Workday Stock

Please welcome Investor Relations Vice President, Justin Furby.

Thank you. Thank you. I love that video. In fact, I was actually thinking we could just end it there and go right to Q&A, if you guys are okay with that. I've got a few laughs out of that.

Welcome to Rising. Welcome to Analyst Day. Really thrilled to have you guys make the trip out. We've got a great group here in Las Vegas, a great group on -- joining us on the webcast as well. So I appreciate all of you. I know there's a lot going on in the market and this week as well. So I really appreciate you making the trip out.

There's a lot of energy in this room. We're going to bring it up, though, as we go through the course of the day. We're going to show a lot of product. We've come a long way just in the last year. So excited to show you. And if you took in the innovation keynote this morning, you saw some of that. We'll show you a little bit more for you all and give you a look into what we've been working on over the last -- really, last year, but in the last 6 months, in particular, a lot of acceleration around innovation.

This is what we're going to expect today. It's going to be about 2 hours or so. We're going to go across most of the -- much of the leadership team and talk a lot about innovation and then how we're actually delivering it to customers and what that adoption cycle looks like. And I think as we go through the course of the day, and we'll close out with Rob, we'll talk about, and this is a question we get a lot, what does that journey look like in practical terms when a customer goes down that path with us.

So this is my obligatory safe harbor statement. During today's presentation, we will make certain forward-looking statements. Actual results could differ materially. Please see our latest Form 10-Q filed with the SEC for a discussion of key risk factors.

With that out of the way, it is my pleasure to invite on stage our Co-Founder, CEO and Chair, Aneel Bhusri.

I was just watching to see how you were doing. So good afternoon. Thanks for being here. It's great to see so many familiar faces. I hope you all saw the keynote today. And in the Q&A, you can ask any questions about that, that you'd like. What I'm especially excited to hear about, you're going to hear from all the product and technology leaders that are setting the pace for the new set of products. Zane has got a lot to cover as well, talk about the market opportunity, the strategy we're executing against. And hopefully, what you see is that there's a big bench of talent at Workday that's driving the company forward. And in many cases, new talent because it's a new era, it's a new time. And we've got largely a pretty fresh team driving us into the future.

I talked about the refounding moment in the keynote. Was there -- how many people were at the keynote? Everybody? Some people weren't. Okay. What were you doing? No kidding. I'm kidding. If it wasn't for AI, would I have come back to Workday? I don't actually know the answer to that question. I get asked that a lot. But once AI showed up, I felt like I needed to be back. And I had many discussions with my co-founder, Dave, about the future and what makes a great technology company, what lets a technology company pass the test of time as a company that people admire and that does good work for their customers. And it's winning across multiple technology generations.

So we were a clear leader in cloud. I was part of what happened with client server, but PeopleSoft didn't make it to cloud. Workday made it to cloud. And now Workday needs to lead in this next generation of AI, and that's a large part of why I came back. Also came back, which is about driving innovation, but also came back to make sure we're refocused on our customers, refocus on our employees. And so I'm 9 months in, so far, so good. This is not just another product cycle. This is something like none of us have seen, everybody wants to -- has all these hyperboles around what AI means. But I've been around long enough to know I've never seen a technology like this before. Simply put, it's trying to replace the human brain. No technology in the past has done that. It's all been around increasing levels of automation. And so do I know where this technology is going to go? No, but I do want to have a say in where Workday heads with this technology as it continues to evolve on almost a daily basis.

So just to remind you, I'm not going to go into detail. You've been covering Workday for a long time. We've been at AI and machine learning since 2013. One of the reasons in the founding principles of Workday is we thought data would be really valuable at some point down the road. We weren't sure how. It was before machine learning existed. But as soon as machine learning showed up in that '13 time period, I was actually on the board of Cloudera, one of the pioneers of Hadoop, and I saw what was the start of something really powerful and magical. We just kept investing along that trajectory. And today, those bets along the way paid off. We're still down to one data model.

One data model means we can aggregate all the data across all of our customers and train the models in ways that nobody can touch, not ADP, not SAP, not Oracle. They have their customers on multiple systems. And on the HR side, no one has the scale of employees that we have at 80 million to begin with. One security model. You don't have to adjust security going from version to version, which means when you're using AI, it only has to traverse that one security model for whatever application is using, one version of the system. Every customer on the same version. So when you come out with a new agent, you don't have to try to customize it between 6 different versions of legacy systems.

One agent works on all of our customer systems. And so that's where we are and lots of transactions, 20 years of trust, which is not something to underestimate, especially with so many new companies emerging. They don't have the data, they don't have the trust. They don't have the ability to actually drive the models the way we do. To get that trust with customers took a long time, but the way we translate it is into this universal master service agreement that lets us use our data in an aggregate way, anonymous way, but that lets us train the models in ways that no one else can do.

The other part of what we're doing is just understanding that AI is just very different. It's not about determinist -- it's not about an end-to-end business process. It's about probabilities and reasoning. And I said this in the keynote this morning, you can't get a payroll 90% right. You can't get a close 90% right. They have to be 100% right, 100% of the time. Reasoning can add an element that helps you move a process from step to step, but it can't replace that process. But when we can take what we know with our platform and tie it to AI, AI work starts getting done on behalf of people and business, and it can rely on those guardrails. So that really is our differentiation.

There are a lot of spaces where AI can just run amok. Maybe it's in the creative space where you're just creating new content, you're creating new images, but not in the HR and finance world. These spaces are highly regulated. They have permissions. In some places, in the U.K., you track religion. In the U.S., it's illegal to track religion. You can't have agents that are just running across your data without any insight into the rules and regulations that run their business. And when you get to the financial side, same thing. So those same security permissions, workflows and biz rules, these are what customers rely on.

And so that's what makes for lawful use of AI. And that lawful versus lawless distinction is really important to us. For those that were you in the audience, you saw the ad that we did with Peyton Manning on the lawful versus lawless. In the spaces of HR and finance and ERP, that really, really matters. And so there was that talk about SaaSpocalypse, which I never believed in, but now I think it's becoming clearer in our space that companies like ours, AI is an opportunity to leverage those business rules, leverage those guardrails and build AI on top of it, which for better or worse, means that SAP and Oracle are probably fine, too. They have deeply embedded business processes and functions. We'll see if they can build AI on top of it, but no one's going to rip out SAP manufacturing that I've ever talked to. I mean no one's ripped it out for 30 years. Why would they do it now?

I talked about the distinction about the deterministic rails. That payroll example is one I always come back to. What we need to do as a company and part of our refounding is this differentiation is take these deterministic rails. Every business process has a start and an end. Some business processes have 20 steps along the way. A lot of that work between those steps are very mundane. They could be automated. There's a human involved. Well, AI can actually move the process from step to step. And in some cases, just redefine that business process. And that's where Workday comes in, to take the strength of those deterministic applications and now come up with the agents that can move work across these different business processes.

The last part I talk about is operating with a start-up mindset. And coming back, you heard this in my keynote, if you were there, I didn't really have a guidepost of how do you do this when you've been gone for 3 years, a new technology emerges and you come back. So I watch a lot of Steve Jobs videos. And I've said this many times as much as he was a great product leader, he was an equally great management thinker and leader. And so his thing when he came back to Apple was to think about Apple as a start-up again, and that's what we've done. We've got the scale. We've got the security. We've got the platform, 11,500 customers, but we need to innovate like a start-up. And so we've organized that way in how we're running the company and how are we operating differently.

We're doubling down on what matters most, concentrating on AI, on our platforms. Our core apps are still important. But I'll just say talking to customers, that 100th feature in HR or finance is not as important to them as these new capabilities in AI. Having said that, we still have a lot of our development team still working on those features because we do have a backlog of things we need to work through for our customers. But it also means doing fewer things. When I came back, there were 50 agents. Now there are 20. 17 in production, 3 more to come down the road, focus on ones that really matter. That still sounds like a large number, but it's not when you look at the scale and breadth of our platform. And moving away from niche products, focusing on the ones that really matter. We are a leader in HR. We're a leader in finance. Let's work on agents that really leverage those capabilities and really help our customers at scale.

And we are moving much faster. Hopefully, you saw that today. A lot of that work got done in the last 9 months. I'm honestly blown away. I'm so proud of Gerrit and Joel and Yasmeen and Max and Gabe and Alet. What they've done in the last 9 months, I've never seen before. Even in the early days of Workday, we didn't innovate that quickly. Part of it is just this AI technology allows you to do that. Part of it is the mindset of the team. We are working at speeds I've never seen before, and it's starting to pay dividends. And you'll see that maybe not this year or -- I don't know when you'll see it, but it's going to start seeping into our business as well because these agents are truly very transformational for our customers, and they will generate a lot of revenues for us.

A couple of examples. Workday Decision Intelligence built that organically, concept to GA in 4 months. Singapore payroll using AI, localized in just 8 weeks. We thought that would have been before that, we thought it was a year project, and now it was done in 8 weeks, 10x faster than anything we've done before. So that speed really does matter. And I guess the other part, which I've mentioned a few times is we're making ownership much clearer. When you hear from our product team, Yasmeen owns Data Cloud, Alet owns Agent Factory, Joel is our Chief AI Officer, Gabe owns platform, Max owns apps -- applications. When I came back, it was very diffuse. AI was owned by all the application teams, APIs were owned by all the application teams. And frankly, we're moving too slowly. When something is being done by someone and is 10% of their time, it doesn't get done. When you're up against a start-up, they're devoting 100% of time and activity, we had to do the same thing. And so putting leaders close to the work, closer to the customers, making them accountable, that's what we've set out to do.

I'm going to quickly talk about the 5 ways to monetize Workday. I talked about the different opportunities. So I'm not going to spend a lot of time with this. If you were in the keynote, you saw the 5 use cases. So let's just turn into monetization. Agents. Obviously, we're going to sell agents on a Flex Credit basis. APIs. If you don't want to use our agents on the front end or you want to use something like Cowork. Cowork, by the way, Anthropic integrates into Sana. It doesn't even integrate directly to our base level APIs. It integrates through Sana. Workday Data Cloud is a way you want to do deep analytics off to the side and marry with a whole bunch of other data sets, we've got the Workday Data Cloud. Workday Extend AI, if you want to build your own custom applications, again, Flex Credit-based. And then, of course, we still have our core applications that we monetize.

So 5 different ways. It really does cover every use case. We're largely neutral on which ones you choose. Do we make more revenue on agents? Yes, but APIs are ones where we don't really have to have a sales and marketing cost, so that can be equally powerful. Workday Data Cloud, brand-new opportunity that we really didn't have in our business plan. Same with Extend AI. So this model of monetization, still new to Workday, but it's coming together in a really nice way, and customers are embracing it. We still have work to do on the Flex Credit front to make sure that they understand how that works.

In a few minutes, you're going to see them all in action. And with Agent Harness, which we announced this morning, we get you that same foundation, trusted foundation to every agent. Gabe will share that in more detail. On APIs, direct way to access and monetize agents. Customers won't always start inside Workday. They happen in another third-party application. That's okay. These APIs are purposely built -- purpose-built for AI. I talked about the data cloud. Extend AI, that used to be Extend Pro, as you know from our earnings reports, it's been one of the fastest-growing revenue streams we've had, and we're seeing customers build agents in a very short amount of time. They're incredibly powerful. And we're not going to build all the agents that run at Workday. We don't need to, but Extend AI lets us participate in the building of those new agents.

I do want to remind people that we're not stopping investing in the core applications. We are continuing to invest in those core applications. So you'll still see us adding new capabilities. There's new areas like financial consolidations that we probably need to do a better job of. So there are still business process applications. And any time we build a new business process application, it creates data that feeds the model. So we're not done with that area, but we have such good products in that area. Customers are more focused on the features around AI.

So there you have it, 5 ways to monetize Workday. Each one matters in its own. But together, they reinforce a very open platform take what we built with Workday and use AI to make it better. With that, I'd like Zane to join me on stage, and we'll get into all the financial questions you want to get into. So thank you.

All right. Good afternoon, everybody. It's good to see so many familiar faces out there. So Aneel, as CFO, I feel like I'm obligated to tell all of you as much as I know you like bigger numbers, bigger slides that this backdrop was repurposed from a meeting we had yesterday. So we're thrilled that you're here. This isn't all for you. This was actually intended initially for our exec symposium. And this room was 2 or 3x the size it is now, and we literally had hundreds and hundreds of CXOs listening to our story and talking about AI and looking to us to understand where we are with AI. So it was an exciting time. It's an exciting time to be here at Rising, 17,000 attendees in person, 14,000 virtually, I believe. So just a great time to be here.

It's fun. It's fun to be back. Yes, it's just an exciting time to be back building product. It feels like a kid in a candy store right now.

Right, right. And for those of you who missed, I know a number of you got in this morning. Obviously, you'll be able to have a chance to see the keynote, but we've got all the talent here to give you a private showing as well. So with that, Aneel, you've been talking about market size and market growth. And for those of you who were here last year, you saw that we had a slide up looked similar to this, except instead of $276 billion of TAM, it showed $188 billion. So we're very proud of the growth here that you can see both HCM and FINS TAM has grown nicely, both through innovation as well as just the market growth. So that's approximately $176 billion as we calculate it today.

And the area we're most excited about is the $100 billion opportunity for us under AI and platform. And for those of you who were here earlier, you saw the power of Sana, you saw the power of Workday Cloud and our agent-ready tools that are really driving that $100 billion of opportunity, which is more than 2x what it was just last year. And what this doesn't include are some of the interesting things that we're now getting into, notably ITSM and of course, a big announcement for those of you who missed it earlier today with C1. So I thought this is maybe a good opportunity, Aneel, to talk about the C1 opportunity and how you've been thinking about identity?

Yes. I'd first start by saying I've been back for 9 months. I've talked to a number of customers. When you look at that AI and platform circle, they are looking to us first. I'm not one to exaggerate. I think most of you have known me for a long time. Our window is not forever, but we have a window 12 to 18 months where if we deliver our agents, we're going to be the default choice for our customers. They trust us. We already have their data. No start-up has the data we have access to. They believe in the guardrails we have, and they want us to help them make their businesses better. So we have this window where I have yet to meet a customer who doesn't say, we're looking to you for the agents, please deliver. So I just think that, that $100 billion opportunity is -- it's ours for the taking.

I'll just say like Data Cloud, I don't really have that forecast into our business. And I think Data Cloud could be a huge new revenue accelerator. So getting to identity. I've been talking about identity for a long time. I was one of the founding investors in Okta. I love that space. And I think there's a nuance that's lost on the market. HR systems are the source of identity. We have massive share in the HR space. Not saying I would do this, but if we turned off access to Okta to our HR system, they'd be in a lot of trouble, which just tells you we are at the front end, we're upstream of all the identity systems. It's a very fragmented industry. So HR is the source of identity. Now we're providing all the governance around it for not just humans, but for agents.

We can work with other IDPs whether it's Microsoft or Okta, but we now have that agentic layer that manages human and agent governance around all the things that are going to happen in the world of AI. It's incredibly powerful. It's going to take a while for the market to realize. It's going to take us a little bit of time to ramp up the sales. But I can tell you, it's going to be very disruptive to the identity space. And we're now in the security space in a place that we have a right to win. So I'm very bullish, and you guys have all seen all the reports about agentic identity and security. Well, we're now front and center in the middle of all of it. And C1 is a very special company. So you'll learn more about that over time.

That's right. That's great. And as we align with the growth and opportunity for AI, you can see the improvements that we've seen in this category on a year-over-year basis. We mentioned on our second quarter earnings call that we're approaching $600 million in annual recurring revenue with our AI agents and our AI portfolio, which is up significantly over 3x what we shared with you just this time last year. So while it's still early days, really tremendous growth in this area. And it's not just the breadth of agents. And again, those of you who saw the keynote this morning, you can see we have a number of very exciting opportunities and agents that we're building, but it's also the depth.

And if you look at areas like Sana, Extend AI, HiredScore and Paradox, they're all growing nicely. Three of them are over $100 million, and Sana is approaching that number very quickly. So we're very excited by that opportunity and obviously, the growth in our agent capabilities. As of the second quarter, we had 300 customers that had signed up for Flex Credits (sic) [ 200 ]. But as Gerrit will talk about, we have over 5,500 that are using a number of our organic agents already. So it's really getting that flywheel started. Rob is also going to talk about the opportunity on a customer basis and how you see that flywheel build up with an average customer. So we're excited by that opportunity in aggregate.

Now when we break that down and we look at our customer base, we've been focused on the dynamic with the customer base. And obviously, this, as you all know, represents 60% of our trailing 12-month subscription revenue. So we see this as a tremendous opportunity to leverage AI. And if you look at that opportunity just over the last year, it was the second quarter where we saw AI become just over 50% of that mix between core and AI. So 50% in the second quarter. We expect to end the year with more AI going into the customer base than just the basic core. And then as we look to next year, we estimate roughly 70% of that selling motion will be AI-driven and that revenue will be AI-driven. So it's tremendous growth.

Aneel, maybe just touch on some of the customers that you're talking to this week and how they're leaning in on the AI story.

Well, so just last week, I talked to Julie Sweet at Accenture. They're rolling out the Self-Service Agent to 400,000 employees, right? And that application is based on Flex Credits. You can just think about that Self-Service Agent Joel talks about as employee concierge. It's probably 30% of what it's going to be in a year, but it's already an incredible application. And I think it's the first killer application. And I suspect many of our customers are going to deploy BMO is the other one, and they're well along the path and very happy.

The customers are also very excited about the developer agent. They want to build their own agents, so are the service partners, by the way. I wouldn't ignore them in terms of talking to the service partners, the ability to build custom agents that they can resell to a whole bunch of their customers are really powerful. Then we have all the functional agents. But I mean, across the board, a huge amount of interest in every conversation I have with the customer starts around AI and our agents.

Right. And it's really that flywheel effect. If you look over the trailing 12 months, we had just under 900 customers that purchased at least one agent and the uplift we got from that subset of customers was roughly 12%. And you're going to hear from Rob where the idea is to get those agents out with those customers, and you'll see how that can ramp significantly higher than the 12%. So it's still early days. We're starting to see appreciable improvement and increases, and we're excited about what's still to come with the existing customer base, which highlights the other part of the opportunity, 40% of our opportunity is still around net new and how we're growing both internationally and how we're leaning in, in particular, around the medium enterprise space.

Rob is going to talk a lot more about our initiatives there, and you've heard of Workday GO and really how we think about not only selling AI into those opportunities, but leveraging AI, you talked about around the world as far as looking at Singapore payroll and all of the initiatives we have to localize our product and accelerate that road map. But there's also the time to completion, the time to execute and the time to get those products out there. So it's an exciting time with medium enterprise. We've got a lot of initiatives, and we do believe that, that's a key part of our growth with net new opportunities going forward. So again, a nice mix there.

Yes. And in the medium enterprise, a lot of the international market is medium enterprise. I happened to be in Europe 2 weeks ago, met with both large- and medium-sized companies. I was kind of surprised how far their thinking is on AI. I thought maybe they're going to be a little slower. They were -- Europe, in general, was slower on cloud. They're not slower on AI. They're embracing AI in the same way, and I think is really exciting.

Yes, and a great opportunity for us. We've actually, as you know, seen good success on our international markets over the last number of quarters. So we expect that to continue. And then the focus ourselves, Aneel talked about a start-up mentality and culture. And when we think about investing in growth earlier this year, we talked about really understanding what that opportunity set is. And today is going to be more about the product set. So we're eager to hand over to Gerrit and his team to talk about those products and get you excited about those products. But it's everything from rethinking how we deploy and how we engineer those products to the go-to-market side. Rob is going to talk about how we use AI and leveraging AI in our go-to-market capabilities, but also thinking about the whole adoption, whether it's forward deployed engineers and how we lean in with our customers. It's really around how they adopt. And that's what they want to know and what to learn from us.

So when I think about what we're doing in AI, we have to be customer #0. We have to be the best user of our technology, and we have IT and what we call BT at Workday, a leader, Rani, who is totally embracing that. And so when I look going forward, there are a couple of things that come to mind. I don't personally think about running the business for margin. I think about running it for growth. But if we run the business the right way, the margin should and will get better over time for multiple reasons. We get back to start-up mode, we have to reduce layers. We just did a -- reduction was painful, but 2.5% of the company, I promise you it wasn't for cost cutting. It was purely the fact that in some places in the R&D organization, there were 10 layers between me and someone actually building code or writing code.

That's not how you move quickly. They were -- those individuals were complaining about how long it took for them to get anything approved. So we slashed a lot of those layers to get back to that start-up mindset. So not about cost, but about speed, about ownership, about moving quickly. If we are a good user of our tools and other tools that are AI-based, naturally, we're going to get benefit for margin. And so we're going to set pretty aggressive margin targets to drive us to use these AI tools. And I mean, we have to eat our own dog food or we shouldn't be selling these products to customers. And so far, the early results are very positive. But we're looking at the products across all of our software providers and how we can use them to use AI to drive margin. It may not be in terms of more reductions in force, maybe there are. But I think it's -- I think there's also the opportunity to just not hire in areas they were hiring in the past and just leverage AI instead.

And we've been doing that through the course of the year with headcount. Aneel mentioned earlier in the year, our intention was to keep headcount relatively flat. Again, we want to be very thoughtful in where we invest and how we invest as well as a company-wide thorough review on how we think about people, process and systems, all working together to just get better at what we do. So a lot of opportunity there. And then our last slide before we hand it over is, of course, around the framework.

