity just as we think about what a scrum team looks like, how agents can factor into that and be part of that team, how the teams don't need to be the same size, how the software development life cycle actually becomes integrated with the product development life cycle and so on and so forth.

So there are areas that we are just marching across the company on to really think about how do we transform the way we work. And it's a mix of new tools and end-to-end process for engineering. There's researchers, there's analysts, there's a sales operations. There's area after area, which, in our mind, easily comprise about half of our staff. And you think about comp and benefits, it's closer to 2/3 of our cost base, right, out of $7.5 billion. That means there's a $5 billion pool of expenses that we can tackle and think about how do we systematically change and transform and make more efficient and more effective at the same time.

I think that's why, in effect, we were very clear at Investor Day, and we're happy to reaffirm, but we see it that we can comfortably deliver on the 50 to 75 basis point margin expansion each year. And we think there's even more upside in years of cyclical outperformance. But that's because we have these programs in place. We see the next 3 or 4 programs in front of us, and they cover so much of our staff in really significant ways. And so in a way that -- I think it's not just the bull or the bear case. The actual case is AI pays for itself. And it pays for itself multiple times over and delivers that margin expansion.

Now margin expansion doesn't come on a perfectly smooth line, right? So we had nice margin expansion in fourth quarter. First quarter, we expect margin expansion again, but it will vary. For example, in first quarter, we expect margin expansion of about 50 basis points, both in Ratings and in Market Intelligence. And then relatively muted margin expansion in some of the other divisions as we go through some seasonal patterns, productivity and investments. But we feel comfortable with margin expansion on a full year basis, 50 to 75 basis points, margin expansion in that range for every business because that's what we've been driving towards and those are the plans that are in place and are -- we already see coming through with action and results.

Very helpful. So with the Ratings business and kind of maybe wrapping up the discussion around AI, how do you see AI spend broadly in data center build-out, specifically have an impact on Ratings this year and beyond?

Yes, I can take maybe start, and Eric, you can add in as well. So it has been quite positive for us. I mean, particularly, we saw in Q4 some outsized issuance around the data center spend and some of the announcements from the hyperscalers around their intentions of CapEx. I think what's important for us is that we're in the market. We have very well-developed and robust methodologies, and we have deep expertise that we've developed over several years on this. And so we find ourselves to be quite well positioned, I would say, in terms of being able to rate the issuance when it comes.

The only point that I would make, and you know that we are always thoughtful about issuance. So we've seen about $700 billion worth of CapEx announced. The truth is we don't know how much of that will materialize in 2026, and we don't specifically know for a fact how much of that will actually be funded by debt in 2026 or under what structures. And so we are very prudent in terms of how we think about it. And I would say, over the medium term, having outsized growth in data center issuance does not -- is not required for us to develop our medium-term plan for Ratings.

I'd just add the data center hyperscale or project finance because it's a mix of investment grade and project finance. We'll have to see how it plays out. It's worth about 2 points of revenue growth for us in the Ratings business over the last year, but it could easily be 1 point, 2 points, 3 points, 4 points, just depending on how that market evolves, what we see. We've been prudent, as we said at earnings around describing our issuance activity. We're careful. And we really want to just see how it plays out. We just don't know if it's going to zigzag a little bit or not. And we'd rather see it come through, see it in first quarter than second quarter and then appropriately adjust our estimates if it's another strong year.

Eric, one of the things that I think we mentioned at IR Day on this one as well is that it is possible depending on how much of that CapEx comes to market that we could see build issuance improve in the kind of 2-ish, 3% range, depending again on how much of that CapEx comes to market that's debt funded.

A lot of upside.

And then sticking with Ratings, another current event is private credit markets are in the news. Just broadly speaking about private credit markets, where do you think we stand in terms of their evolution relative to the public markets and then S&P's ability to build out a franchise in the private market space?

I can start, and Eric, please chime in. So I think maybe start with Ratings, which I think is where you're going to -- your original question, and I can kind of expand around that. So we've obviously been working a lot, and you all have asked us many, many questions on private markets and how we think about that for Ratings. And it has been really a phenomenal growth driver for us, and we'd expect that to continue to grow.

It comes not just in the form of private credit, specifically where it originated around direct lending, but also, of course, in asset-backed financing, energy infrastructure, data center deals, alternative investment fund ratings and things of that nature. And so we see really a very, I would say, diversified business that has developed within Ratings. And as you know, we are very, very specific about using the same Ratings methodology, whether something gets rated in the public market or the private market. We've always viewed that as incredibly important. I would say that it is even more important as we see these very large issuances that could have a public piece and a private piece, for example, in the hyperscale area. And so that's been really important for us, and we'd expect that to continue.

I would say outside of Ratings, if you want to sort of like take a bigger step back, I mean, the health of the private credit and more broadly private market space is strong. And we saw about an 11% increase year-over-year in fundraising in 2025 versus 2024. One of the things that is very interesting to us about that increase is that we're seeing a bit of a rotation so that it's not as much U.S. But we're seeing quite a bit of interest in Europe and across Asia. And as a global player, we are very well positioned to take advantage of that. So just to give you a sense, almost 70% of the fundraising in 2025 went to Europe funds and multi-region funds.

And so this is where the strength of the global franchise that we have is very important, whether it comes to actually rating that debt or even working with sponsors and investors who want information around those funds in those markets. And this is where the acquisition of With Intelligence comes in as being incredibly valuable for how we serve the overall market with this as well. There's plenty that we will do there around generating those synergies based on that very unique set of content that -- With Intelligence brings to us on top of the great private company data, BigDough data and other data that we have also.

And perhaps the last point I would make is we do see an increasing opportunity around indices, whether it's public, private, private stock indices, private credit indices and we're continuing to innovate around that. You'll see us launch new products. You've seen that already. And the team is working very quickly already with the With Intelligence team to look at the data and see what they can launch there by way of new innovative indices also.