Now much of this, we talked about it in the last earnings call, so it may be a little anticlimactic for some of you in the room. But we're obviously holding to our guide this year. We mentioned on the call that we expect to have 11% in subscription revenue growth into FY '28. We still believe there's some upside there. I mean, Aneel, if you want to touch on some of what you're seeing through the course of the week, but I think we've mentioned that a lot of this is about adoption and how customers are embracing the technology. And that's where we see with the proliferation of agents that we're building that there is some potential for upside into FY '28 and beyond.

I'm hugely bullish and optimistic on what we're doing on the agentic front. Just before this meeting, I met with 4 different customers, and what they're frankly worried about is the token cost tied to those agents who tells me they want to use the agents, and we have to get smart in how we work with them to make sure that the costs don't run away from them. But that's a good problem to have because I think we can -- that's a better problem to have than they don't want to use our agents. They want our agents. And in some cases, they badly want our agents.

So I'm very optimistic on that. It's hard to figure out what that looks like in a year, I know it's going to be great. Where along the curve does it happen? I don't know. But then I look at the new areas around identity. I look at the new areas around ITSM, and those are all, to me, upsides in the model. But AI, I think we're in the process of catching a tiger by the tail. Hard to figure out when these agents, we've got 17 agents. They are all young agents. When will they actually take off? But when they take off, they're going to be huge.

Agreed. As we talked about through this conversation, and we mentioned already, we've obviously focused on non-GAAP operating margin and expect that to be greater than 33%. But as important to us is SBC as a percent of revenue. You continue to see the decline. We expect next year to be roughly 15%, but it is something that we're focused on and expect that number to decline even beyond FY '28. So we'll start talking more about non-GAAP operating margin, including SBC, and you can see nice growth here and expecting over 17% next year with that important metric. We know it's one that you all follow closely as well.

And with that, we're also focused on how we deploy and how we think about capital allocation. It was just this time last year when we announced a $5 billion buyback. I was thrilled to see that happen sooner than expected. Market conditions obviously helped in that regard. But we also have $4 billion authorized for an open-ended buyback as well. So excited about how we're balancing that. And then the last line item here, I know is very important to all of you, and that's free cash flow per share. We are focused on that as well, expecting $13 this year and $15 into FY '28.

Yes. I guess I'd say just on the agentic front, the agents, the APIs, Workday Data Cloud, this new consumption model is a beautiful model. It's a flywheel. Once it gets going, it really gets going. And it's new to us. It's not new to us as executives or leaders. It's new to Workday, and it's new to you and how you look at Workday but it's a far better model than a people-based subscription-based model, which will continue for a long time. But I'm super excited. I see the bills we have to pay to Google Cloud and AWS and Azure. And I think why I'd like to be in that business, and now we have an opportunity to be in that business. And we have to do it in the right way for our customers.

But once you start using these agents, I've done it myself with the Sana Self-Service Agent, you get kind of hooked on it. And it just keeps -- and you got to stop yourself because I realize I was probably burning through a lot of tokens. But I do think it's something that people are going to underestimate how powerful this is going to be for Workday. I'm confident of that. I'm not one to get way ahead of myself, but I see it. I see it. When exactly it happens, I can't give you a date. I think it will happen over time, and then it will just explode as customers get real value out of these agents. And that's the key. They need to get real value out of these agents.

Great. So with that, the most important time here is with Gerrit and his team because we want to have this be more you seeing the products in use. We would like to invite Gerrit and then Aneel and the team and I will be here later on for Q&A. So with that, let me invite Gerrit.

Hello. Good to see everyone. Did any of you catch the innovation keynote earlier to this day -- today? Some nodding, yes -- Mark, I know, I saw you. Anyone else? Okay, a few. Okay. I'm going to do just a very quick recap of some of that, right, for some who may have missed that. But we're going to keep it brief because I know I stand between you and some pretty awesome product demos. So I want to have it going on the double for all of you. So AI is pretty incredible technology, right? And we all can agree to that quite easily.

The interesting thing is though that on the enterprise side, except for very specialized roles like coding, the breakthrough really hasn't happened yet, right? It really is mostly being applied to the old ways of working. It's just making everything a little better. And if you look at total company output, total productivity, the impact has not been as large as of today. And this is actually where we think there is a massive opportunity for Workday if you understand, a, what drives it? And why is that really, right? What is preventing that from happening at scale? And understanding that when you actually change your perspective and look at it from a Workday lens, there is actually a lot of growth that Workday can drive from AI.

It falls into 2 categories. What does every single company right now go through? No matter the industry, no matter the country, right, more or less, but in broad strokes, everyone is working through the AI transformation. And what are they all trying to figure out? How do they need to reconfigure their organizations to be AI led? How do their jobs change, their profiles change, what skills do they have, what skills do they need? What system sits in the middle of all of that? Workday on the HCM side, right? There is a very interesting narrative. And I think some of you are actually guilty of pushing that.

And that's that interesting thought that AI is just a squeeze, just an efficiency gain, right, do more with less. That's all AI can do, right? You automate, right? You automate and you automate and you automate, right? But it is actually a quite limiting perspective. And well, I would say it's a real misunderstanding, right? Because the whole promise of AI is that actually you can drive greater productivity, address new market opportunities, serve your customers better. It's a story of growth. That is what every company is trying to figure out. Not every company is trying to be only more efficient. Everyone wants to grow, right? And that's the big promise of AI.

The opportunity that we have now at Workday is that on the one side, we are building that system of Work Intelligence that allows you to completely transform your workforce, again, which every company has to do. Everyone tries to figure out what do I need to hire, what skills do I need to build, where do I deploy my talent the best, right? The age of overhiring is over, right? Companies don't hire anymore to grow. That was the old recipe. The new recipe is that you actually grow the company and then you may hire, right? Maybe. And then secondly, what is actually preventing all of those organizations from adopting AI at scale? No one has a recipe for how to actually do that. And it starts with very foundational primitives like security and identity and permissioning and guardrails.

I'm sure you all read the headlines with the Hugging Face incident, right, of OpenAI model breaking out and hacking a website, right? And that sounds really concerning enterprise context because there are so many things that can go wrong when you say enterprise from the obvious things like paying people to the real hard things, compliance when closing the books, right? This is what makes AI hard. But what if you could solve the problem, right? What if you could have a platform which lets companies deploy AI at scale in a safe, reliable and in a lawful way? Two massive opportunities for Workday.

Just very quickly on the first one, right, because there is, again, also this idea that it's only compression and compression and compression. And yes, if you get very specific in graduate hiring in computer science, yes, there is a compression. But if you look in virtually any other function, the picture changes dramatically. Hospitality, health care, companies are looking for people to grow. If you look in functions like finance, what you all know, right, it's a very efficient function, but many CPAs actually are close to retirement. There's a huge talent shortage in that side of the world.

And now if you're looking at the new roles that AI is creating forward deployed engineer, every company right now in the tech space is trying to build a forward deployed engineer function. It has grown more than 7x over the last year in relevance. That job was practically irrelevant before. AI is in every job title right now and all the job postings. And most interestingly, outside of tech, marketing, sales, customer service, it is really changing the job profile. And the second thing which allows companies to do is actually changing how they define how they work, what their workflows are. You saw today and you're going to see later Work Intelligence, which is really a strategic toolkit for companies to drive the transformation of work for themselves.

I just want to quickly recap on the progress that Aneel spoke about, right, because it's easy to forget how much we have accomplished and how transformative that change has been. Last year, we said we're going to completely reinvent the user experience of Workday. Today, at Rising, Sana is the new Workday home experience. You saw it earlier in the quick screen video, a complete reimagination of how work gets done. I give you one example because it shows so nicely what it means when you free people from the work about work stuff and give them time to focus on what's important.

One example that you all may like, I like it that most people like is taking time off PTO. Sana cuts the time down by more than 80%. If you look at our customers, that is equal to 1.6 million working hours saved every year. That's just one tiny example. Now just think about if you redeploy that time to something which is productive versus managerial. It shows you how big that leverage function is. It is insane. We talked about the open platform strategy, and Aneel spoke about Data Cloud and what it can drive. We have seen such incredible momentum with our AI developer tool chain. We have trillions, trillions of rows of data in Workday Data Cloud already, growing 75% year-on-year. And all of this is driven by customer demand who wants to use that data for their own agentic transformation, for their own UI use cases, use it as context, bring it together with other data for analysis, all possible.

And based on that idea of giving enterprises strong guardrails, we have had our open platform for AI in early adopter for 4 months, more than 6,000 applications developed, multiple hundreds of agents built with it. And it really stems from that need that, yes, I want to have a frontier model. Of course, why wouldn't I? But I want to give it a safe context and guardrailing system so I can run it reliably and lawfully. And last but not least, last year ago, we were just getting started with Workday organic agents. We had a couple, but I think it's fair to say not many of them have been in production yet. Today, we are at approximately 6,000 customers who are using Workday organic UI in production. We just achieved a milestone of 1 million users for Sana Self-Service Agent. That just shows you that incredible potential that we have and really reinventing the work across finance and HR. So bringing it back to the convictions that we have, right, how we think our portfolio strategy, why C1 makes sense, you may wonder, and what we're going to show you next.

The key stepping stone to overcome is that AI needs to be trusted in an enterprise context. That is foundational. And you would be surprised how hard that problem is to solve. Because guess what? Current guardrailing mechanisms, current way of thinking security, all of that is conceived from a human, right, from a human continuity of something like a service account. No one has really thought about, right, what it means in the age of AI because an AI model can now act on my behalf and is doing something very different, if it's acting on your behalf and doing something else, right? And yet I need to understand the security model per request at the right time to -- in order to enforce it correctly. And it's very important when we say that AI must be trusted that we mean with that all AI in an enterprise context needs to fulfill that guarantee of being reliable, auditable and secure.

The second thing, which I have just said, and that's driving so much of our momentum, this moment of redesigning work, really reconfiguring every enterprise in virtually, all aspects, team, talent, organization process and giving them a system where you actually move from this age of copilots. That is really the limiting factor of stand-alone AI, right? It's that smart side panel sitting on the side, having no understanding of how to actually change the process itself because you just prompt it in the traditional way of doing work. And like I said, there are some domains like coding where this is just incredibly AI friendly. But in 99.99%, that isn't the case. Companies work fundamentally different. And that redesign moment allows us to introduce these autopilots.

And they are incredible game changers because you all think economically, right? I would say, roughly speaking, in economic terms, AI assistant equals to software spend. Autopilot equals to labor spend, right? Because it's actually doing something independently, behaving like someone performing that function. And last but not least, this idea of making AI a growth driver through your talent by actually putting the org and the workforce transformation in the center of that conversation. And like I said, every meeting I have had, be it with customers, prospects, partners, even before I joined Workday and worked for a very different company beforehand, every company was trying to map out the AI transformation. And every of these companies were starting with how do I actually reconfigure my organization and my talent around it? That puts Workday in the center of all of that.

So Work Intelligence, that analysis platform for recomposing work on a continuous basis, that's the brilliance of Work intelligence and its counterpart decision intelligence that the enterprise is not sequential anymore, right? Something that maybe we have all liked annual plan, annual budgeting, zero-based budget, all of that stuff, going to a continuous fluid model where you constantly redeploy and reassess your talent mix. That's Work Intelligence. I spoke about the autopilots and recruiting is one. Sana Concierge is another. Sana Coach is yet another one. We are bringing all of them to market because this is where we are seeing the biggest unlock and a trusted agent platform underpinning them all. It's the platform that we are building on. And that's why we are so confident in giving the same platform to our customers.

And again, I want to address it because you may have that false contradiction that should I use a frontier model or the trusted agent platform? This is not how it works. This is like saying, should I choose a CPU or a cloud hyperscaler, right? You have to think of it as a value chain in a stack, right? We are using all of these models, and we are providing all of these models, including Jev from TypeSafe, recent innovation on the block, if you will. And we are exposing them and giving them everything which they don't have, like the trusted context, enterprise guardrails, workflow awareness, domain knowledge in HR and finance. And we are bringing this, which you saw in innovation keynote into all canvas, very important to us that Workday meets you where you are. This is why we are introducing candidate search and application in ChatGPT. We announced today the partnership with Anthropic, Sana, and Claude. That's how it all comes together in the AI ecosystem around us.

I want to say just 2 quick things about C1 because it is not just about acquiring a company. For us, this has been, like Aneel has said, an incredibly strategic move for 2 reasons. One is, identity is fundamentally broken, comically broken, I dare say. What is the source of all identity in any enterprise? Who knows who is getting hired, who is moving teams and who is leaving the company? Any guesses? You're not a shy crowd, are you? You're usually having the sharp questions and the sharp minds. So the HCM system, of course, that's the source of all of it. And all of the identity vendors are basically trying to organize themselves around it, but it has big limits. One big limit is there is a huge delay from hiring someone to provision access or from someone leaving and deprovisioning access. Big question in the compliance space.

But there is even a bigger one when you think about AI. Who knows what the person actually got hired for? What's their job? What are they working on? Who are their teammates? If you know all of that, what can you actually automatically infer in access rights and how intelligently can you automate them in a way no one else can. If you're a software developer, what you should have access to based on the true work graph of your environment. That is a huge potential. And then secondly, the reason why C1 is so special is because it thought about it not from the old ways of the human identity, but the task-based identity, permissioning work that's happening right now at a task basis. This is what makes it unique. And this is what makes it so incredibly valuable for AI because it solves that biggest problem, how do I do contextual permissioning for AI requests on a real-time basis? And again, something for the quantitative side.

The estimation is that only I think in 2 or 3 years, agents probably will outnumber humans 50 to 100:1. That is a real growth opportunity because, guess what, the physical world is limited. There are only so many workers in the world, and there is a limit to the growth, what it ever can be. But a digital universe, it's unlimited. Again, when you think about your economic model, this is why this is so interesting because you can have indefinite economic growth because you are not resource constrained in the way you were in the hire-to-grow economy. And C1 basically gives us the platform to be the security enforcement and identity layer across all of it.

It also completes our world model of work. In the world of AI, there are just limited ways of creating real value. One is you can provide that very foundational base model. You can conceive it as evolution. That's model training. That's the best metaphor I have. It's like evolution. It creates something with a base intelligence. And then everything which you are building on top of it and around it is contextualizing it through tools that you give them, or you can call them harnesses, right? Things you give it to act, data and context, you give it to allow it, what's relevant, what needs to happen, what's the goal and how to do it and embedded in the real-time flow of work. And now with C1 and identity, right, we truly have that across finance, HR and IT.

We have an incredible TAM opportunity. And saying -- and Aneel spoke about it. So I'm just going to skip ahead and tell you, I'm as the product person, I have it easy, right? I'm saying, in spite of the numbers, I'm not a product visionary person. And it allows me to say that I actually think our TAM opportunity is much, much bigger, much bigger than this. And here is why. We have the opportunity to go into new areas that no company, not even Workday could actually enter the way we can now. Just think about employee service, all types of employee service delivery. Pre-AI, that was a question of expensive software and shared service centers. Sana Concierge, our self-service AI already deflects more than 25% of HR cases today and gives back our customers a 20%-ish gain in productivity. This is just the very beginning.

With C1, you saw how we extend this into all of the IT requests. We're going to do this on all of the finance scenarios as well. This is going to be a hyper-converged AI service center that we're going to provide. Secondly, we are going to really bridge the gap from work about work that get people actually frustrated and also gets in the way from doing value-adding work in their companies through autopilots to a place where actually people can work all of their time and what it takes to drive their business forward versus alignment, coordination, management alignment, reviews, et cetera, et cetera. It's a massive simplification of work. And if you heard yesterday, Ethan Mollick saying -- Ethan Mollick said basically, right now, companies are regaining control of what they were actually meant to do because all of that mundane work is being automated away. Talent acquisition is the best example where you can actually see how that transforms in a complete agentified way.

And last but not least, finance. Finance is an annoyingly efficient function, right? So when you think about total spend, right, of a company, finance is tiny. But this is not where the opportunity in finance is. How much money do companies lose through uncompliant spend? T&E is the biggest manageable expense line that exists, huge problem. How much money is lost on incorrect payrolls? You would be surprised. So the economic potential for us in finance is that it's not about making finance less, but actually having all of those financial controls being applied continuously and in real time and actually having that perfectly executing company at any segment, not just at period close.

So I know I said a lot, and I'm going to give it now over to the demo team, which is going to show you examples of all of that. But you've got to remember, when you think about Workday, Workday wins in all ways. Whether you're accessing our platform through agent-ready tools and Claude or Copilot, it's our AI APIs on our Flex Credit consumption models. If you're building agents and you want to run them on safe enterprise guardrails and you deploy them into Workday, you're sitting in our run time. And again, right, Workday directly is able to partake in the value creation.

And last but not least, if you're going for the full and dare I say the best experience for HR, finance and IT, you're using Sana. You saw how transformative it is. And all of those 3 things come together in one agentic workplace, again, right, that we partake in. So this is really the key, right? No matter what path a customer chooses, and maybe I'm telling you a little secret here, there won't be a single clear cut customer who's saying, I'm only doing 1 or 2 or 3. Customers are doing all 3 simultaneously for various different use cases. And the greatness of our model is that we are a part of all of them. So I said I keep it short. I hope I could share with you the most relevant pieces of Workday strategy.

And now I would like to hand over to Joel and Charlotte who are going to show this to you in practice. Joel, Charlotte, over to you.

Thanks, Gerrit. It's fantastic to be here with you all. I joined Workday through Sana and now serve as Chief AI Officer. And my thesis was really quite simple. The company that owns the workflows is going to be dominating the world of AI. And since we brought the sort of start-up spirit and frontier of AI in Sana with the enterprise readiness of Workday and now rolling it out to thousands of customers around the world. Together, we're moving from AI that is simply responding to questions, copilots, if you like, to agents that can safely do real work, autopilots. I'll show you what that means for some of our customers and why I think this creates a significantly larger market for Workday as well.

Workday's opportunity, of course, starts at the core, but it doesn't end there. AI is helping us innovate faster across financials, payroll, recruiting and planning. And I think the larger opportunity is really transforming the work that is around all of these systems. And that's really where we're focusing a greater share of our R&D. Most of enterprise AI systems today are sort of copilots that sit on the side panel, answering some questions, maybe supporting you with individual tasks. We call that single player AI. Our agents can coordinate and perform entire workflows. They anticipate what needs attention, they advise on the best path forward, and they can act within company policy and controls. We can actually get work done. So this expands our TAM truly beyond the software budgets into the labor and services spend attached to that very workflow.

And I think this slide does a good job at showing why this opportunity is so large. Across each one of these categories, we already serve thousands of customers. More than 80 million users under contract. So we aren't entering these workflows from the outside. We already have the customer relationship. We already have all of the operating context and every repeated workflow is an opportunity for our agents to do more work. And that creates measurable value for our customers, but it also gives Workday multiple paths to expand within our installed base.

So I think this is really where Workday has a real advantage. We already understand these workflows. We already have the context across people, money and processes to get work done here and we operate the systems where all of the action needs to happen. And this really enables us to have agents that do real work. They don't answer simple questions. They actually execute the entire workflows. Customers get capacity to move faster and Workday grows as more and more and more of these agents run through our platform.

Let's just take HR and IT service delivery as an example. It's high-volume work that causes HR, IT and multiple systems, but our customers are spending tens of millions of dollars on outsourcing firms on. Today, this market still starts with the ticket. So in May, we introduced the Self-Service Agent as well as Sana for ITSM. And today, we're bringing all of those capabilities together around our new offering, Sana Concierge. This is a new way to deliver employee service across HR and IT. And I think it's really delightful to use. Employees can get help with onboarding, leave, payroll, access, IT support all of that in a single place.

As an employee, I just type what I want and Sana takes care of the rest. So instead of these employee systems, creating tickets, sending that to a person, Concierge is built to complete that request itself. It's the patterns that we've seen applied to customer service around the world, but now working for you internally. It understands the employee. It understands the company's policies, takes actions across Workday, but also all of the connected systems around it. And when judgment is needed, it prepares a case for a specialist.

So with the history, supporting context and the next steps already serve there, a specialist can approve it. This is very, very difficult to replicate without Workday's context and processes. Customers get fewer tickets, faster resolution and lower support costs. And this is a radical change. We already heard 25% increase in resolution rates across Self-Service Agents. We're only getting started there and tens of millions of dollars folks are spending on outsourcing spend here, we think we can make a significant cut too.

But also employees become productive sooner. I'll show you shortly what that looks like but for Workday, this also creates a much broader sort of premium offering for our customer base. It also creates recurring usage across the employee life cycle. Actually just saw a tweet before I came up here and with someone about our new user experience and said, "Oh, Dan, will I start loving to use Workday now?" And I think it's a pretty good proxy. People love coming back to our product experiences now. We're bringing a consumer-grade DNA to our product experiences and customers can't stop to use them.

So we have a single employee that now can instantly onboard to the company. We have HR and IT service delivery that can run on autopilot. It's a really incredible experience, and I actually want to show you like what it all looks like. So let's start by an employee getting onboarded here. So historically, this would have been an employee jumping across dozens of systems, creating a bunch of tickets, escalating that to humans, a human resolving the ticket and a lot of back and forth. Here, you can see the onboarding experience with Sana, it's all set up from day 1. Sana, it looks at all of your systems, what you will be working on and so on and sets up your plan.

So here, for example, you can see the Sana learn experience has created all of the courses and the training sessions, already scheduled them for you and what you need to get done. Sana has already gone ahead and scheduled the meetings with all of the folks that you need to meet your first week, your manager, your direct reports and some colleagues that you will be collaborating with. And also, through Sana for ITSM, as you can see here in Concierge, it's ultimately all of the setup of all of the tools that you will need access to. So on day 1, this is all set up for me and creates a very delightful onboarding experience.

But I can also just go straight to the Concierge experience. And this is literally a Concierge. I can type in whatever I want access to. So for example, if I need access to Cloud, Sana will route that, look at the approvals required for this, whether it's safe to provide any access. And it looks like this is all good. So I can just hit submit and Sana will give me access to this system instantly. So that, which would have historically taken a lot of back and forth, created tickets, being escalated to a human was now run by out the autopilots. And that's what we mean by autopilots. Autopilots can actually get the work done for you.

But we've also been really pushing on the user experience. So what we've been working on here together with the team at TypeSafe is dynamic UI. This is instant UI. This is UI that's literally generated in hundreds of milliseconds. And Workday is the first company on the planet to bring this to the market. So here, it means I can write something like what's my first paycheck, Sana will reveal that for me instantly. I can type a query like who is Victor Miller. And it's so fast and it feels so obvious that you barely notice when it's being generated. Here, I type something like whose Victor Miller and it pulls all of the details for me instantly but it can also create these richer components like a calendar view. So I jump in here, and I want to schedule a meeting with Victor, it sends that out. And for frequent workday actions, such as filing a PTO or a similar task. Sana generates the calendar schedule pre-populates all of these different fields. So it all looks good, and then I can send out that request.

So as you can imagine, a lot of companies are building conversational interfaces to solve this task. For very few tasks, that's actually the most efficient UI. UI augmented AI is really powerful, and we're really excited about the product experience that we've created here. So since joining, Sana has entirely reimagined the user experience. We brought a lot of new agents to market, and I couldn't be more excited about this progress.

But to share a little bit more about what we've been working on, I want to hand it over to Charlotte. I'll see you soon.

Thanks, Joel. That was what our new experience looks like for our employees. But what we need to also focus on is how we're looking at new decisions about the workforce itself. Right now, I'm going to play the role of a CHRO, and I want to review our hiring plan for the next quarter.

So I simply ask Decision Intelligence. Once I do a quick refresh. Sorry, everybody, live demos. So I want to review my hiring plan for the next quarter. So I'll ask Decision Intelligence to help me understand what's happening. The current plan includes 50 new hires. But I need to know if that's what's right for the business, do we still need those 50 new hires? I can ask Decision Intelligence to understand based on the work we know about the team. Now it uses our work intelligence capabilities, understanding the tasks and the skills that we have within our workforce and identifies the work that can either be automated or augmented by AI.

From here, it's going to find out any duplicated work. Underused capacity, Skills Cloud will show the capabilities of the skills that we already have and with external connectors, we can bring in third-party benchmarks as another source of context. The answer is we don't need 50. We actually need 42. That will reduce hiring costs without relying on a simple headcount cut. So I ask Decision Intelligence to update the plan. But before acting, I want to understand the broader impact. Decision Intelligence actually recommends that we even fill 9 of these roles internally. It searched my entire global workforce for suitable employees. The employees that have the skills we need, the experiences and have even indicated those career interests. Now this reduces the need for external hiring. It creates meaningful growth opportunities for employees and my plan now actually reflects the skills, capacity and the actual work. This is far more precise than a traditional headcount plan.

But every workforce decision has a financial impact. So as a CHRO, I decide to share this plan with my partner over in the CFO world.

We'll now move into the SD&A experience once this is shared out. So I share this with my financial adviser -- my financial adviser, I share this with my CFO, and I'm going to be ready to review this. However, from a CFO perspective, this is the Decision Intelligence is bringing the same data. There is no copy and no sync between HR. HR does believe that we could fill these roles internally. But from a financial perspective, I want to actually understand the impact that this will bring. So from there, I noticed that we see that we have faster internal hiring recommended. And this could mean faster revenue growth.

So I ask that same Decision Intelligence about if we fill these roles internally, what is our revenue potential. And it's going to model that outcome. I see stock rates, ramp dates and finance is now using a model that is no longer just cost data. This information includes people, skills. It's got the ramp time to the different roles. And it's even bringing in pipeline data and demand data from Salesforce. Decision Intelligence analyzes all of those inputs. It shows that we can actually support our higher revenue target and this target is based on roles that we can actually fill. It isn't just based on hoping that we hire faster.

Now I want to look at the information behind this. HCM provides the skills and the interest but I can see what the handoffs start to happen. I see Peakon is providing the sentiment insights and confidential comments, allowing me to better understand my employees. Financials has brought in the actual cost. Salesforce provided that pipeline and the demand data. And normally, this type of amalgamation would take weeks and several spreadsheets. Now I have one with the sources actively identified and clearly traced.

I now have a plan that by business can execute. Decision Intelligence doesn't write back anything on its own. It waits for me to review and approve the changes. Once confirmed in the working plan, the approval train will always be visible. All of Workday security and approvals remain intact. So what did we just do? We analyze the data, we made a decision and we recorded it. That is the value of owning the full decision loop.

But as AI companies -- as AI helps company move faster, financial controls must keep up and traditional controls often test a sample after the fact. And by then, the damage may already be done by an issue that was caused. Financial test suite continuously test transactions as they happen. Here, I see it's examining the work completed by people and agents. And in this example, it reviewed 90,000 transactions but it's identified a small number of risks that do require investigation.

Let's start with procure-to-pay. Here, I see various tests covering several payment risks. These tests include duplicate invoices and cutoff issues. We can also now evaluate actions taken by the agents themselves. In this case, this test reviewed more than 400 actions by an AP agent. However, these same controls applied to people now applied to agents. But I want to really investigate this payment change to bank account details after they were changed. And this is where I noticed that there were some suppliers -- some suppliers that change the bank details shortly before payment. The agent identified the risk, place the payments on hold, and now I can either reuse the hold, cancel the payment or investigate further.

To do this, I can see the transaction lineage. This shows who approved and who initiated each step. From there, I can quickly see what changed, and I can also confirm whether it was within our policies. But based on this, I can decide I might want some more coverage for these high-value financial transactions. So I can go to my test library, where I'm able to see tests that come from both Workday and our third party partners like KPMG. KPMG here is providing a 3-way match exception detection, allowing me to do that as an AP cutoff. However, based on what I just saw, I really want to focus on building out a test for segregation of duties. And now we see a test is provided by Workday that will check whether or not one person can change, think details and pay. Definitely something we shouldn't be allowing. That is a combination of admissions that introduces significant risk.

So I asked the financial test suite to build out this and configure this new test. Before publishing, I'll be able to review the methodology that was used in order to build out this test. And I can even see a preview of the people and transactions that were flagged as a result of this test. Now I noticed that there are some responses, but the agent also anticipates and advises some changes we can make to this financial test that will improve the outcome. So I accept the recommendation and rerun it and see the new results.

Once I'm satisfied with this test, I publish it available to the financial test suite. And already within this, we see the results and it immediately begins running across all of our transactions. This makes continuous compliance possible before an external audit.

Now let's look at a very different process, talent acquisition. This makes Workday a major gateway between employers and talent. However, as recruiters, it still requires significant administrative effort. This includes screening, sourcing, scheduling and all of the related follow-ups. The talent acquisition agent changes that. So now recruiters can focus on the people and the business of judgment. Here in our talent acquisition agent, we see a new role that was created that didn't previously exist, such as our AI safety engineer, normally, this information would wait until I logged in. Like most recruiters, I am managing a lot of different things. The talent acquisition agent doesn't wait for me. It continuously runs and scans every open requisition.

Now I see that it's flagged a potential hiring risk. The AI safety engineer doesn't have enough candidates in the pipeline to reach a potential target higher date. The agent diagnosed the problem before I even looked at the requisition. And it's found out some previous applicants and members of our talent communities that I can reach out to. These could be silver medalists or the second place run up in a previous requisition or we can even utilize external partners such as Finder and HiredEasy as a sourcing opportunity.

So now the agent has drafted a potential reach out to 15 candidates. At this point, I can review and use my judgment to approve it. This is hours of sourcing saved and now becomes more focused on a review. So after I approved that outreach, I see that applications have started to arrive, very exciting. It helps me identify the strongest candidates faster. I'll be able to see and understand why a candidate is a great fit. This is bringing together our highest score Paradox and recruiting capabilities all in a unified experience. But importantly, I also see the gaps and why they might need more attention. However, I think this candidate looks pretty good. And so the recruiter is still going to be responsible for the decision. I move this individual to an interview, but the agent has made this decision easier and better involved and now the agent starts the interview process. It checks availability from the candidate and the hiring team. It sends the invitations and handles any of the rescheduling. That removes a large amount of administrative work.

So during the interview, it means we can focus on the most important thing, the human connection that still matters the most. So we start the interview. And when it's time for the interview, the agent is there. Doing the interview is the actual fun part. Writing the feedback that may be not as exciting. The agent steps in with prepopulated responses based on transcripts and notes, I'm not starting from scratch. This gives recruiters and hiring teams the time they need back in their day, so they can focus on their teams and the interviews and removing the administrative burden. This interview then becomes another signal about the candidate. So from here, I'm able to see and understand more about the agent signals and what they're using for candidate rediscovery. It might decide to rediscover this candidate for another role in the future should we not move forward with them.

The organization also means in control of all of this. In the control plane, this defines what the agent can and cannot do. It also defines what must wait for a person. This means the agent moves quickly, but within the boundaries that are set. Now we transformed the recruiter experience. But we've also made applying easier for the candidates themselves. People are now discovering jobs in entirely new ways. The application experience should meet them where they are. Today, I'm going to use ChatGPT to look for a new role. Little awkward with my entire leadership team currently watching me to apply for a new role, but we'll do it anyway. The candidate profile now gives me one identity across Workday hosted applications. I no longer need to create another account for every single employer. I verify my identity through a quick text exchange. Sana then surfaces roles based on my skills and who I am as a person and the experience that I might want to consider.

From there, I can see how well my skills fit these particular roles, but also where it may have gaps. At this point, I decide whether or not I want to apply. I answer any of the in-line questionnaires and the application experiences right in the flow of that work. And then from there, I'm able to directly submit my application. There is no longer a long form of fields and candidates and passwords to remember. This ultimately can help strengthen candidate pipelines by reducing candidate drop-offs.

So you've seen a lot, but I would like to pass it over to Joel to close out our little section.

Thanks, Charlotte. Wasn't that really good? I mean you just saw how we're completely transforming the work across all of these Workday processes. So of course, as we do this, we drive tremendous efficiencies for our customers. But I also think there are many illustrations of how this is opening up entirely new sources of TAM for Workday.

In recruiting, for example, as you just saw, we are completely changing the economics of recruiting. Today, we have over 400 million applications on the Workday platform just last year. And this creates an opportunity for both Workday and our customers, where our customers can continue owning the relationships and all of the hiring decisions but the agent takes on more and more and more of this work. And the more work that our agents take on, the more our opportunity grows. It's no longer based on the number of users on the platform. This opens up a labor pool of more than $100 billion just on the recruiting space alone. So these examples represent a much broader road map for us. Our agents can anticipate, advice and act across many workflows and over time, they take on more and more and more of this work.

Of course, it starts with these individual tasks, but then it expands into the continuous coordination across complete workflows. And where we're focusing Workday is where we have that differentiated context, where work happened repeatedly at scale and where that customer outcome is measurable. Workday against new products and more platform consumption as a function of this, but we also get deeper engagement inside of our core applications. So today, we showed you some of these examples of where Workday can transform workflows directly. I'm a very simple man and my thesis here really is we own the workflows. We build agents that can deliver on these workflows, and we expanded the TAM to take on labor as well. It's an incredibly exciting time to be building AI at Workday. But our customers also need an open platform that preserves this governance.

So I want to hand over to my good friend and our CTO, Gabe, to show you what this looks like across the full ecosystem. Over to you, Gabe.

Hey, everyone. It's good to be with you today. And I'm excited to dive into some of the coolest tech that is, I mean, really transformative. I mean, it's such a special time to be in the industry right now. And Gerrit had a point that I want to pick up, which is enterprise AI only works if it's lawful, not lawless. And that means running inside of enterprise rails versus around them.

Now what happens when something like that could go wrong, when you take a sneak peek at some of the creative.

[Presentation]

Funny, right? But AI that's almost right is wrong. It's true, right? You can't get payroll right 99% of the times, it's got to be right 100% of the time. And this is true in a lot of different scenarios in the space of HR and finance. And that's why Workday's role in this transformation is so critical. It's also why Workday is evolving from a system of record that you log in to at your desktop towards an open platform that you can build on and that you can easily extend.

We call it Workday's Trusted Agent platform. And it's differentiated on 3 core points that drive our strategy and drive our platform business. The first is that we're Open by Design. This is a key to our monetization engine. I think Aneel and Gerrit both mentioned this and we'll talk more about it.

The second is it's backed by builders. It's important because everyone today is a builder. Natural language has democratized the art of engineering these systems, right? So we want to create that product-led ecosystem and flywheel. And the third, and this is really critical, and this is something only Workday can do is we are lawful by default, and this is our unmatched competitive moat, and we're going to cover each of these.

So let's start with Open by Design. And if you remember nothing else today, I think this is the one to remember. And the exact path Gerrit mentioned, this is the one that lets customers connect their own agents straight into Workday. Now again, Gerrit talked about this, but it's really important. A year ago, we stood up at Rising, and we promise an open platform. Today, our trusted agent platform makes that real. What does that mean headless access to HR and finance data. Every capability required to do that is now live in GA. And the cool thing to me is we're customer 0 for this stuff.

So if you take a look at the demos that were in the innovation keynote, all the stuff that Joel just shared, all of that is powered by all this headless technology, right? We're building on top of the same stuff. But it's also a major monetization shift for us. This is where we can create a brand-new product-led flywheel that's going to drive platform consumption and really extend the growth of the business. And I mean, look, we don't have a lot of clarity on what this looks like yet because it's still early days. But we know there's tons of demand out there for folks building, whether it's personal agents or different ways of driving the headless business. It's really a big demand.

And so to kind of walk you through how this works and some of the challenges, frankly, that we see with this, we're going to walk you through a company that we set up here, Acme Industries. And I want to be very clear, this is modeled after the very real Fortune 50 customers that I see on this headless journey. Now meet Maya, she's an Engineering Director for HR IT at Acme Industries. If you're going to do a very common task, right, building an internal mobility agent, very common thing that we see from our customers. So you could do it the way that we see a lot of customers do it. Own stack headless. You need a few things, way to pull her open job recs, a way to move people between different roles. And all of this critically, and this is the part of what you guys pay attention to is it's got to be scoped to what Maya can see and what Maya can do.

There's a couple of ways to go about this. And before I show you the right way, I actually think it's more instructive to show you the wrong way first because this is where I think the market has it wrong. I know certainly some of the customers I talk to have it wrong on this. And it's wrong in the sense that people think it's safe to build agents on custom MCP engineered solutions and or data that's kind of extracted out of Workday and put into some external data lake.

And I want to show you guys, this is not safe. This is actually causing a lot of problems. It is lawless, as we say. So let's show you headless the lawless way. So we'll move over to the demo here. And what we're going to start with is here, we're obviously in cloud. So we're going to think through this internal mobility agent. But first, I want to show you, this is the pattern. So Acme Workday MCP. This is not Workday. This is built by Acme. By the way, this is a true story, okay? I have lots of customers who are going about it this way. Think of it as like they're creatively taking a way around our guardrails and our path here.

Well, a lot of them don't mean to do that, but they are doing it. If you take a look at what's inside of the MCP server, we got some read only tools, we've got some right tools, should be enough to execute what we want to do. So let's just try out some of the gestures required to build this agent. So I'll paste in, share me my open job recs -- or sorry, show me the job recs. Now the word my is doing some work here, right? My open job recs refers to Maya, okay? Now you're going to see we get 30 open job recs back, okay? So that's first part. So it looks like we got a tool came back. Second part is let's move Casey on to my team as a senior engineer. These are the building blocks of internal mobility. So this works, we can probably build a whole agent that does this. And you'll see that we're submitting some stuff, and it looks like it's done.

Now here's the problem. This was supposed to go through approval chains and workflows and business processes that we've set up that our customers have set up inside of the tenant. None of that actually happened in this case. So this is a big, big issue for that, okay? Now let me show you another problem here. This is kind of the other pattern that we see with our customers, which is I want to take the data inside of Workday. I want to extract it as like a snapshot, put it into a different system like Snowflake, which is what we see here. So you could see we've got this Workday snapshot. We have all these tables. We've got all these different tables here, all the different data inside of Workday. So it's quite helpful to have this data in a lake. And you can see here's our job requisition field. So we should be able to ask similar questions. Let's try it again.

Show me my open job recs. And we're getting 30 back. And what I'm noticing here is this is actually account executive roles. This is the sales team. These are not the right roles for this agent. This is actually a completely over permission agent because remember, Maya is in the engineering department. Why is Maya seeing roles from sales, marketing, HR, this is actually not what we want. So just sort of a crazy example here, but we'll go paste something else in, what's the CTO salary just as an example. I mean, this definitely not come back. We take a look and here it is. It's coming back. And I'm sharing this because this is very real, right? When you extract the data out of Workday put it into a data lake. All of the rules come off the data. And so these kind of things are not only plausible. This is, in fact, how this looks. Building agents against us is very risky.

So point an agent at the lake. For a lot of customers I talked to, it feels like the obvious next step for their data strategy. But what it's really doing is it's quietly turning a governance system like Workday into an ungoverned one. Now I do want to be clear, data lakes are awesome. They're actually great for lots of things. They're great for joining your other enterprise data with Workday data. They're great for building reports and analytics at scale, browse reports, things like that. But hopefully, you saw in that example that you can export the data from Workday. You can't export the rules that govern the data. Maybe you could try and rebuild them, but that really doesn't work long term as a strategy. And until today, we haven't really offered our customers a great answer to this dilemma.

But with that, let's see headless now the lawful way. All right. So we'll move back -- and this time, we're going to start on the data side, this is in tableau, and we're going to take a look at this connection. You could see there's a client ID and secret. I know you guys probably don't quite follow exactly what this is. This is Maya, logging in as Maya, okay? And getting low level access to Workday data through our live data query product. Now we're going to ask that same question, paste it in here, show me my open job recs. And what you're going to see is we're executing that query. Now we got a different response. We've got 16 open job recs. And I can tell by looking at these that these are actually scope to engineering. So these are the right roles. So I said before, you need to see what Maya needs to be able to do what Maya can see. So this is what Maya can see.

Now the other cool thing and this is something I hear so much from customers is look, Workday has this unbelievable object graph that has been the secret to our succes for so many years, it powers all of the 20 years of HR and finance success that we've had at Workday. But it's also been tough for our customers to get raw access to this. So what you're seeing here is a SQL query that select statement there. And this is something our customers have been begging us for. Developers get raw open access to live Workday data without making a copy that leaves the rules behind.

All right. So let's move on to the MCP front here again. And you can see this time this is the official Workday MCP server, what we call our agent ready tools, now generally available. We'll go ahead and connect this up. And the first thing you notice is we got to log in, okay, because this is going to be done as Maya. So we're going to sign in as Maya, and this is now connected, then we'll go ahead and start some of these prompts again, show me my open job recs. Again, the identity piece is so critical to this to get right. And you can see that we're getting 16 open job recs, these are all mapped to the engineering role. And again, if we go ahead and move Casey, we're going to see a better outcome in this case which is not only are we going to find hopefully right Casey, which we did, Casey, who's a software engineering data platform. But what we also did is we started an approval process and workflow versus just executing the approval right away, which is what often happens in some of these other failure mode cases.

Now the other thing I just want to point out because this is the really exciting piece is check out how many tools we have. Look at this list of tools about 400 tools we have, read tools, write tools, I'm not going to read through all of these, but this is the surface of Workday. By the way, we're constantly expanding this list. Customers ask me like, how many tools, like when do you get to done? Honestly, I don't know where ever going to get it done. There's always going to be new combination of tools we're going to build for customers.

So incredibly exciting potential here through the headless enablement at Workday. And why is that will headless used to force a choice between speed and control. And now today, that choice is gone. Now lots of great capabilities, but let's talk for a minute about what headless enables, what it enables for our customers. If you think about Workday, in some ways, Workday represents your company's institutional memory. I like to think of people and money data as like the base of enterprise needs, right? Everything in the enterprise from a data perspective, it all derives from your people and your money and all of that context used to be locked away.

Starting today, any agent that customers build anywhere can get to use that context and use it safely as defined by our guardrails. Now what can this unlock, lots of things. Just a couple of examples that come to mind. Field operations, imagine an agent that is able to assemble a field crew, the perfect crew, right, the right experience, the right -- based on performance history, kind of pull that all together, do that without any data leakage, really exciting.

Maybe on the R&D side, even closer to my world, the agent could, let's say, model the financial cost of a team's big new bet, right? We're going to go build something crazy and do all of that right inside Jira where the engineering team works or maybe retail operations where the agent can match staffing needs directly to point-of-sale traffic, balancing real-time availability with exact cost center performance. This context changes everything for our customers. When they have access to this headlessly, who knows what they're going to build, who now much usage and demand this is going to drive. We honestly just don't know because this is so early. But my bet is, given how foundational authoritative people and money data is to enterprise workflows the demand for this is going to be incredibly high, and we're already seeing signals of that now.

Now to bring this all together on Open by Design, Workday's now have us, agent ready tools, GA, tons of momentum on this. The demand is just incredible for this, as I said, 500 tools at 4-ish, 500-ish. We're shipping about 130 of these a month, by the way. So the momentum is really accelerating in terms of our ability to churn these out cover more surface area of the product. And by the way, I do want to mention, I think this was hopefully noticed in some of the news, but we have been partnering closely with Anthropic and some of the other AI labs on this MCP surface. They are our customers. And so there's not only like the fact that we're shipping things, but that they're getting used by the likes of Anthropic is, I think, an important proof point.

Now Workday Data Cloud. Also, GA, live data query, that capability I showed you before, SQL access to the Workday object graph, this amazing piece of technology that is propelled Workday for so many years, now GA, right, live direct SQL access to Workday data with the rules built in. And the feedback from EA customers is, look, they want options. As Gerrit kind of laid out those 3 options, they want to be able to choose the right path based on the right use case, right? Some paths are going to be headless, some paths are going to be subagents, some paths are going to go through the Sana workspace and some of the unbelievable end-to-end product that you saw in Joel's demo, right? And like we win when our customers win, and that can happen on any path.

Now shipping tools is only part of the job. The other part is making these tools effortless for folks to use because today, everyone is a developer, every one is a builder. And I'd like to reflect on the AI companies that I see, right? If you go to any of these big AI companies, when you -- you get to sign up for the products, you get to use the product. You don't have to talk to a salesperson first. And I think Workday has really kind of thrived in that prior model, but that's not the future. The future is log in, sign up, get an account. And that when we do that right, it fuels a product-led flywheel that will drive pipeline on the sales-led side.

There is the 2 key updates that I want to share on that front. Starting today, you can get a free account on developer.workday.com, and you can also get instant access to a developer tenant. And that allows you to basically probe on the MCP surface. Fun little fact, we did this CIO keynote today where we shared this news. Biggest applause line of the day was actually this, right? Because folks who try to get access to Workday the tenants know it's been pretty frictionful right? Trying to get a tenant. It's also been expensive frankly, for Workday to provide these, right? Because these systems are architected for pretty large scale. And so we had to actually build and engineer a new kind of lightweight small-size developer tenant to create this product-led flywheel. But the net result is you can now go to a developer.workday.com, sign up, get the tenant, build your headless app, promoted into the marketplace and probably do this with whatever tools you want to use, right? So the cursor, cloud code, VS Code whatever.

We also have our developer agent, which is our prescriptive way of building agents. They give it as like the guided path for building agents the way that we think they should be done. That product has been a rapid success. Since June, 125 customers have built 500 agents and 6,000 forms-based apps with developer agent. In fact, I have one customer who built 25 agents over a weekend, this is a media customer, totally insane velocity that we're seeing. Now what does this mean for financial levers. First, on the ecosystem front, we have tripled our developer community in 2 years. A lot of momentum here but we are only just beginning. We believe that with this product-led motion, we're going to be able to 5x our developer ecosystem from where we are today.

The second is marketplace expansion. There is still a huge need for content on the marketplace that is areas of the product that Workday kind of first-party road map is not going to cover. We think there's a great opportunity for developers, whether they're affiliated with a service integrator or a major partner of ours or maybe unaffiliated to build apps to monetize those apps and to take part in our ecosystem.

And thirdly, there's a need for a global talent pool. And we hear this a lot. Workday is obviously a global company, but we need help. Our customers need help implementing Workday, deploying custom AI, headless integrations, building advanced workflows. And we need to make sure that there's a base of talent who understands Workday worldwide and these solutions that we're describing helps us create that global talent community. So product-led flywheel, developers, marketplace adoption ultimately long-term pipeline.

The final pillar and the crux of that commercially, you folks just saw, and this is really the secret sauce. I mean, this is the moat right here is lawful, right, and the ability to map to our guardrails. Anybody can wrap in LLM, I think that's pretty clear at this point. Nobody else has 20 years of HR and finance logic that is driving core business workflows for companies at the scale and import as Workday. It's just a fact. Agents with a capital L -- sorry are Lawful when the reasoning and the execution run inside of the platform that governs it. In other words, the reasoning has to sit next to the system of record. And I'm excited to share the work to agent harness, which is what does this is now GA, the trusted run time for enterprise AI.

So walk into some of the details on this. Now I want to be clear, this is unlike MCP, some of what you saw before. This is about keeping the execution and reasoning on Workday, sort of the token path, what we sometimes refer to as the better path. This underpins every agent in Workday, by the way. So every demo that you've seen, all of it runs on top of this agent harness. What does it have? Memory, guardrails, sovereign routing, sovereign governments, I talked to a lot, they need to make sure that the AI is all within the country boundaries. Full visibility into reasoning and context, all of that in one place. And what we're now doing is we're actually opening up this harness like from a tech perspective and letting folks build directly against it, right, making sure that these layers are all available directly to the customers who want it.

Now one point I want to make on context just to try and pull out the differentiation here. Imagine that you're trying to find a successor at a company of about 40,000 people, okay? 40,000 folks in the organization. You need to churn through, I don't know, 10 years of people and performance history, that's going to be about a gigabyte of data -- sensitive data by the way. And if you're using Claude or Gemini outside of Workday, you're going to have to painstakingly extract a gigabyte of context across to some other harness tool call by tool call, pulling a gigabyte of data, data that probably shouldn't be leaving Workday, by the way, and send it over the public Internet, by the way, right? With Workday agent harness you don't need to do that. The context is ambient. Nothing moves because the system of record is right next to where the reasoning is happening. This is engineering physics, and this is part of Workday's structural moat.

Now why is lawful by default giving us a moat at some other pieces here. LLMs lack business logic and permissioning. Nobody else can match executing inside of Workday. We also have platform stickiness, right? This capability -- these capabilities agent harness, for example, it locks in our core HR and finance workloads while driving high trust AI. And it also solves the #1 CIO we hear about, which is risk mitigation and this idea and this concept of lawfulness, I think -- or sorry, lawlessness. I think when folks start to see that they really perk up because intuitively, they understand how much risk there is here.

So a few takeaways for you, Open by Design, new platform consumption revenue backed by builders, this hybrid sales-led and product-led motion. Ultimately, our ambition here is to scale that ecosystem I referenced by 5x and fuel pipeline in the process and lawful by default. No one can match our HR and finance core that really drives a lot of the differentiation from the agents that run on this platform.

Now we're taking governance even further. I think you've all seen the C1 acquisition. Fun fact about this, we actually surveyed our customers about this. And Gerrit, you have a small-size survey, but 70% of them told us that they want HCM and Identity Governance combined into one system. I'll never forget, I was on the phone with a mining company and they told me -- the CIO told me it was, "Why are you making me buy a second system for this? Like this should be one system." And I took that as many months ago, and I was like wow, this is -- there's something really here because identity is so central, as you can probably see to sort of this lawful lawless piece. It's all about identity at the end of the day. And Workday, as Aneel has said, is the upstream provider. It is the source of truth from which identity derives.

And so we're doing that today for humans, but as we look forward to AI, when we look at the growth of nonhuman identities, they're going from about 1 to 50 to like 1 to 70-ish. In other words, 70 nonhuman identities for every single human identity. That's the projection over the years to come. This acquisition puts us in a really incredible spot to start to capture value around how can govern that in conjunction with the rest of the org chart and the rest of the business processes that we provide on the HCM side and do it all with one solution.

So super excited. Together, we're going to become this identity governance and security enforcement layer for not just people but also for agents and do that across the enterprise. So for customers, what this concretely means is no more accounts with keys to the entire enterprise universe, right? Permissions get rightsized to exactly what's needed, exactly when it's needed. One platform, one set of rails. That's the platform opportunity.

And I think with that, we're going to hand it over to Rob. All right. Thanks, everyone.

Hi, everybody. Good afternoon. Great to be here. I am so excited to be able to take what you've just seen to market. And you can see from the keynote today, our customers are really, really excited.

So I'll walk you through our go-to-market motion, how it's evolving and share a closer look at our customers journey as they adopt our AI solutions. So let's just jump right in.

As Zane and Gerrit shared, our total addressable market is substantial, spanning both new customer acquisition and expansion of our existing customer base. And on the ground, I can tell you, almost all of my conversations, our focus on AI APIs, data cloud and how this connects with finance and HR.

To capitalize on opportunity we're seeing, we're sharpening our go-to-market focus and investing across the following key growth areas: customer base, AE, COE, medium enterprise and global growth. Customer base expansion remains our single largest and fastest route to revenue. As Zane shared earlier, we are on track for AI to represent over 50% and of our incremental customer base ARR for this year. We're committing substantial go-to-market resources to capitalize on the deep trust platform stickiness we've built with existing customers. And this investment is broad-based within our customer-based team, but it is strategically weighted towards larger customers.

This is where we see the highest expansion potential and the most immediate predictable pathway to cross-selling and growth, particularly as AI adoption accelerates. We're not just adding sellers though. We're also adding specialized COEs to incubate, scale and mature our growth products. Our current areas of focus are on Sana if you didn't get it, talent, platform and spend across both organic bills and acquisitions. The COE is partnered with account executives and work across the complete go-to-market motion, selling life cycle, driving real execution, deal execution, strategy, enablement, evangelism, demand generation, marketing and customer insights.

Our 4 deployed enterprise architects work closely with our customer pilots during the sales cycle to activate the agents and accelerate enterprise AI adoption. Partners are key. We're empowering the GSIs such as PwC, Accenture, Deloitte, KPMG, to build differentiated IP and AI offerings that reinforce Workday's core specific to industry, personas and geography.

Over the past year, we have sharpened our focus on the medium enterprise segment. First, we focused our ME upmarket land team on the category of 500 to 3,500 employee segment. This is our sweet spot. And we've been more intentional about this. As a result, we've seen improvement in win rates and an increase in net new deal sizes nearly 20% year-over-year.

We also simplified the packaging and implementation model and expanded Workday Go into more than 2 dozen markets. We're seeing good momentum as we continue our rollout and expansion, including strong win rates and faster deal cycles. In Q2, Workday Go volume increased more than 5x over Q1. And within the ME customer base team, we have increased our capacity and aligned our teams with the COE sellers that I mentioned earlier. This is driving nice uptake of AI solutions within our ME segment. In fact, our customer expansion rates in ME are very similar to what we're seeing in LE.

Switching gears to global growth. We're seeing strong performance out of certain markets like the U.K., Canada, Japan and parts of Northern Europe and ASEAN. To sustain this global momentum, we're taking the following actions. We opportunistically adding capacity in high-performing territories. We're opening up new markets targeted at international markets, where we are scaling our value-added reseller program. We launched our VAR program in Feb of 2026, onboarding 20 unique partners now reselling across 14 countries.

Workday's AI is grounded in deep enterprise context, speeds up the customer's part the value by combining business logic, unified data and strict governance. We are seeing strong uptake of AI across several areas. In total, 25% of our core customer base has adopted one or more SKUs, representing $600 million of ARR, and that's up from just over 10% of our customers a year ago. We also see more repeat buys. This is a very strong signal of the value that our customers are achieving. And as Zane mentioned, the monetization we are seeing is driving a healthy balance, as you can see from this slide. The growing base of our customers build a flywheel of value statements that we can leverage.

In addition to building commercial momentum, we are really pleased with the adoption we're seeing across our newer initiatives. Over 50% of customers have signed our AI terms of service, and we're beginning to use -- and they are beginning to use their entitlements, and we see a clear path to 75% over the next few quarters. We have more than 125 customers and partners in our EA program for MCP, which is now in GA. We've already signed our first wave of customers on the Workday Data Cloud since our launch a couple of weeks ago with a rapidly building pipeline. We've also signed 18 of the most significant brands in the world in our Sana Enterprise Lighthouse program. These are companies that are deeply co-innovating with us over the next year and have agreed to service the references. We forgo 1 year of licensing, but we are thrilled with the partnership here and believe it will lead to much larger long-term opportunities.

While much of the $600 million of AI today is sold via traditional subscription license, a growing mix is coming from Flex Credits, a usage-based pricing model we announced last year at Rising. These are typically 1- to 3-year commitments from customers that are tied to measurable outcomes, not token consumption.

For example, when we sell Flex Credits tied towards a recruiting use case, it's based on the number of applicants. We are very early in the Flex Credit model but momentum is building rapidly. We have nearly 300 customers that have moved on to Flex Credits, including nearly 200 customers we closed in Q2 alone. There are a couple of things that's happening in the background that should drive an accelerated uptake of Flex Credits as we move forward.

One, our first-party agents continue to mature and we are accelerating the amount of innovation we are bringing to market. You could see it year-to-date. Because of the Flex Credit model, which is fungible across our agentic portfolio, the more solutions we bring to market the more measurable value our customers will get and the more appealing the Flex Credit model becomes. Two, we are opening up our MCP and Data Cloud programs into GA right now, which should also lead to increased momentum as customers leverage the power of the platform.

So let's take a look at 2 very distinct customers. I think the one might be the same as Gabe mentioned, putting Workday AI to work to reinvent how their businesses hire, operate and scale. Our first story is about a health care company with nearly 70,000 employees. They turn to Workday to optimize their data in a runway for AI, enabling them to maximize resources and focus their dollars where it matters most, the patient. In FY '25, they adopted Hyatt score, which enabled them to develop the AI governance strategy in line with Workday's responsible AI model. And that foundation paved the way in FY '27 to add Flex Credits to get them capacity to roll out solutions, including Self-Service Agent. Ultimately, AI adoption across this journey has driven a 50% uplift in ARR.

Our second story is a large manufacturer/mining company in Asia Pacific with over 60,000 employees. Initially, they came to Workday to solve challenges with manual recruiting tasks, long hiring cycles, excessive administration workloads for their managers. What started as a single HR platform deal has grown into a strategic partnership, a cycle of investing, measuring the result and then expanding. In FY '26, they adopted Hyatt score to reduce the burden of manual task on talent admins. 9 months later, they closed a deal for Paradox to layer conversational AI and candidate nurture on top of it. And today, we are seeing continued investment outside of talent with Eversoure, Extend AI and Sana. The payoff, they've automated scheduling, improve candidate communication, reduce hiring time, cutting the time of managers spending on recruitment in half, and their AI journey has driven a 40% uplift in ARR.

This one I'm really excited about. In the last few minutes, I want to talk and quickly touch on the opportunity that I and I know the teams are very excited about. The CIO is an emerging distinct buying center alongside HR and finance. This dynamic is one of the many reasons I'm excited about today's announcement. AI is pulling them into the Workday conversation in ways we haven't seen before and this represents a huge opportunity for Workday. To capture it we'll be focusing on the CIO persona with our innovation offerings like Workday Data Cloud, Extend and the AI agent use cases.

Since we announced Workday Data Cloud last year, we've moved from concept to GA in less than 12 months. We see tremendous interest with more than 1,000 enterprise customers of ours that are leveraging Snowflake and Databricks for data warehousing, and have already closed 20 deals with rapidly growing pipelines. Building up on this momentum, we're also expanding our partnership with Google Cloud and AWS to deepen integrations and broaden our reach across cloud ecosystems. The deal economics are already proving out. Platform adoption is driving meaningful ACV expansion opportunities for Workday. We are seeing growing interest in Extend AI to build both traditional and agentic applications on Workday. And there are 2 different types of opportunities here.

Convert the more than 1,000 customers from traditional Extend towards Extend AI. This drives a roughly 20% increase on average to what they were paying with the traditional Extend license. Two, drive first-time platform customers, and this is the biggest driver of growth with Extend AI. It's also worth noting that for customers to leverage our agents ready tools at MCP server, they need to be licensed on Extend AI as the first step, and this is helping drive momentum.

We are just getting started here. Nearly every customer I meet with is excited about leveraging our platform and MCP for certain use cases. Our MCP program is in GA, and I believe this creates a tailwind moving customers on to Extend AI and Flex Credits. And Sana Enterprise is a central AI orchestration engine across the enterprise. And you all heard exciting announcements this morning about C1.ai, which opens up a much broader opportunity with the CIO around identity governance, a top priority for many customers we believe only accelerates with the proliferation of AI. It's an incredible opportunity for us to leverage our trusted position within the enterprise and C1's innovative technology to drive adoption.

So to bring it all together, the runway ahead of us is vast. We're excited about it. Our teams are excited about it. You can feel the customer excitement. We're excited about how this go-to-market motion will evolve over this year, and we're confident that this will position us to drive rapid customer AI adoption and capitalize on a TAM that's growing both the land and expand opportunities.

So thank you for your time today. And with that, I want to invite back the leadership team, and we're happy to take questions. Thank you.

We are going to go around the room. I know there's a lot of people, and we're not going to get to everybody, so I apologize in advance, but we're going to -- why don't we go [indiscernible] on your side, we'll start with Alex. If you could just say your name and then make sure they can see you.

Alex? The button turns it on. Broken tech.

Thank you guys for hosting. Alex Zukin here with Wolfe Research. Really inspiring presentation kind of at all levels, the tech, the interface, the modules, the TAM expansion opportunities. I wanted -- Aneel, maybe to ask you, it feels like all of -- there's kind of a big debate about headless becoming the new kind of interface layer for interfacing with enterprise workflows as much as applications or software agents. What is -- what do you anticipate those economics to look like? Some of your other kind of compatriots are leaning heavily in kind of, I think, as you guys are on the headless strategy. And consequently, they think they're able to drive significantly higher unit economics from that strategy. And then there are some others that are leaning very hard in the other direction. So how do you expect this balance of trade to kind of result when you're interfacing with customers?

And then maybe, Zane, for you, I know we're not doing midterm or long-term targets here. But maybe just the conviction, given the amount of innovation you've demonstrated in maybe the sustainability of double-digit growth as an aggregate kind of concept.

Sure. So I guess at the highest level, I don't think anybody really knows how it's going to play out between headless and your own front end. Now I think a lot of our competitors and peers don't have anything like Sana. So they default to headless because they don't have their own prompt-based AI-driven user experience the way we do. And I'd say the other piece is we are an HR system. So we do naturally touch every employee in the company, not just a group of employees, maybe in sales or marketing or services. As HR, you touch every employee in the company. So I do think we have a different strategy.

Now if people want to do headless, they work through our APIs. And my expectation is we'll be margin neutral. The beauty of APIs requires a lot less sales cost. I'd always like people to use our user experience. But if they don't, our guardrails that are exposed to our APIs are super valuable. That's the real value of the underlying system of business process, of security model, of org chart. So I kind of think we win either way. But I think so far, what we're seeing is customers really like our strategy where we have the user experience that's best-in-class. And that's only because of Sana.

And just to add today, we didn't announce APIs in Cloud. We announced Sana in Cloud, right? So this is an [ AI-to-i ] integration, which means the reasoning intelligence happens on the Sana side, right? So I think the interface is a bit over blade and relevance. The real question is, there is the reason.

There's a reasoning to happen.

And I'd just add, getting beyond FY '28. We intentionally wanted to highlight for all of you the incredible work that this team is doing on these agents and the receptivity and adoption that we're seeing from the customer base. As Aneel put it best earlier today, our intention is to focus on growth and to drive growth, and we're excited by this consumption model. I'd end it there, but our intention is to lean in and continue to grow the business. So that's the intent. As Aneel said, we'll see how things play out. There's a lot of interest and a lot of adoption to come, but we feel like we've got a tremendous portfolio to drive that.

This is John DiFucci from Guggenheim. Gerrit, you said that other than coding, the AI breakthrough hasn't really happened or not yet anyway. And it took a long time for the large enterprise to really adopt Internet-based applications. And Aneel and Dave saw that coming and got into it before it happened and actually, was ready for it when it came. I guess, how do you think this market evolves for the use of AI by businesses and how is Workday positioned differently, and this is really, I think, for Gerrit and Aneel differently for this major technology paradigm shift than the last one?

Do you want to start? Should I start?

You're smarter, you start. If you haven't figure out he is smarter.

This is smart way of handling that question actually. Yes, the reason is that for AI transformation to really happen, companies need 2 things, right? One is they need to actually understand how to transform their existing work, right? The success in AI is not in applying it to the work you already do. And the reason why we see so much success in coding is we code to a large degree of language. It's a very fiber problem. There is high proficiency in the models per se. There's not a lot of domain specificity to it. There is so much code in a public web that you can train models on. And it's mostly driven from a very simple business process, right, you write code and you submit it and you should review it maybe in between and then you deploy to production. So it's a very simple workflow.

Now if you take any other enterprise workflow, right, which brings together multiple functions. For instance, finance and HR, you have hundreds of steps, thousands of variations, different people interacting with each other. And one key part, which is why we announced Work Intelligence today is actually getting to comprehension and to understand and understanding about how does work actually mapped to the language of AI models, which is tasks. Models fundamentally don't think in jobs and job profiles, that's like anthropomorphizing that space. They have task proficiency. They can do one thing really valid, maybe another thing. But I think in the middle, they can't do renewal, right? So you have to extract all of the things they can do from the things they can't do and maybe also the things they shouldn't do. And then you have to project this on a new workflow configuration inside of an enterprise. That is the fundamental step for at scale AI adoption and that's what makes Workday so strategic, right?

Because fundamentally, you talk about an HR people and organization transformation first and foremost, right? Usually, as saying keep saying, technology comes last, right? First, you actually have to change the business and the process. So that's why Work Intelligence is such a big stepping stone. And then secondly, and this is why C1 for us is such a big part of our strategy is that even if you have an understanding of where you want to apply AI to, now the question becomes, how do you do this in a secure, reliable and lawful way? And the problem is that none of the recipes that you have in classical ERP. Let's just say how we thought about ERP, enterprise resource managing, right, the builds of material and the supply chain and blah, blah, blah, right? Everything that was built for that doesn't work for AI. The unit of work is different. The cost model is different. You need to have no real-time economics based on real-time spend against tokens because it becomes such a big part of the operating expenses.

And you need to think about security, right? How do you do this and stay compliant. How do you do this and stay safe. So you have to fundamentally rethink what the platform and enterprise who runs on, which used to be our repeat actually does. And this is what agent system of record, C1, right? This is why we are bringing all of these assets together because we think with that work transformation, also the business applications are going to reconfigure themselves around agentic identity, agentic work and agent to human collaboration.

Yes. I guess the only thing I'd add to that is, just look where enterprise -- enterprises have adopted AI and specific to our world, kind of on the edges so far, recruiting, not super high risk, and it's a pretty contained environment. Same thing with what we're doing with contract intelligence. This next wave of agents actually go deep into the bowels of an organization, and it requires real transformation. The best place to start is at the top, which is why Sana and Self-Service Agent or the Concierge product is so important. But then you start drilling into middle.

The financial audit agent, which is my favorite agent because it's going to automate the financial audit process, will be really powerful, but that will require a lot of workflow changes.

And that makes a ton of sense. And one -- my understanding is within Workday, you're all using the Sana interface.

Yes excessively. Same worry sometimes.

We worry about token usage. But I think most of us here probably are Workday customers. I know we are. And I'm -- I think, like you said, it starts from the top, like, once we get that, when will we get that?

You have it now.

We have it now? What are the...

Today. Well, you have to turn it on, right? So it's not the standard home screen or the home experience for Workday is Sana.

Okay. Great. The example you showed, Gerrit, just taking...

Just call your IT team and tell them to turn it on. Tell them the button turns it on, works all the time. Just click the button.

Kirk Materne with Evercore ISI. Thanks for the day. Gerrit, Josh, Gabe, you guys gave a lot of great really intuitive examples of how agentic sort of integrate into the platform. So the question is for Rob, which is you guys have a lot of customers that are using Workday that are paying you good dollars to use the system as is. How do you make sure that you transition these new -- the value created in a lot of these newer products into kind of incremental revenue in those customers. Some of them are used to buying per seat to Aneel's point, they have to rethink sort of the processes around this.

What is the opportunity over the next 12 months is it sort of you just have to sort of not give away but see the products in them so they start to see it first and then you monetize after the fact. It seems like there's a lot of avenues to pursue. I'm just kind of curious where you think the lower-hanging fruit is and how you get there.

It's a great question. I would say the appetite for our customers has evolved rapidly over the last 6, 7 months to understand how. First of all, AI SKUs fit into it, how we build the recruiting end-to-end solution for them and bring that to market and determine the value. And so it's really value driven, all of these equations. We have to change the sales cycle that was traditional seat-based into value-based selling type and it really showcase customers how they get the value. The big thing for existing customers is this is not like you sold software previously. Will you sell other values x and you're going to gain it in 24 months and just wait and see, and it's going to really feel good. This is about showcasing in the moment, like getting these agents activated, deployed. We've taken an extremely thoughtful approach, I would say.

Like when we brought Self-Service Agent to market, we work with 10 of the largest companies in the world, bringing the most complex self-service skills into the market and bringing them live on a day to -- actually a week-to-week basis. And so as we get that harder, now we have an opportunity to scale it and scale it. I think that's how we will drive it across all of the customer base. When you implement with new opportunities, we changed the sales cycle because the value equation now becomes agentic as well and we build a new value equation into that customer base.

I would say the seat-based pricing is kind of the baseline and everything in the future is going to be value-driven. Managing the cost model for the customers and on behalf of the customer, I think it's really critical to be successful.

Tal Liani from Bank of America. I have 2 questions. AI is growing. Also, you're focusing on medium-sized enterprises, but still subscription is slowing down. So I'm talking about the next year, the next 2 years, can you define the strategic challenge why is growth decelerating, subscription growth decelerating? What's happening in the market that we don't see stabilization or acceleration before AI?

The second question is about AI. I see a lot of similarities between your strategy, Salesforce strategy, ServiceNow strategy. So customers will have to deploy if they deploy all of you, they'll have to deploy multiple identity solutions because each one of you has a solution, multiple interfaces because you have Sana, they have Slack and others. How is this going to play out? Are they going to deploy 3 identity solutions and 3 interfaces solution? Or are they going to deploy an external one by someone like Microsoft maybe to harmonize everything. I'm trying to understand from which direction this market is going to evolve?

I'll answer the last part first, having spent a long time in identity, HR is the system of identity. We built the agent a system of record to couple with our HR system. There's no question, no will debate you that HR is the source of identity for all enterprises. Where else do you get your source of identity. ServiceNow doesn't have it. Salesforce has it for salespeople and the people that are in their system. But the one thing about every company is that everybody in the company is an employee, and that's where you get the identity. And we were architected for that. That's why I don't think they're going to be multiple -- there might be multiple identity systems in the company. There'll only be one source of truth, and that will always be the HR system for employees and the agent system of record for agents and then the governance of what those employees and agents can do, which is what C1 does.

So I don't really think it's -- I don't really think it's that complicated. I just think we have the winning hand because we are that core system of record for identity.

And as a matter of fact, right, today, customers have multiple identity systems and the HCM systems sits upstream from that. And the multiplicity in identity system today is the problem they're trying to solve for.

And that's where the governance comes in, which is why C1 is so powerful because we have multiple identity systems, one HR system for identity, multiple identity systems that are authenticating and giving access to applications. Well, then how is that governing in a centralized way, and that's where we come in. So we basically think about Workday surrounding the IDPs. What was the other part of the question?

To understand the growth deceleration.

So without talking about acceleration rate, I mean, I'll leave those things to Zane. But I will say the thing about medium enterprise is, it is a massive part of the market. It's always been important to Workday. The biggest issue we've had historically is that the cost of our deployments have been more expensive than folks like UKG as an example, cost of software close to 1:1, but our deployments might have been 2 to 3x the expense of UKG partially because they subsidized deployments and partially because we built a highly configurable system for large-scale enterprises and going through those choices, we're hard for medium enterprise customers.

With the deployment agent that Gerrit and team have come out with, we dramatically reduced the cost of the deployment. Completely changed it. We've already seen it in the win rates as people start using the deployment agent and I actually think what's going to happen is you're going to see UKG customers leave UKG and come to Workday because UKG doesn't have a strategy for agentic technologies. So if you're a company that wants to embrace what's happening in AI you get a really fast conversion over to Workday, and then it opens up all the AI capabilities that we have. I think you're going to see that happen across the board.

And I'd just add to that. The model is changing and what you've heard today is as we move more towards the agentic towards consumption, and that value-driven opportunity. It takes time, and we're doing things like lighthouse programs, and we're really driving future growth and trying to get that flywheel going. We've been very transparent around renewal cycles, M&A lapping year-over-year and things like that as well as international, which at times has been a huge propellent for accelerated growth and at other times, it hasn't.

So you take the noise out, I'd say, as we continue to move this model more towards what you saw today, we're very excited about that medium and long-term opportunity that you've got to go into that and customers have to adopt that.

Mark Moerdler, Bernstein Research. In the last year, you've come really far on the technology and the capabilities you've shown today are very impressive compared to what existed before. And I'd argue you've even done that on the vision side with the explanation of lawless versus lawful and trying to explain the value.

I would like you to answer the question. And I know, Aneel, you're going to have a thought, but I think others might on the question everyone asks us. And that is when you expose your data, your system of record, your semantic knowledge through to someone else's Claude or someone else ChatGPT's front end. How do you assure that you maintain the customer relationship and the economics on a go-forward basis rather than the front end being the capture of that upside in that economics?

Well, I think simply for those tools to work the way you described, they have to go through our APIs. If you just go directly against the data, you lose all the context. You have no idea of the business process, what guardrails are built around it. We have that example of query the database for the top 5 sales reps where the Northeast VP. Well, without knowledge of the org chart, without knowledge of what you can see is that Northeast VP, you'll get top 5 sales reps in the world. That's a very basic example, and Gabe came up with that example.

But to describe that situation, that's the headless situation. They have to go through our APIs. And those who are fine with us because we get paid that way, too. I just don't see HR and finance customers going around APIs and taking the risk of screwing up payroll or screwing up financial audit because they didn't have the context of the underlying business process are yet to meet a customer that wants to do that.

And one other thing I'd add to this that I think is maybe at risk of getting missed here is, as Aneel said, yes, we have to -- they're going through our APIs. But the laws and the rules and the governance that those APIs provide are actually being provided through the core HR system. And so one does not exist without the other. The value of the APIs exist because the core system is providing the tenant configuration, the business process configuration, all of the approval workflows. And so it's those 2 things working together that allow us to maintain that direct customer relationship.

And look, if they're coming in through our AI APIs or MCP surface, as we've said, we're going to monetize that as well. But I think over time, there's also another dimension of this, which is we look at a progressive upgrade possibility where folks can start off on an MCP surface in a true headless fashion, maybe progress towards using subagents. What we've talked about with the Sana and Claude piece and then ultimately progress towards using the full Sana AI workspace. And we think that's going to be a use case by use case journey, but we do see the ability for customers to sort of migrate across different paths, which gives us optionality to make sure that we are controlling the customer relationship.

Okay. We're going to do just 2 more questions. I know we've got Siti over there and we've got Dan over here, and then we're going to break for a happy hour after this. So go ahead, Siti.

Siti Panigrahi from Mizuho. There's a lot of innovation today. It's great to see. As you know, most of the time, it's a customer-driven innovation that's an enterprise application we have seen, but it seems like what you're today showing is a lot of new innovation, you are trying to push to the customer, like how the work is changing. So how are you going to sell this to customers? How are you going to convince them to change the way they work and so that what you're selling and so that to leverage your product, it's kind of -- it's a new innovation that you want to change their -- the way they work.

But I think I would categorize it differently, actually, in the opposite, it's the customers, it's the market coming to us. And every company on this planet right now ask the questions, how do I transform with AI? How do I become an AI-led organization? And as Aneel said, you're right, based on the many conversations he's having constantly, right? They are turning to Workday as the source for 2 of those elements, right, as an HCM system, how do I do structurally and as a software vendor, right, what capabilities can you give me to drive this in HR and finance.

So it is incredibly customer-centric because you tell me the organization who is not trying to figure that out. And what we do is that we are not then you just taking this trivially but we actually use the opportunity of AI innovation and rethink at the core, every process, in HR and finance and in IT to completely transform it through the use of frontier AI models. And this is what you have seen, right? It is reimagined based on our domain understanding. But based on the request of the market of transforming...

I'll just add to that. We listen to the customers. We have 20 agents. Maybe some of them are not the right agents, but we'll keep iterating and learn from that process. It's getting back to that start a mentality in terms of innovating with our customers. There's nothing on the road map that a customer hasn't asked for.

Dan Jester, Bank of Montreal. First of all, I've used the Self-Service Agent. That's great.

Yes, you guys are the best. You were the first ones to really drive it. Thank you.

Thank you for going for the school of [indiscernible].

So I wanted to ask the question, Aneel, you had talked about this. The first generation of agents are a little bit in a Sandbox like they're defined. The next generative agents are going to actually require business process change by your customers. So can you just give us a sense how your customers are actually thinking about that? What's the role of sort of the ecosystem and partners driving that change? How much can you do and help versus how much it really makes you have to wait until the customers are ready?

Yes. So I'll push the ecosystem question to Rob. But I love Joel to answer the question on. I think actually the Self-Service Agent and how you deployed it, Joel was front and center with that. That is actually how we're learning from customers and how it's not an edge case like recruiting, but actually something that is central to how organization works.

So yes, if you think about something as the sort of this copilot experiences, at best, you will make someone 10%, 20% more productive. And as we position to this more out-of-pilot ask experience, you're really reengineering the entire workflow to be handled by these agents. And we have a few different ways in which we support that. First is our first-party agents. You can think about there as we've done the sort of full last mile. You can just deploy these agents, they're turnkey. We've sold them soup to nuts.

The second is the experience that we have in the agent pillar, where we offer you templates, but you can build any custom agents. And how I see this play out is for customers they'll have hundreds of thousands of agents ultimately. And the work of the employees will be doing the sort of meta work of creating these agents. So you will be doing less of actually carrying out the work and more building the agents that do the work. And so as that role shifts, your role shifts towards redesigning the processes to be handled by these agents and be increasingly handled by these agents.

And so first generation of a lot of the systems, I think was a lot sort of 10% productivity gains. I think when you start seeing orchestration of agents handling the work with increased autonomy the workflows will need to change entirely. And first, we want to build the best sort of pre-built experiences for that, that are turnkey, you can just turn on and run with, but also enable you to build thousands of that on the Sana agent builder products.

And just on the ecosystem, just like we've had it changed dramatically in the last 12 months. I think all of the ecosystem players, whether [ UGSIs ] whether you are local providers, whether you are BPO providers, your business is changing and you better change fast. If you look at implementations, typical way. You don't see configuration as an important path anymore. So what's left? The business model innovation is what's left. And so I think we will be in the next couple of years going through a major shift in business innovation and new business models will evolve and we feel really good about where we sit.

Okay. I think we are going to end it there. Thank you guys so much. That does conclude the Analyst Day 2026.

Thank you. Thank you. Thank you.

I appreciate you guys all coming out.

Thank you, guys.

Ladies and gentlemen, welcome to Workday's Second Quarter Fiscal Year 2027 Earnings Call. [Operator Instructions]

I will now hand it over to Justin Furby, Vice President of Investor Relations. Please go ahead.

Thank you, operator. Welcome to Workday's second quarter fiscal 2027 earnings conference call. On the call, we have Aneel Bhusri, our CEO; Garrit Kazmaier, our President, Product and Technology; Gabe Monroy, our Chief Technology Officer; Rob Enslin, our President and Chief Commercial Officer; and Zane Rowe, our CFO.

Following prepared remarks, we will take questions. Our press release was issued after close of market and is posted on our website where this call is being simultaneously webcast.

Before we get started, we want to emphasize that some of our statements on this call, particularly our guidance, are based on the information we have as of today and include forward-looking statements regarding our financial results, applications and solutions, customer demand, operations and other matters. These statements are subject to risks, uncertainties and assumptions that could cause actual results to differ materially. Please refer to the press release and the risk factors and documents we file with the Securities and Exchange Commission including our fiscal 2026 annual report on Form 10-K for additional information on risks, uncertainties and assumptions that may cause actual results to differ materially from those set forth in such statements.

In addition, during today's call, we will discuss non-GAAP financial measures, which we believe are useful as supplemental measures of Workday's performance. These non-GAAP measures should be considered in addition to and not as a substitute for or in isolation from GAAP results. You can find additional disclosures regarding these non-GAAP measures, including reconciliations with comparable GAAP results in our earnings press release, in our investor presentation and on the Investor Relations page of our website. The webcast replay of this call will be available for the next 90 days on our company website under the Investor Relations link.

Additionally, the prepared remarks of this call and our quarterly investor presentation will be posted on our Investor Relations website following this call. Our third quarter fiscal 2027 quiet period begins on October 15, 2026, and Unless otherwise stated, all financial comparisons in this call will be to our results for the comparable period of our fiscal 2026.

With that, I'll pass the call over to Aneel.

Thanks, Justin, and thanks, everyone, for joining us today. It's hard to believe I've been back in the CEO seat for 6 months. Time flies, we're having fun, and I'm having a lot of fun. This is a fun time to be back in the tech industry. Q2 was another strong quarter, and AI played an increasingly bigger role. AI products alone drove more than $100 million of new ACV, which accounted for more than 25% of all new ACV closed in the quarter and is starting to lift our core business, too, including our win rates. We had commercial success with AI in the quarter, including strong early returns with Flex credits, and we expect this to accelerate going forward. But I'm watching more closely is adoption. Today, more than 5,500 customers are using one or more of our organic agents. That's up more than 35% from last quarter.

As we continue to build organic agents on Workday, we're also deeply integrating acquired agents like those from Paradox, HiredScore, Evisort into our platform. And we've signed some of the world's largest brands to our Leidos program, which gives strategic customers Sana Enterprise free for a year. We've rolled it out to our own work made last month, and they're hooked. I expect these customers will be, too, and we know that if we deliver the value, monetization will follow. After two strong back-to-back quarters, I really like the momentum we have going into the second half of the year. Gerrit and our product and technology teams have our innovation engine humming again. While Rob and his team have done a phenomenal job building pipeline that will drive more new business. Dave will cover the numbers shortly, including the impact of AI adoption on our outlook for the second half and fiscal year '28.

I spent much of the past 6 months with customers. Last quarter, I told you I had met a single customers looking to replace Workday with something they're building internally or buying from a start-up. A quarter later, that hasn't changed. The reason is the deterministic rails I've talked about before. Our agents are lawful. They work inside the permissions, policies and business process a company already runs on. That's why our customers can trust them with the work that matters, and that's why we're seeing our organic agents really take off this year. One of those customers is BMO, a top 10 bank in North America. They piloted self-service agent with 500 employees in May and successfully rolled it out to all 55,000 employees in June. SSA gives BMO employees and managers a personal, intuitive way to get HR questions answered and work done faster and easier. And because it's native to Workday, the agent understands employee permissions and which HR policies apply to them.

That built-in context is exactly what makes this a responsible and scalable AI deployment for BMO. BMO is one of many. More customers are moving from pilots to production with our agents. But we know that no one company will build every agent. The future will be opened and CIOs need a trusted platform to connect at all. We're building for that world with Data Cloud and Developer Agent. Data Cloud lets customers use their Workday data alongside the other systems they run on, without copying or moving it. Customers see the value and demand is building. Developer Agent, which we announced at DevCon in June, makes it dramatically faster and easier for developers to build on Workday using natural language. It's one of the innovations I'm most excited about. I'll add just one thing, because I don't think it's fully understood. Workday is not just an enterprise apps company. We're an enterprise context platform. We were built that way from the start.

Agency contacts to do anything useful. Who reports to whom, what the policies are, how money moves. So whether a customer runs our agents or builds their own on top of Workday, we win either way. Gabe will go deeper on this shortly.

Finally, Rising is coming to Las Vegas, October 12 through the 15th. I have to tell you, Gerrit and his team have what me through our rising announcements, and it was loan away by how much innovation we have to show, not slides, live demos and customers talking about work our agents are already doing inside their business. That's the proof I care about most. We'll also be hosting our Financial Analyst Day at Rising, and I hope to see you all there.

To close, as many of you know, I'm an unabashed optimist, but I'm not leaning on optimism here. We're shipping air products. Our customers are adopting them rapidly. It's happening across the board from the agents we built ourselves to the ones we've acquired. This is Workday moment and never felt better about where we're headed.

With that, I'll hand it to my Vulcan Mine Mill friend, Gerrit.

Thanks, Aneel, and hello, everyone. In Q2, once again, we have accelerated our road map and added new AI capabilities across our platform. All of it builds on our unique growth model of work, and we keep moving more agents into production at scale. So let me put this into numbers for you. Nearly $600 million in ARR from our AI SKUs and that is up more than 200% year-over-year and up over 20% from last quarter.

Here is what this looks like in practice. In recruiting, more than 30 million candidates interacted with our talent acquisition agent and the automatically scheduled more than 8 million interviews last water alone. In functions like procurement and legal Workday Contract Intelligence Agent drove nearly 70% year-over-year growth in agreements processed. And NHR case resolution, more than 100 customers move Sana self-service agent into production last month. Since February, we have nearly doubled the tools and skills in the agent that run in production.

So now let's talk about three key innovation highlights from last quarter, Sana, Adaptive Decision Intelligence and our deployment and adoption agents. Let's talk about Sana Enterprise first. Sana Enterprises our AI workbench [indiscernible] HR, finance and IT to build, orchestrate and run AI across the entire end rise. In Q2, we have shipped 23 new capabilities in Sana that open up what customers can do with it. For example, our brand-new Sana Agent Builder lets any user create in action in natural language and then run it on a schedule or trigger it on a business event. Every one of those agent runs in a secure sandbox.

We now have one shared agent task inbox in Sana, where work is managed in one place, human or AI. And we have added custom MCP connectors. So Sana can connect to any third-party application out there. This innovation, it's already changing AI adoption inside and outside of Workday. Here is what we have done. We rolled out Sana Enterprise internally on August 4 and already have 12,000 active users on it. These workmates have built 22,000 custom agents in 3 weeks alone. Now this is what AI looks like when it's embedded into real work. We have also brought Workday Learning and Sana learn together into one product. It is in GA now with a learning admin agent, AI-based course generation and AI tutor for self-paced learning and MCP support as part of our open platform, and the results are clear.

In Sana, monthly active users grew almost 190% year-over-year and 78% of all published courses were created of AI. And we are taking the next major step to Sana Workday. As we have shared in the past, Sana is our vision for an eye driven work experience across Workday and beyond. With our unique meta-driven platform, we can now unlock all Workday processes for generative UI in Sana. So by work their [indiscernible] [ Gober, ] Sana's conversation AI experience will be the default home screen to Workday.

The second big AI innovation is Decision Intelligence. As you know, frontier models are good at analyzing data, but they sit on the sidelines of the operational system, they are detached from business [indiscernible]. They are working off downloaded spreadsheets, and they are unable to close the loop back to work actually happens. Adaptive decision intelligence is different. It is our AI agents for analytics and blending that runs analysis, generates plans and takes government action directly inside Workday, all based under our security model, audit trails and governance rules.

On July 31, Adaptive Decision Intelligence entered into GA. And this was one of the fastest products we have ever delivered from concept to general availability in four months, and it's built organically within Workday. Here is what we have shipped all AI agent-based, life analysis of blender scenario modeling, sensitivity analysis, recression models, version comparison and the recommendations that you can submit as government plan updates with approval, audit trails and staleness detection.

And as of today, 170 customers have already purchased it. And one AI customer told us, it gives finance teams answers they can actually defend. And you're not stopping here. We just kicked off the early adopter program, connecting adaptive decision intelligence directly into Workday Finance, to give it access to general lines, planned data and to our accounting center. Our customers can now tie AI to financial outcomes with transaction level evidence.

And next, we're going to move to the workforce analytics, connecting live people data with financial decisions in One AI agent experience. And our third AI highlight for this quarter is deployment and adoption agent. Deployment age momentum has been dynamite. As of today, we have more than 4,600 customers, almost 24,000 users and query volumes surging nearly 500% in Q2.

Mohegan Gaming is now live, and Mohegan says the downstream impact is priceless. Deployment age and deploys updates so rapidly that employees remain focused on their core business. And our long-term target is reduce deployment time with this agent by 80% to 90%. And once customers are live, adoption agent helps keeping them ahead of what's new. It surfaces the releases that matter and recommends the next step for their environment. Adoption agent entered GA just last week. We had more than 200 customers signed on in the first 3 days alone. With 20,000 release notes evaluated and achieved a 94% customer satisfaction rate. One customer solution Health used adoption agent on their latest release. They ran it across every functional area, and they have cut that release time down by 70%. And here is why this matters so much faster deployments, faster adoption and a lower cost to serve a feeling Workday goes momentum in the medium end price.

Workday go win rates and deal volume are both increasing in Q2. And here is one more note for you. Travel agent and Sana for ITSM have both moved into early adopter with the first customers already boarded. And the bottom line of this is this. The broad model of FERC is not a thesis. It is in production, it is compounding and you can see it in the numbers. A key part of this question is our open platform strategy, unlocking the power of Workday for our customers and for the entire ecosystem around us.

I'm going to pass it to our very own Gabe Monroy, Workday's CTO and the leader of our technology platform to share our progress here. Gabe, take it away.

Thanks, Gerrit. It's good to be here. Building on what Aneel said, it's almost as the Workday was built for AI 20 years ago. Having one day to model, one security model, one version for every customer from the start is an incredible advantage, and it's a big reason why I came to Workday. Over the last several years, we've modernized that foundation to handle the complexity of running AI at scale. We built tools that can query Workday using industry-standard analytics solutions and an MCP layer, so AI models can talk to our APIs in natural language. But access is only half of it. The stakes are different in the world of people and money. That's why we've updated our security model and built the agent system of record. So our agents act with the same permissions, rules and controls our customers already trust.

And Asian isn't just the model. It's identity, permissions, guardrails, logs and governance, all working together. That's what separates a lawless agent from a lawful one. A lawless agent will attempt to take action on its own. A lawful agent takes action because the system allows it. Inside Workday's deterministic rails, every step is checked against the security model, the business process framework and the compliance logic before it runs.

Now in Q2, we advanced our platform strategy in three ways, making it more open, extensible and lawful. Starting with being open. CIOs aren't going to settle for a single rigid AI stack. So we built Workday with three paths in. Developers building custom agents on their own AI stacks need safe governed access to Workday, both for querying data and for taking action. Data Cloud gives external agents and partners like Snowflake, AWS and Google, zero-copy access to HR and finance data. In Q2, we closed 6 deals with all customers choosing our premium Data Cloud Pro Edition. Data Cloud remains on track for GA in Q3. And at DevCon launched agent ready tools over MCP. These agent APIs allow third-party agents on any stack to safely get work done inside Workday, like updating an employee record or approving an invoice without breaking corporate rules.

Agent Ready tools are now available to early adopters through Workday Extend Pro with GA in Q3. Today, more than 1,600 customers use Workday across third-party services like Teams and Slack as well as Copilot and Gemini, which we added in Q1. Over 100 of those customers are already leveraging self-service agent directly in the tools they use every day. Whether a manager approved spend or logs and expense right in chat the underlying policy checks in compliance stay securely anchored inside Workday. And some work simply outgrows the chat bubble, travel and IT service management, which Gerrit mentioned earlier, they'll need a canvas. That work was in Sana, where we own both the reasoning engine and the experience. Whether a customer uses their own agent uses our agents with their own front door or Sana, we meet them wherever they work. And because all of it runs through Flex credits, we monetize every action happening on our rails, regardless of the path.

In Q2, custom apps built on Workday spend grew over 90% year-over-year. Even when building required specialized engineers. Our new developer agent removes that bottleneck. Now builders can generate policy-compliant workflows using plain language directly inside tools like cursor, codecs and quad code. This takes development time from weeks to minutes and opens up the platform to all builders. Customer uptake was intent. Developers have built more than 3,000 custom apps and agents since DevCon.

As we expand these plain language tools across our user base, we fundamentally shift our business model. You don't have to be an engineer to build on Workday. Finally, none of this matters if the transactions are not lawful. In Q2, we launched Asian Passport. It gives security teams a verified auditable record that an agent was tested against critical risks before it deployed and is monitored after. Cisco joined as a launch partner, bringing Cisco AI Defense to test agents against leading standards and protect them in production. We'll add more security partners and out of station stamps in coming months, giving CISOs the confidence required to write higher value work through Workday.

In short, our customers can work where they want build in plain language and trust every execution.

With that, I'll hand it to Rob.

Thanks, Gabe, and hello, everyone. Our customers trust Workday with the most important parts of their business, and we see it in the field every day. Companies on legacy HCM and ERP systems are realizing they can't get value from AI with modernizing their core. They want one platform they can trust with security and reliability, which is a big driver behind the demand for Sana Enterprise. AI is amplifying the value of the software stack customers already trust. You can see those tailwinds in our Q2 results. With more than 65% of the Fortune 500 running on Workday, we continue to bring on some of the world's leading brands.

In Q2, we formed new relationships with companies such as KPMG U.S., Danske Bank, BWX Technologies and Guidehouse. In medium enterprise, as you heard from Gerrit, Workday is taking off. Customer volume increased more than 5x over Q1. Across large and medium enterprises, AI is a key reason companies are modernizing their Core in Workday. In fact, over half of our net new wins in Q2 signed up for 1 or more AI solutions, and we're seeing even faster AI adoption across our base. As customers leverage our unmatched HR and finance context to truly unlock the value of AI in the enterprise.

Genesis is using our new financial audit agent, a Chief Accounting Officer described it as a first step towards the dream of getting a touchless audit. Seminal hard rock services is using payroll agent, automate complex back and compliance calculations for 28,000 employees. In [indiscernible] investment, one of our first 20 customers back in 2007 added Sana Enterprise to power an AI layer over the employee experience. This bolds on the other AI agents they recently added, including recruiting, contract intelligence and planning. Sana Enterprise had an exceptional launch in Q2. New customers included AstraZeneca, Novartis, Caterpillar and Delivery Hero Group. Since we combine Sana Learn with our core learning management system, we've seen a sizable jump in our overall learning business, which more than tripled quarter-over-quarter. Adaptive Decision Intelligence helped drive strong performance across the entire planning business and our ecosystem is moving fast with it. Partners have helped build more than 100 industry-specific use cases in a little over a month.

In late May, we made Sana Workday and Sana Health Service available to all our customers on our AI terms of service. That drove a surge in the number of customers that have signed universal main service agreement, which gives them access to our agents and our AI capabilities. That strategy clearly worked. More than half of our customer base has already migrated to the UMSA, and that momentum is accelerating. Our focus now shifts to driving adoption through Flex credits. We've already signed 200 customers this quarter, and we expect to significantly grow that number in the second half as R2 adds more GA agents and [indiscernible] platform and data cloud capabilities. We continue to see strong execution across the globe. North America, our largest market, had an exceptional quarter, anchored by U.S. large enterprise and another strong quarter in Canada. EMEA drove solid growth, the strong performance in France, Germany and the Nordics. AI now accounts for nearly 1/3 of new ACV in EMEA.

Japan also had a standout quarter, further proof that our continued investment there is paying off. I'm proud of the results our teams delivered across the business in Q2. Let me close where I started with trust. For more than 20 years, organizations have trusted Workday with their most critical work and now with the AI. That's a durable advantage, and it sets us up for an even stronger second half.

Now over to Zane.

Thanks, Rob. Good afternoon, everyone, and thank you for joining us. Building on Rob's remarks, our second quarter results reflect the continued strength of our platform as organizations rely on Workday to power their most critical HR and finance operations.

Subscription revenue in Q2 was $2.471 billion, up 14%. Professional services revenue was $178 million, resulting in total revenue of $2.649 billion, growth of 13%. Looking at our results by geography. U.S. revenue totaled $1.97 billion, an increase of 12%, while international revenue was $682 million, up 17%, benefiting from stronger performance over the last few quarters.

Turning to backlog. 12-month subscription revenue backlog or CRPO, ended the quarter at $9.03 billion, an increase of 14.2%. Growth was again fueled by expansion within our existing customer base with AI increasingly a driver alongside a steady contribution from new logos.

Total subscription revenue backlog ended Q2 at $27.4 billion, up 8% from a year ago. The year-over-year growth rate was impacted by a continued mix shift towards customer-based bookings versus net new and the mix of industries that drove our net new bookings. Gross revenue retention remained strong at 97% for the quarter and net expansion from existing customers once again led to about 60% of our subscription revenue growth. Non-GAAP operating income was $824 million for the quarter, representing a non-GAAP operating margin of 31.1%, driven by a combination of revenue outperformance and ongoing cost discipline. Our GAAP results in the quarter included a $374 million nonrecurring tax benefit related to an internal IP transfer. Operating cash flow totaled $520 million in the quarter, and free cash flow was $460 million. The year-over-year decline was impacted by the timing of the payroll calendar, which had an additional payroll run this Q2.

We repurchased $1.3 billion of shares during the quarter, completing the $5 billion repurchase plan that we discussed at our Financial Analyst Day last September, 6 months ahead of our target. Buybacks will continue to be an important part of our capital allocation philosophy, and our Board has recently approved a $4 billion open-ended share repurchase program. We ended the quarter with cash and marketable securities of $3.4 billion. Our headcount as of quarter end stood at 20,896 workmates around the globe.

Turning to our outlook. We are pleased with our first half results, and we now expect FY '27 subscription revenue of $9.94 billion to $9.95 billion, growth of 13%. For the third quarter, we expect subscription revenue of approximately $2.515 billion, growth of 12%. We expect Q3 CRPO growth of 11% to 12%. We lapped the Paradox acquisition in the third quarter, which added over 1 point to last year's Q3 CRPR growth. For Q3, we expect professional services revenue of $175 million. And for the full year, we expect $710 million. We continue to prioritize investment in AI alongside strategic investments in the core while driving efficiencies across the business. With that, we're increasing our FY '27 non-GAAP operating margin guidance to 31%.

For the third quarter, we expect a non-GAAP operating margin of approximately 30%. We expect to continue expanding margins while positioning ourselves for future growth. We expect Q3 GAAP operating margin to be approximately 18 percentage points lower than our non-GAAP operating margin. And the full year FY '27 GAAP operating margin to be approximately 18 to 19 points lower. Our FY '27 non-GAAP tax rate estimate remains 19%.

We are maintaining our FY '27 operating cash flow outlook of $3.45 billion, and we continue to expect FY '27 capital expenditures of approximately $270 million, resulting in free cash flow of $3.18 billion [indiscernible] 15%. As our Q2 progress demonstrates embedding AI across Workday's platform provides a significant opportunity to drive customer value.

[Audio gap]

extend with Data Cloud and our AI agents all of which are seeing great early demand. In addition, we expect our non-GAAP operating margin to expand by at least 2 percentage points next year. We're encouraged by the significant opportunity ahead to continue to deliver long-term earnings and free cash flow growth. We look forward to diving deeper into our platform innovation at our Financial Analyst Day on October 13 in Las Vegas, and we hope to see many of you there.

With that, I'll turn it back over to the operator to begin Q&A.

[Operator Instructions] And our first question comes from the line of Gabriela Borges with Goldman Sachs.

Zane, I really appreciate this early look into growth rate exiting '27 and then the longer-term upside potential. There are -- the question I want to ask about business twofold. One is tell us a little bit about how you're thinking about monetization for headless. And the second is, how do you as an executive team, think about the risks that some of the upside opportunities end up coming as a trade-off between some of the core. What I mean by that is do customers end up essentially negotiating hard on the core products or exerting pricing pressure on the core products such that you end up at a similar place even when adding new functionality. So maybe just those pieces together, I would appreciate your thoughts.

Yes. So I'll take the first part. On the head list transactions, we are pretty much indifferent whether somebody uses from a profitability perspective, I think it will show on a revenue perspective, whether a company buys our agent uses our APIs, which we get to monetize or goes through data cloud, which we get to monetize. So -- or the other option is to build their own agents using Workday Extend AI. So we feel like we're pretty covered in all ways that AI gets used, and it doesn't take away any opportunities. If anything, it grows our market opportunity than where it has been before. Second part, I'll probably ask Rob to weigh in. What I actually see, Gabriel, is that customers are making 5-year, 7-year decisions on new platforms and AI is a huge decision point for them. And if anything, it's impacting our win rates on the platform, because we're viewed as the much stronger player in terms of an AI vision and AI agents than our legacy competitors are that we all know so well.

Yes, Gabriel, from my side. We don't see compression on the call. What I see is customers starting with the AI discussion and wanting us to be the AI platform for agentics on HCM and on finance. And I think that's driving a broader conversation. And a much broader conversation to the value we offer. You can see it actually in the amount of uptake on the agents that we started to announce and bring to the far where customers -- this is where they actually want to see where HR is going and where finance is going in the future.

Yes. And just to add to what Rob said, our competitors don't have one data model across there are multiple versions of their applications. These legacy companies might have 6 or 7 different versions. And as a result, they can't aggregate the data model to drive the the AI models. And so we are just way ahead of where they can be, not just where they are now, but where they can ever be from that AI perspective in terms of driving outcomes using AI.

Hi, Gabriel, I'll just add. The early look into FY '28 is just to give you a target on how we're thinking about it. As you can tell, we have a number of initiatives in place, and we're very enthused by what we're seeing as early indicators in our AI products. Not all of that has been factored into our FY '28 outlook. So were as you can tell, very enthused on the upside there, but I just wanted to ahead of Financial Analyst Day, give you at least a baseline to see to let you see how we're thinking about it.

And our next question comes from the line of Michael Turrin with Wells Fargo Securities.

Appreciate you taking the question. A lot's changed over software over the past couple of months. We've seen the topics shift to the rise of open source, open weight models, some scientific cooperation between the Frontier labs and existing vendors. And Aneel, I'm curious where Workday fits within those discussions, if any of that, if any of those shift your view on where to focus, and I want to also give you a chance to respond to just some of the recent headlines around private equity interest, given we've all been feeling a number of questions there as well.

I obviously can't comment on the latter. On the former, we're going to do what's in the best interest of our customers. And so I'm going to ask Gerrit to talk about how we think about the different models, and we work with all of them, but we're trying to do what's best for our customers, both from our performance but also from a cost perspective.

As Aneel has said, right, we are really focused on driving the right ROI and economics for our customers. So as of today already, we deploy a large set of models for multiple vendors. We have small models, open rate models and large frontier models, all in the set of models that we use to build our AI systems and agents with. And quite frankly speaking, we are really excited about open weight models. So if they open up new opportunities for us for having own reinforcement learning, building on adapts over them they give us a much stronger optionality when you think about international and sovereignty. So it's a core tenant for us, as Aneel has said to be more agnostic and because of the different characteristic already, we get great benefit from them. And now as the benchmarks that are getting closer, we have signed the open [indiscernible] initiatives as well as auto companies. we truly see a real big upside for us and our customers to drive better ROI out of our investment. And last [indiscernible], we also started our own research foundation inside of Workday. So we have an own research lab, which specifically actually focuses on getting high accuracy HR and finance, AI systems in place. One of the things that this team is doing right now is actively actually exploring opportunities for us to not only use open weight models, but really to specialize them to our purposes and see what [indiscernible] get out of that.

And our next question comes from the line of Kirk Materne with Evercore ISI.

I think this is probably for Aneel or Rob. Obviously, we can -- we hear the enthusiasm around the early progress on AI. I was just kind of curious if you can give us an idea, is AI crowding out some of your other products at this point in time, meaning when you go in and talk to a customer, you obviously want to talk about AI, you obviously want to get AI into their hands. Does that mean sometimes your salespeople have to put something they might have been thinking about a year ago on the shelf for now? And the reason I ask that is because your tone and your enthusiasm is obviously very apparent. But when I look at CRPO just for a proxy, that's more or less in line and Zane gave a guide for early guide in the last. For next year, that seems more or less in line with where people were kind of forecasting. So it seems more substitutive than incremental. So I was just wondering is there something from just a go-to-market perspective where there's a purposeful push with AI, whereas we're not going to try to load everything in every customer right now. Let's get them successful with AI. Even though that might mean we're not seeing as much incremental benefit. I hope that makes sense.

Yes. I'll start. Thank you for the question, Kirk. So first of all, you're right in that it's early days. The difference on these agents versus traditional applications they iterate and become better so much faster. So I'm very optimistic that we're going to see ramping up usage of these agents faster than we ever saw of our apps. And we're also new to the Flex credit consumption model. And that's a delayed gratification model that is, frankly, newer to Workday again, very optimistic we're seeing great early signs. But I think that's one of the reasons for cautious optimism going into next year because we are aggressively moving towards a hybrid model between subscription and and this consumption model. I don't actually see it as crowding out. I actually see it as customers -- new customers choosing Workday because of our Agentic strategy, existing customers, they have an AI budget. And now we have products that actually fit in that AI budget, which is a big win for us. But again, a lot of these AI products are consumption based. So we won't see the impact from revenue until months or a year down the road. So Rob, what do you want to add to that?

Yes, I would add there's a lot of excitement around AI. But our focus has really been about getting adoption. And when you look at bringing an agent, you got to harden them, so you've got to get them adopted. The more customers that go through early access to more customers that are adopting these products just get better really fast. And so that's how our merger has been around how do we get adoption for us. The more customers we have access to our agents, the more they're using those agents, and that's how we're measuring them and moving the company in that direction. And I think you can actually see it in the amount of new UMSAs we've signed. UMSAs have really started to take off. Customers really want that they need to have the UMSA to actually get into the AI world. And then you link that to the data play and the Extend Pro and what you're doing with the Developer Agent. As Aneel said, this is a [indiscernible], but our conversations are really good. And it's in almost every conversation, irrespective of the level of customer speaking to whether it's a C-level executive or the ACM team or the finance team really start to understand that Workday has really entered agentic world in a big way.

Kirk, and just to add to that. As we mentioned, we've got 5,500 customers using our organic agents and just over 200, I think, that have actually signed up for Flex credit. So that's the delay that Aneel is alluding to, and that's been factored into our CRPO guide as well as our revenue guide for the remainder of this year, but also our cautious optimism heading into FY '28 and beyond.

And our next question comes from the line of John DiFucci with Guggenheim Securities.

My question, I think, for Aneel and Gerrit and maybe Gabe, listen, Workday's approach to AI seems, at least to me, seems sincere and frankly, more thoughtful than some of your peers. But it's also more pragmatic. In other words, it makes sense in my understanding is simply it, AI is going to be part of everything you do, which again, sounds simple, but also an immense task. And frankly, the right move. It sounds like you're certainly on the way from your prepared remarks. But how much effort do you think it takes to accomplish that? And of course, it's a continuous effort. But when do you think you'll get to the point where you can see we've arrived as an AI platform. Is that going to take years, or just curious how you think about that?

I'll start. And I think both Gerrit and Gabe should weigh in. We are trying to be very thoughtful in the way that we're building our Agentic solutions. They're there meant to solve a anybody can solve the simple problems when I look at what we're doing with the self-service agent is really hard. What we're doing with the financial audit agent is really hard. But by building these agents and coming out the other end, they add tremendous value to our customers and frankly, from a competitive perspective, they're really, really hard for anybody to compete with because they're so deeply embedded in the bowels of Workday. I don't know when we arrive. I think we're arriving now, and I think it just gets better over the next couple of years, but it's all about adoption and customer success. We have to have agents that have real ROI, and that's been the lens we've been looking at it since I came back. We had a lot more agents when I came back. We killed a lot, or we rolled them into [indiscernible] agents. And the ones that we have right now, I'm very optimistic they're all very meaningful to our customers. But let's have Gerrit and Gabe add to that.

Yes, I had a couple of points on the top of the stack, if you will, and then Gabe on the platform side. But to give you a few concrete points on what are the key milestones that we are looking at that we truly believe our landmark moments for Workday as well as for the industry of moving into the AI era and enterprise SaaS. And one of the biggest one for us is how work is going to change in the work experience with Sana. You heard in the prepared remarks that Sana is going to be the default home screen for Workday coming rising this year. Rob spoke about the lighthouse program at Sana Enterprise, and I have shared this changed the world of work inside were there already. We have 24,000 agents being built in just 3 weeks. We really see this coming this rising as a key moment because the phase of SaaS and how work happens is going to fundamentally range. And frankly, we believe it's a stark difference to what that work experience is than what you get from generic jet Copilots because they're deeply tattered into the system of action and a system of work. Secondly, you heard you know that our agents are making a lot of progress. And when we say agents, we really mean AI systems that automate large parts of the value chains in HR and Finance. We just put Decision Intelligence into GA, which is truly a reimagination of how you collaborate with AI on enterprise data. We are about to bring new functionality to recruiting age, and you have heard earlier how much momentum that has already. We are making great progress in one of the areas that Aneel is most excited on financial audit and financial compliance agents, all of these agents are coming out either day out already or coming out of rising at the end of the year. And I think when we come together in the next call back and you look at the momentum we have built until then. I think there will be no question mark left anymore about Workday being in an AI company or not because the world of SaaS will have changed.

Gabe, over to you for platform.

Yes. And thanks for the question. In terms of just the time line view on this on the platform side, it's pretty obvious that the AI technology evolution has been at a frantic pace, right? We're seeing rapid and continuous evolution. And I don't really see an end to that. It's going to be continuous, constant evolution. And so the way we're looking at this is as these new integration patterns change, as protocols change, as identity approaches change, we're on a process of taking the new capabilities, pulling them into the platform, driving adoption, as Rob was mentioning, and then delivering outcomes and ROIs. And the key is going to be doing that continuously in a loop. That is the art of building AI systems. And that's going to be a long journey. This is not something that's going to end anytime soon.

And our next question comes from the line of Alex Zukin with Wolfe Research.

Probably another AI question here. But just it's great to hear about the agents and the data cloud opportunities that you're getting front of customers, but maybe just help crystallize us how you're monetizing? And maybe any specifics around like how many Flex credits does an onboarding or procurement agent actually go through, and what that could mean in terms of a net expansion in terms of spend at a customer that's deploying them or like a sales force yesterday talked about in order for customers to unlock AI functionality, they had to upgrade to a premium version that's 60% to 80% more in some cases. How do you see that with some of the MSA agreements we were talking about, Rob? And when should we think about that as a tailwind to numbers? Is that a 2020 -- fiscal '27 dynamics or the following year?

You said it's a question about AI, but you are hitting all of the cards here from sales of finance to car technology. So maybe let me start and then I hand it over to Rob and probably saying on the outlook question. What we are seeing is that the workload that these agents are driving quite substantial. When you heard about early the numbers and our volumes, we are driving recruiting already. And the key of the ambient agents, the agents that are running in the background, we see a substantial opportunity, but we are not comparing it to software spend. Actually, what we are modeling it against is the labor spend that companies have in those given roles already and think about what is the share of the agent that actually will get basically transferred from a labor spend into an AI agent spend for that specific task group. Right now though, and Rob has said it, so I want to repeat that. Our focus is really on adoption, adoption adoption, right? This is the way how you actually build great AI systems. And so what we are doing right now, and Rob spoke about it, right, we're incentivizing this with programs like the Sana Lighthouse program that we basically allow customers to use it for free in the first year self-service age and one of the most consequential agents we do we put out a promotion that we are not putting on a flexed meter until the end of August or September. So the question that you're asking, how does this translate now to sales and dollars right now, it's difficult to answer because this has not been our focus point. But then you ask me for the potential that we have because of how much work or it actually processes. It is incredibly substantial. And this is why San has said, right, we are so bullish as this being an upside because we can see on the 1 side, the usage increasing, and we sit on the inside that this represents significant monetization opportunity for us.

I mean you kind of said that, look, I'm super excited. We focus on the adoption side of things. Now we're starting to focus really on the consumption side of things. So as we move into this, the sales motion changes, and what you see with broad adoption of Sana self-service agents, it's going to rise all the other agents as well because it gives it a completely different look and feel on how you utilize Workday in the future? And what kind of users can work with Workday pretty much anyone. I watched the CFO and a COO look at the the intelligence agent. And it was just -- they were completely blown away. So I think the opportunity for us is really good. The back half of the year looks really positive for us. And I can't see that changing. And we are lockstep in making certain that these agents are to adopt them and consume them. The quality of the agent continues to improve all the time. And I think that's what he meant by it's a circle. It's a loop. And I think we've got a really good process on how to define that loop. So the field is excited by it. Every single one of my customer conversations is really, really interesting. And even customers that I've known for years that are not really in the HCM or finance space. We really want to understand what we're doing and one Workday to lead in the space of HCM and finance. And then lastly, I'd just say, don't say that we've also got agents like talent acquisition agent and a document where we actually measure by different statistics. And that -- if I look at the [ Telemacquisition ] agent, we had more than 30 million candidate interviews in Q2 with 8 million in view schedule. So the numbers are starting to show up, and it will continue to improve over the next months and quarters.

Yes, Alex, I would just add, this quarter, we talked about roughly $600 million in AI ARR, which is up from around just over 150 just a year ago. So we expect that trend to continue. As Aneel mentioned earlier on the call, this is all about customer success and customer value, and that's going to be the ultimate driver of our revenue. So we've got some of that built into the back half of this year, as you would expect, but really growing from FY '28 and beyond where the AI component becomes a significant part of our incremental ARR. So we're excited about the future, as you can tell, and we just want to be thoughtful as we monetize it.

And we will now take two more questions. Our next question comes from the line of Karl Keirstead with UBS.

Maybe I'll direct this one to Zane. Zane, you gave us a preliminary look at 200 bps of margin expansion next year, a little bit more than I was modeling. And actually, a greater pace of expansion than you're guiding to this year. I'm assuming there's no big change in the prioritization on investing. So perhaps you'll probably address this at the Investor Day, but a couple of things that might be driving that.

Yes, Karl, thanks for the question. As Anil mentioned earlier this year, this was the year where we intentionally invested heavily in AI and brought in some great talent and feel like we're doing a lot in that area. And I think we've done a credible job prioritizing and then leveraging size and scale and really being thoughtful on how we drive just thoughtful expenses in the future. So it's a continuation of that doing, I think, a pretty good job utilizing AI ourselves internally and expect that trend to continue. So it's really been about the team focusing on what matters and rethinking what we are doing and as importantly, what we're not doing where we're not going to be spending money in the future. And it's that kind of focus that I think is also driving the increase. And we believe that the 2 points for next year is a good starting point. As you know, we've increased to 31% this year, and we believe we can continue to see that improvement as well as leaning in as much as we have in investments in critical areas around AI and our platform.

Yes. I would just add, we're leveraging AI internally, and we're doing more with flat headcount. That's the goal. And I think that's a really important direction for us to head.

And our final question comes from the line of [ Samik Chaterjee ] with JPMorgan.

You talked a lot today about the organic agents and the adoption curve you see there. Maybe if you can sort of dive into the acquired acquisitions that you've done and particularly the acquired agents and how you're thinking about the road map there in terms of integration finest of making to a product and then the monetization on that front? And particularly, how should we expect that to impact your fiscal '28 sort of financial outlook as well? Any thoughts on that front would be helpful.

Well, I'll just say that they're all doing well, but most importantly, they're all deeply integrated already. We don't ever buy technology and just leave it on the outside. We deeply integrate it right away, so we can deliver that unified experience. Maybe, Gerrit, you want to talk about where the products are headed?

Yes, awesome. So it's a great question because actually, we kind of spoke about it earlier, the big products that you can think of is a higher score on the recruiting side in paradox. They actually both are part of our talent acquisition agent now. So they are basically agentic skills as we evolve our AI systems. And both of them have tremendous momentum. I'm going to hand it over to Rob in a second to talk about that. But we are not really thinking about this as, hey, this is separate from the core. As Aneel said, we have a really good M&A regime that we look for strong technical fit. And so as we move forward with Workday recruiting, HiredScore and Paradox, they are an integral part of that, and they're all coming together under the row-based agent for talent acquisition. Again, right this whole idea. This is the embodiment of an actual recruiter with all of these skills. And on the Sana side, which had an absolutely blowout quarter as well gangbuster growth. We put it into GA in a combined product. So Workday Learning and Sana Learning is actually one product now. It's in GA already, and it's driving substantial growth for our customers. But as we take it to them, we don't put rates as Workday and others. This is the learning agent from Workday. This is the recruiting agent from Workday and those acquisitions, they are just widening the breadth of skills these agents have. Rob?

Yes. I'd simply say, I mean, we drove more than $100 million of new ACV with our AI products, just 25% of all new ACV. So if you just look at those numbers. And then we -- our ARR numbers are up at 600 -- close to $600 million now. More than half of the new into signed up for AI solutions. So our AI solutions are really paying off. And as Gerrit said, I think it's really important to point out, they are integrated into the Workday Foundation. It's one core, it's one view for our customers, and that allows us to deliver the agents even on top of that.

And ladies and gentlemen, thank you for your participation on today's conference. You may now disconnect.

Ladies and gentlemen, welcome to Workday's First Quarter Fiscal Year '27 Earnings Call. [Operator Instructions] I will now hand it over to Justin Furby, Vice President of Investor Relations. Please go ahead.

Thank you, operator. Welcome to Workday's First Quarter Fiscal 2027 Earnings Conference Call. On the call, we have Aneel Bhusri, our CEO; Gerrit Kazmaier, our President, Product and Technology; Rob Enslin, our President and Chief Commercial Officer; and Zane Rowe, our CFO. Following prepared remarks, we will take questions.

Our press release was issued after close of market and is posted on our website, where this call is being simultaneously webcast. Before we get started, we want to emphasize that some of our statements on this call, particularly our guidance, are based on the information we have as of today and include forward-looking statements regarding our financial results, applications, customer demand, operations and other matters. These statements are subject to risks, uncertainties and assumptions that could cause actual results to differ materially.

Please refer to the press release and the risk factors in the documents we file with the Securities and Exchange Commission, including our fiscal 2026 annual report on Form 10-K for additional information on risks, uncertainties and assumptions that may cause actual results to differ materially from those set forth in such statements. In addition, during today's call, we will discuss non-GAAP financial measures, which we believe are useful as supplemental measures of Workday's performance. These non-GAAP measures should be considered in addition to and not as a substitute for or in isolation from GAAP results. You can find additional disclosure regarding these non-GAAP measures, including reconciliations with comparable GAAP results in our earnings press release, in our investor presentation and on the Investor Relations page of our website.

The webcast replay of this call will be available for the next 90 days on our company website under the Investor Relations link. Additionally, the prepared remarks of this call and our quarterly investor presentation will be posted on our Investor Relations website following this call. Our second quarter fiscal 2027 quiet period begins on July 15, 2026. Unless otherwise stated, all financial comparisons in this call will be to our results for the comparable period of our fiscal 2026. With that, I'll hand the call over to Aneel.

Thanks, Justin, and thanks to everyone for joining us today. It's great to be with all of you. I now have a full quarter under my belt since returning as CEO, and I truly feel the energy building at Workday every day, both around our path forward on AI and the company as a whole.

We're in New York City this week for the Sana AI Summit, where we brought together some of the brightest minds in AI with our top customers. It's an incredible event, and it was great to see a few of you there. A few weeks ago, we hosted our top industry analysts at our Annual Innovation Summit, typically a skeptical group. They came away generally impressed by the pace of innovation and by our renewed focus on operating like a start-up. One of them even called it the reinvention of Workday.

Indeed, their reaction to our vision and execution around AI told me that we are absolutely on the right path. So do our Q1 results. We had a great first quarter. In fact, it was the best first quarter of new ACV growth in 5 years, anchored by the strength of our core business and the traction we're seeing with AI. Following slower ACV growth in fiscal year '26, we're seeing momentum once again building in the business. I'm confident in our ability to drive accelerated new ACV bookings this year as we bring new agents to market for our customers and drive even greater adoption.

Last quarter, I mentioned I came back to help Workday lead again during the biggest technology transformation of our lives. After being back for 3 months, I have even more conviction that this is Workday's moment to lead. But to do it, we need to operate differently than we have been. And coming back, I was very focused on returning Workday to a start-up orientation and a growth mindset. Indeed, I watched a lot of Steve Jobs videos where he talked about his management approach when he returned as CEO. What struck me most wasn't about what Apple built after he returned, which was obviously incredible. It was more about his management philosophy.

There was one interview in particular from All Things D where he called Apple the biggest start-up in the world and said it was the start-up mindset he brought back, fewer layers, faster decisions, the best ideas winning, more ownership. We're trying to emulate that start-up playbook. As a great philosopher Yogi Berra once said and apropos that we were in New York City this week, it's like deja vu all over again. And so we're going back to our founding principles. I've said before, Chapter 4 is a refounding moment for Workday.

With AI, we are essentially a start-up again. We're a start-up sitting on one of the most important enterprise platforms ever built and the trust of more than 11,500 customers. We need to embrace that mindset. It's all about focus and trust, clear ownership and the best ideas winning. That's how we are leading Workday now, and it's how Dave and I led the company early on. As part of this mindset, we've simplified our priorities to 3: number one, build and deliver the AI future; number two, grow with our customers; and number three, live our values.

We've also streamlined ownership across the organization so every Workmate knows exactly how their work connects, fewer things done with greater focus. A dedicated AI agent factory, building agents across all of our application areas, clear ownership and accelerated development of our AI APIs. We've got the right people to do it. We have some incredible leaders from the companies we've acquired now in key roles at Workday. One of them is Joel Heelmark, the founder of Sana, who we named our Chief AI Officer just today.

That's by design. These leaders know the start-up mindset, and they're helping Workday move faster and stay focused. I've also thought a lot about how Workday wins in this new chapter. I've met with dozens of customers since I've been back, and I keep hearing the same thing. Not one of them is looking to replace Workday with something they're building internally or from a start-up. Instead, they were looking to us first for AI solutions for the HR and finance world and hopefully, IT in the future. It's really our opportunity for the taking, but we need to execute flawlessly and with speed.

We have all the requisite components, one data model for all customers, one security model and a true cloud architecture. Our business process framework gives AI the rails it needs to operate safely and accurately inside the enterprise. And over the past several years, we have completely rewritten our tech platform to be AI native in the way we manage transactions, reports and UI requests. That's basically the foundation we've spent 21 years building and now it's been modernized for AI down to the core OMS.

And we're delivering the results as well. Q1 was our first quarter with both Sana and Paradox fully integrated. With Sana, we're giving our customers a completely new Workday experience. It's a new front door to Workday that is simple and modern. The Sana platform is also the foundation for everything we're building in AI going forward. Joel and his team have created something remarkable and the integration has gone further and faster than I anticipated. We've already proven that customers trust Workday deliver AI through agents we acquired. This is a year we prove that they also buy the agents we're building organically, agents that only Workday can build, and Gerrit will share more on that momentum in a moment.

And while there are some who believe that AI can disrupt Workday, I see something different. Our chance to once again be a disruptor with AI clearly driving that disruption. To that point, Gerrit will talk about Sana for ITSM and the new travel agent we announced today at the Summit. These are early examples of what it looks like when we use Sana to rapidly innovate on top of our data and context. What ties all this together is one simple truth. Customers don't want AI for AI's sake. They want AI that adds value to how they run their businesses. Our early adopter customers are already seeing that, and they want more from Workday.

To close, I am confident that Workday is ready for this AI moment. Our core business is strong, our AI strategy is working and our execution is accelerating, starting with Q1. Seeing the agents Gerrit is building and the success Rob is having selling and deploying them with customers, I couldn't be more confident in our path ahead and ability to lead. Gerrit, over to you.

Awesome. Thanks, Aneel, and hello to everyone. For AI, the world model, it is like the Holy Grail. Today, a large language model, it just predicts the next token in a sentence. And the world model, it is the step change needed for it to understand the physics of its real environment. It's about how things actually work and the laws that govern them.

On Workday's platform, we have over 80 million users under contract and approximately 1.4 trillion transactions annually. That is giving us a set of data and context that no other competitor can replicate. For more than 20 years, we have been on the journey of building the world model of work. And here is what we have done. We have mapped the patterns of work at scale. Who approves what, how money moves, how people get hired, assessed, developed and scheduled for their work and the policies, the processes and the exceptions around them.

And here is the key insight for you. This world model of work, it is the best context engine for Agentic HR, finance and beyond. It unlocks unmatched enterprise-grade accuracy for AI automation. All of this is adding up to agents that our customers can trust to perform actual work inside real business processes. And you can see that clearly in the impact that they are delivering already for our customers. In Q1, for example, we have supported 14 million hiring processes with our recruiting agent. That is up 44% year-over-year. And we have analyzed more than 1.1 million contracts with contract intelligence. That is up 53% from last quarter. Now that is the world model of work at work.

And while we're driving all of this amazing impact, the pace of innovation here at Workday, it is accelerating. We now have 20 organic agents in GA or EA, and the number of customers using these agents has more than doubled quarter-over-quarter with over 4,000 customers using at least one organically developed agent as of today. And here are just a few highlights for you. Deployment agent is now being used in our first end-to-end customer projects. It is designed to deliver an estimated 30% reduction in implementation hours and costs. And in our next wave of AI-driven projects, we are aiming to get that reduction up to 50%.

And here is why this is so important. This reduction in time and in cost of deployment, it is removing a historic barrier to choose Workday, particularly in the mid-market segment. Further, customers like the University of Arkansas System, GE Vernova and Mohegan, they are using deployment agent across their Workday systems to instantly resolve issues and answer questions. So admins, they can spend their time moving their projects forward.

Also, we are seeing a super fast takeoff of our self-service agent. This quarter, our first Fortune 500 customers are expected to go live on self-service agent. And we will take another big step at the end of this month. All HCM and finance customers on our AI terms of service, they will get Sana for Workday and our self-service agent as a part of their existing contract.

So now let's talk about our accelerating AI business momentum. In Q1, our new ACV from Agentic AI products, it grew more than 200% year-over-year. And we are also approaching USD 500 million in ARR from our Agentic AI solutions. But we are not stopping here. AI, it lets us break free from the narrow definition of legacy business applications that lead to frustrating user experience breaks and outsized spend for so many companies out there. With Sana as our AI platform, we are pushing the boundaries of HR and finance and IT with new AI solutions.

Just today, here in New York City, we announced 2 new Agentic solutions from Workday that proved this out. Sana Travel Agent brings business travel planning, booking and expenses into a single conversational experience. With more than 5 million expense reports processed monthly on Workday and much of it is travel, this agent, it takes on the heavy lifting. It can automatically handle bookings, receipts, policy checks and expenses. So employees get a more seamless travel experience and finance teams, they get real-time visibility into current spend and future travel commitments.

We have also announced Sana for ITSM, which automates workflows for employee on and offboarding, access changes and everyday IT requests. Many service requests start with employee life cycle changes that Workday already knows about, like joining a company, moving across teams or even exiting. And with the key data, the work identity, the org chart, job profiles and so much more running on Workday, we inherently know the chain of approvals, the required policies and the right work context. That allows us to simplify and automate ITSM requests at a whole new level.

Lastly, let's take a look at the Workday platform and our AI momentum there. Workday Extend Pro enables customers to build their own AI-powered solutions on our platform, taking advantage of our AI APIs. In Q1, Extend Pro continued to be one of the fastest-growing products with new ACV nearly doubling year-over-year. And here is our approach. At Workday, we embrace the AI ecosystem, and we design for openness. So our customers and our partners, they can build their own AI innovations without locking them in into a single vendor stack.

We are giving our customers choice and 3 clear paths to run agents on the Workday platform designed to meet them wherever they are. First, our customers can build their own AI agents with Workday's agent-ready tools. These are a new class of Workday connectors and APIs that are purpose-built for autonomous consumption by AI agents at enterprise scale and available via open standards like MCP. Second, our customers can plug in Workday agents into their agentic front door using the A2A protocol. And already in Q1, we have made self-service agent available in Microsoft Teams, Microsoft Copilot and Google Gemini.

And third, they can use Workday's agents in Sana for the fully optimized work experience where Workday provides the reasoning, the context and the ultimate AI user experience. It's the AI workbench for work. These options give our customers and partners the flexibility to adopt AI the way that best fits their business. So stay tuned for our upcoming developer conference, DevCO, the first week of June in Las Vegas. There, we will announce new Workday AI platform innovations.

And here is the bottom line of all of this. Enterprise AI starts to pay off when agents can perform actual work with the same approvals, security, policy and guardrails that govern the rest of the business. That's exactly the future we are delivering for our customers, powerful AI agents harnessing the world's model of work built on an open platform. And with that, over to you, Rob.

Thank you, Gerrit, and hello, everyone. We're proud that more than 11,500 customers around the world trust Workday for the most important parts of their business from payroll to closing the books. And as Aneel said, growing with our customers is one of our top priorities. You see that in our results. In Q1, expansions once again drove roughly 60% of our subscription revenue growth with customers like Queensland University of Technology, Rakuten Group and Bank OZK expanding their relationships with Workday.

We also continue to go deeper in federal and had a record turnout at our fourth annual Fed forum in D.C. last month with nearly 600 attendees. And in Q1, we kicked off the next phase of our contract with the Defense Intelligence Agency. Also in Q1, net new business drove 40% of our subscription revenue growth. We formed new relationships around the world with key brands, including Harley-Davidson, Del Monte, Australian Gas Infrastructure Group, Smiths Group, Artland Dental and ACHM Hotels by Marriott.

State and local government was also a standout this quarter, where we signed statewide deals with the State of Delaware and the Commonwealth of Massachusetts. Turning to AI. The numbers this quarter tell a clear story. More than 1/4 of new ACV from customer base expansions came from AI and expansion deals that included AI were over 50% larger on average. The pattern is consistent. Customers who adopt our AI go deeper on the platform.

The University of Arkansas System is a great example. They have 21 institutions, including research universities, community colleges and an academic medical center, all on a single Workday instance. They process over 2 million transactions a month. And in Q1, they used our deployment agent to cut support tickets and uncover configuration insights at once required manual searches. Deployment agent has significantly increased the operational velocity and allowed them to scale Workday with less reliance on external consultants.

Our Flex Credits pricing model is quickly gaining traction. With Flex credits, we've unified AI monetization across Workday, one model for agents, AI APIs and data cloud. It makes AI adoption simpler for our customers. While still early in the journey, we're seeing a growing mix of AI monetization coming through Flex credits. And as we bring our new Agentic innovations and acquired agents onto the model throughout the year, this will become a more meaningful part of how we grow.

We're also continuing to make progress outside of North America. In APAC, we expanded our operations into Vietnam, which opens up a brand-new market for Workday. This strategic expansion is made possible by 5 global and regional partners, all dedicated to meeting the growing local demand in Vietnam for digital transformation. And in EMEA, we launched an EU-based data residency in Frankfurt. This was a significant milestone for European customers with data sovereignty requirements.

We're also expanding Workday GO globally to help these customers get up and run faster in a more standardized way. EMEA is now our second largest region for medium enterprise, which we define as 500 to 3,500 employees. And new ACV in that segment grew by more than 50% in the quarter. Workday GO is now available in France, Germany and the U.K. with an additional 14 countries available through our partner network.

Speaking of partners, our ecosystem continues to be a meaningful driver of our growth. In Q1, roughly 30% of net new ACV was sourced by partners. We also hit several milestones worth mentioning, including Insperity's HRScale solution is now generally available, bringing Workday to the PEO market for the first time to deliver full-service HR for growing businesses. Workday recognition powered by Achievers is live, and we expanded our Workday Wellness program with Morgan Stanley at Work and PerkSpot.

The momentum this quarter was broad across expansions, net new AI and international. We are growing with our customers and continuously evolving to meet their needs. Now over to Zane to share more on the financials.

Thanks, Rob, and thank you to everyone for joining today's call. As Rob mentioned, our results this quarter demonstrate ongoing customer adoption across our platform as enterprises around the globe turn to Workday to manage and empower their most important assets. Subscription revenue in Q1 was $2.354 billion, up 14%. Professional services revenue was $188 million, resulting in total revenue of $2.542 billion, growth of 13%.

From a geographic perspective, U.S. revenue in Q1 totaled $1.89 billion, up 13% and international revenue totaled $649 million, up 16%. 12-month subscription revenue backlog, or cRPO, was $8.81 billion at the end of Q1, growing 15.5%. This was driven by continued customer expansion, bolstered by our AI solutions and growth from new customers. Total subscription revenue backlog at the end of Q1 was $27.29 billion, up 11%.

Gross revenue retention rates remained strong at 97% in the quarter. Net customer expansion rates remained consistent with what we observed last quarter, contributing roughly 60% of our subscription revenue growth for Q1. Non-GAAP operating income for the first quarter was $809 million, representing a non-GAAP operating margin of 31.8%. Margin strength was the result of the revenue outperformance combined with favorable spend versus expectations.

Q1 operating cash flow was $696 million, growth of 52% and free cash flow for the quarter was $616 million, growth of 46% and in line with our expectations. We repurchased $1.6 billion of our shares during the quarter and had $1.3 billion in remaining authorization as of April 30. We ended the quarter with $4.4 billion in cash and marketable securities. Our headcount as of quarter end stood at 20,834 Workmates around the globe.

Now turning to guidance. We remain focused on driving adoption of our Agentic solutions across HR and finance, while expanding into adjacent market opportunities, providing a foundation for long-term growth. We are pleased with our performance in Q1, and we are reiterating our FY '27 subscription revenue outlook of $9.925 billion to $9.950 billion, growth of 12% to 13%. We expect Q2 FY '27 subscription revenue to be approximately $2.455 billion, growth of 13%. We anticipate cRPO to increase between 13.5% and 14.5% in Q2.

For Q2, we expect professional services revenue of $180 million. As Aneel mentioned, we are streamlining how we operate the business and are focused on investing in areas with the highest returns. We are increasing our FY '27 non-GAAP operating margin guidance to 30.5%. For Q2, we expect a non-GAAP operating margin of approximately 30%. We expect Q2 GAAP operating margin to be approximately 19 percentage points lower than our non-GAAP operating margin and the full year FY '27 GAAP operating margin to be approximately 18 to 19 points lower. The FY '27 non-GAAP tax rate is expected to be 19%.

We are maintaining our FY '27 operating cash flow outlook of $3.45 billion, and we continue to expect FY '27 capital expenditures of approximately $270 million, resulting in free cash flow of $3.180 billion, growth of 15%. In closing, we remain focused on the potential for AI to transform our HCM and finance solutions. While still early in this journey, we are beginning to see the benefits from AI to our business model across both the top and bottom line, and we are executing on a framework to drive long-term growth while expanding GAAP and non-GAAP margins.

We look forward to updating you on our progress in the quarters ahead. With that, I'll turn it back over to the operator to begin Q&A.

[Operator Instructions] And our first question comes from the line of Keith Weiss with Morgan Stanley.

Congratulations on a really nice start to the fiscal year. A lot of really bullish signals that we're getting on sort of the AI adoption. I wanted to ask a broader question. And maybe, Aneel, I'll ask you to kind of do my job for me because I'm trying to create a broader argument.

You said at the beginning of your remarks that nobody is looking to sort of rebuild the core Workday system and that core transactional engine. And I agree, and I think most investors agree with that statement. I think where more of the concern is the additional functionality that Workday can be selling to these organizations, which kind of drives growth, that there's a new competitive dynamic there and maybe a new value proposition there. And I think where investors perhaps are getting it wrong is assuming that because the cost of software development is coming down with cogeneration tools, there's a change, a significant change in sort of the TCO of getting that additional capability from Workday versus building it themselves.

And I think what investors get wrong is they're looking at it too narrowly in terms of what creates that TCO. So can you help kind of round out that equation of when your customers are looking for those innovations, obviously, the innovations have to be there, but they're also looking for a good TCO. How does Workday now stack up in that TCO versus building it yourself using these Agentic cogeneration tools?

So first of all, Keith, thank you for all the time that you spent on Workday. I know it's your last call, and we very much appreciate all the time you spend with us and wish you all the best in whatever you choose to do next. So I guess I'd answer it in 3 prongs, and I'd hand it over to Gerrit.

When I look at the world of Agentic in enterprise, we have this concept of lawful and lawless agents, lawful being done the right way, lawless going directly against the data and getting results that bypass security or bypass the business process framework. I have yet to meet a single customer that wants to do things in a lawless way. They all have to follow lawful. If they follow lawful, there are 3 paths for us to be successful.

One, the best path is for us to sell our own agents, and there's a clear TCO on those agents. And I think we've defined that, and we're seeing the success with those agents. Second is they can use Extend Pro to build their own AI applications, again, leveraging our platform. And the third is as we roll out these AI APIs on a consumption basis, that's the way that third parties could build Agentic applications, but they still have to use the rails, the security, the governance, the business process framework to make sure they're doing it in a lawful way.

And again, I'll just say there's not a single customer that wants to do things in a lawless way now in the world of HR and finance. And so I don't know if you want to add anything, Gerrit, but I think it's, I think I feel pretty well covered, Keith, in having a solution for whatever customers would like to do.

Yes. And I think Aneel said it well. First of all, we embrace the ecosystem of builders. Actually, we provide APIs as part of the Workday platform, so customers can continue to build their own solutions and partners can continue to build own innovations that are part of the Workday platform and ecosystem. That in itself for us is a huge accelerant and value add and captured in our API Flex credit model.

But I think the real point here, Keith, is that for differentiated AI solutions that drive real value, which are not just augmentations, but actually redefining how HR and finance operates by taking big labor spends and making them smaller software spends, you need to have the 3 ingredients that only Workday has. One is the world model of work, our compounding data set, which lets you actually contextualize AI systems. Secondly, what Aneel spoke about, all of the deterministic business process logic that defines policy, compliance, correctness in the key processes from managing people to closing the books.

And then thirdly, not to forget, it's all about being deeply embedded in the flow of business, right? Us providing that as part of the business processes as they happen, financial transactions, hiring decisions, pay cycles allows us to actually automate the work in the background and not just being a side panel that comes in without a true integration in the flow of work. So we feel really strong about both our platform and openness and the differentiation of our first-party agents.

Outstanding. That's helpful guys. And Aneel and team, it's really been a privilege covering Workday over these past 2 decades and seeing what you guys have built here. So thank you very much.

And our next question comes from the line of Gabriela Borges with Goldman Sachs.

I would love to hear a little bit more about the feedback you're getting from customers as you deploy Agentic. Sometimes what we notice is there's a gap between how these products and technologies perform in a sandbox or on a demo versus what customers are actually able to implement. So maybe just walk us through when you present some of the newer technologies like Sana or some of the organic Agentic development, what is the gap that you have to work with customers on? Or what are the limiting factors to them fully getting the value out of the agent? And how do you work with the customer to solve them?

I'll put it to Gerrit and to Rob. I think there's a piece for both of them in that.

Yes. First of all, what we, Gabriela, is that for us, the big difference is we engage on very specific problems when we speak about AI. We are not coming in generically with a broad exploration of what may be possible. We are solving concrete problems in the value chain from hire to retire to our financial processes from record to report, and that makes it very focused and value specific. So that alone in itself allows us to avoid that POC-driven unclear ROI scenario.

And because of all of the success that we have in that space, we can actually guide customers to the best practices, right? We know how Chipotle, 7-Eleven and so many others have transformed hiring, how NetApp transformed procurement. And that allows us to have a very specific value-oriented conversation. So what we are seeing actually right now is a very fast takeoff on our first-party agents. And frankly, for us, the challenge is how do we meet this demand curve, right?

So we are now starting to provision self-service agent to all of our customers because actually, we got so many inbound requests that we felt it's easier for us just to turn a default on than to have services engagement being wrapped around it. And the last part before I hand it over to Rob, I think what you are pointing to, the true change is changing in the business processes and the operating model of companies when they decree a much higher degree of automation. And that's not a technology change, right? That's a workforce transformation that's happening at multiple levels at the same point in time.

And this is why we've created our forward deployed engineers and our AI consultants. So they go in and they're not just bringing the technology, but they are really engaging on the business process transformation itself and guide our customers through it. Rob?

Yes. I would just add, Gabriela, that we've had, I don't know, maybe 100 customer touch points between Aneel, myself and Gerrit in the last 3 months. And the feedback from all of them have been overwhelming, actually positive, where these customers are really focused on how our agents can help them in the flow of work and what they're doing.

And certain agents have had tremendous success early on like deployment agent where existing customers can see the value immediately and they're actually selling to other customers and customers are your best sales folks. So I would say that's super optimistic, and they all come in with questions on where we are and they all leave with how do we actually get started. As Gerrit said, with Sana as the front door, we're launching that in a big way. And then I'd say with Sana Enterprise, we're more focused on use cases, working with our customers to build use cases that add tremendous value to them. The uptake there on big brand names has been incredible. We ran the Sana Lighthouse program and the demand has been, as I said, overwhelming early on, I would say, the same here.

And our next question comes from the line of Michael Turrin with Wells Fargo Securities.

Aneel, maybe you could speak to just the early progress. I know last quarter, there was commentary just around reprioritizing growth. This quarter, you mentioned best new ACV 1Q in 5 years. So maybe just speak to the progress and what you're seeing within FlexCredit or Agentic usage or some of the efforts there and then Zane, maybe just to complement how you're able to expand margin while still prioritizing growth at the moment.

So I guess I'd say a lot of the right work was already being done when I came back. Gerrit and team were on the right path, building the right agents, building the right infrastructure and we're now seeing the fruits of those efforts. And we're just getting more focused on what those efforts are, right? We're focused on building organic agents, and that's going extremely well with self-service agent and deployment agent.

The acquired agents continue to be strong. And as we roll out more of those agents, we're going to see continued momentum. But we're also doing some really great work on the APIs, which is going to be the way we monetize the headless transaction. So the pieces are coming into place. It's really about reprioritizing to be AI first and AI native as opposed to AI being part of our story.

When you go through a technology transition, and I'm old enough to have been through a lot of them, you've got to put that technology transition front and center. And our core business is strong. But the 150th feature in HR or finance is not going to move the needle for our business. The next Agentic application will. I don't know if you want to add anything to that, Gerrit.

I think you said it well. And like Aneel has described, what we have changed at Workday and have laser focus now is either building APIs for AI or building AI agents. And that allows us really to be fully focused on the biggest opportunity ahead of us.

So Michael, I'll just add on the margin side. Obviously, we're very pleased with the revenue performance in Q1, which always helps you on margin. The same being said, as Aneel said, coming back with focus and the teams across the company are focused on how we work faster, how we stay focused in each area and disciplined in where we make hires and the work that they're doing.

And on top of that, we're recognizing the benefits on AI ourselves. So within Gerrit's team and R&D, we're seeing tremendous productivity improvements, whether it's our customer success business, we're seeing productivity improvements there, a lot of Rob's team on go-to-market as well. And we're using our own products, as you would expect us to. So very pleased with the progress we're seeing, enabled us to move up the guide 50 bps over the course of the year, and we look forward to continuing to increase our margins over time. So we remain focused in both the top line and the bottom line and investing in key areas here.

Yes. And if I could just say, this is more aspirational than anything else. I'd love to see us continue the growth that we had in Q1, but keep headcount as close to flat for the year as possible because we are getting the benefits of using our own products and other AI tools. And I think that's where I think I'm hopeful and believe that we're going to have additional margin expansion as we get those benefits. And I would say that's different than what my view was coming in 3 months ago.

And our next question comes from the line of John DiFucci with Guggenheim Securities.

Aneel and team, a really nice job on the execution this quarter. But I actually have a question related to the Sana AI Summit today in New York. Your new Chief AI Officer, Joel Hellermark, talked about not playing it safe in what is a technology paradigm shift. This all sounds good, and Workday has a leadership position. And Aneel, you know this as well as anybody, the innovator's dilemma is a strong force.

So with that context, I sort of have a high-level question for Gerrit and maybe, Aneel, if you want to join in, too. Gerrit, how do you, as the product leader at Workday, ensure that you do not only enable this paradigm shift happening with Workday, but actually lead through it. And is it possible to do that while leveraging the leadership presence you have built since the last paradigm shift? Or do you have to sort of abandon stuff?

Yes. Thank you for that question, and thank you for attending Sana AI Summit today here in New York, truly a landmark moment, I think, for us and for the industry. And what you have heard today, I just want to break it down very clearly. So we all understand what we say, we are not playing it safe and driving deep AI innovation.

For AI, it's all about understanding what the key value levers are. And as we have said earlier, right, with Workday's world model of work, we have a set of data which allows us to rethink business processes that weren't part of Workday's remit today. And because of the AI leverage that we are getting that Zane described in just productivity, we can execute so fast.

So today, what you've heard that we announced our travel agent. We didn't do travel before, but we did expenses. We did projects. We have the worker profile and the pay cycle, right? So now we can actually venture in this new area by just bringing this together in one seamless experience without taking on a high degree of functional development cost in the travel space because through AI, the data that we have and the productivity leverage, we can bring it together on the Workday platform.

And I think the even bigger one, I think this was the context that Joel spoke about. We also launched Sana for ITSM today. And it's all about being really intentional here. The most complex, the most expensive journeys in ITSM are related to the employee life cycle. Those are all events that we have inherently in the Workday platform already, recruiting, onboarding, offboarding, team changes, relocations. Now taking that and actually extending that out now to the complete workflow automation that sits beyond HR service delivery to IT service delivery suddenly feels super natural.

Basically, AI makes us boundaryless or limitless, right, in the opportunities that we can pursue. And when Joel spoke today at the Sana AI Summit is that we think of ourselves as an AI challenger, not as a defendant. And we are putting intentional investments into areas where we know we have all of the benefits already at Workday today to go out and disrupt places.

And I would just add to what Gerrit said, John, and echo what you said about thank you for attending the event earlier. Playing it safe is not, not playing it safe is not like we're going to take risk with security or governance. It's more that I think AI sort of resets competitive boundaries, and we can make bets in a bunch of new markets. All the bets don't need to work. If we make 3 or 4 bets and 2 of them work, that's a huge success.

And I think that what you're going to see is us is, first of all, doubling down on what we're doing in AI within our HR and finance world, but also taking some bets that expand our TAM because they're there for the taking. Our data model with HR and finance happens to be a very robust data model that really captures every business object under the sun to build other applications. And I think that's one of the reasons why we have that flexibility.

I got to say this is one of the first times I've heard an application company talk about things, and it's not restrictive when it comes to AI. It's actually expansive. So it's still early, but thanks for those answers.

And our next question comes from the line of Brad Zelnick with Deutsche Bank.

Gentlemen, I wanted to ask about deployment agent, reducing the cost and time of deployment. I remember the impact of launch years ago, which was targeted at the mid-market, but then we saw it become a competitive weapon even in the low end of enterprise. How would you compare deployment agent perhaps to launch as an incremental unlock helping to reduce TCO and make you even more competitive, but also could it positively impact seasonality of your business and being able to sign deals even later into the calendar year for customers that might want to go live by the beginning of their next fiscal year. Any additional thoughts about deployment agent would be great.

I think it's Rob and Gerrit.

Yes, let me go first. So I mean, for deployment agent with new implementations and Workday GO, we're seeing, what are the numbers you're seeing?

30% on current projects and 50% reduction in the projects that we are just starting now.

And so that, and that will continue to improve and change the whole dynamics around implementation and speed to implementation. So it goes to your point early on about can customers go live faster? For sure, we would definitely think that's a possibility, and we'll definitely get there much quicker. The hard work in implementations, master data testing and that becomes just so much more effective and faster. So that's a benefit.

And the part that I'm really quite excited as well is the existing customers that are deploying deployment agent. I mentioned the state of Arkansas and the benefits that they receive, the existing customers using the deployment agent when they want to change configuration and they want to do things. They don't have to go out to RFP. They don't have to go talk to a systems integrator. They can see what they need to do themselves. And that makes it very self-service in these large institutions. And that enables them to move much faster to deploy different business models as well. So I think there's broad coverage with it, and there's going to be a broad impact with it as well.

And Brad, since you asked about launch, so launch is a method, which basically has a scope of Workday and an implementation method that allowed us to super streamline it. Now deployment agent is actually applying AI to automate that entire process. So it's the next logical step, if you think about it from improving that method further to make it AI automated.

And the mission of that team, right, the mission statement itself is the $0 deployment of Workday in a month. So we are doing exactly what you already have led to. We are taking now the launch scope and basically drive it with deployment agent to significantly increase the automation, which directly translates to the reduction in project time and customer cost at virtually the same amount.

And we are still at the beginning of that. We are super confident that with that, we can completely squash migration complexity and deployment times for customers to a degree. But the whole consideration in the mid-market, for instance, if you move to Workday or not because time of migration, cost of migrations are a consideration. Our ambition is to make this a completely nonissue. And with that, unlock for our customers Workday at scale.

And our next question comes from the line of Alex Zukin with Wolfe Research.

Maybe just a quick 2-parter. Aneel, for you, it's rare when Q1 has a net new ACV acceleration. It sounded like it was something kind of was a little bit different this quarter, particularly on the net new side. So maybe just dive in, what are you seeing out there in the demand environment? That's not happening for every other application software company clearly. So kind of what do you think is different from a Workday perspective that drove that incrementally better execution?

And then, Zane, just maybe any high-level commentary on how much, if any, DIA benefit you guys saw in the quarter that I think Rob alluded to in the prepared remarks. And just kind of when do you think we'll start to see some of this accelerating bookings that seemingly is kind of happening under the hood actually reflect in some of the cRPO dynamics?

So I'd say, first of all, one quarter does not make a year. So we're optimistic heading out of Q1, but we've got a lot to play for, for the rest of the year. I do think, candidly, I think there were some deals that slipped from Q4. We always talk about how the deals slipped from Q4, we'll close them in Q1. Well, Rob's team really did close a lot of great business in Q1.

But the reality is if you look at the split, the AI products are driving the growth. And what's exciting to me is that the organic products are showing great promise and they're getting early acceptance and deployment, but they're still in the early days. And I think towards the second half of the year when they're deeper into general availability and more customers are using it, and we're on the Flex Credit model. I think it just, it's all goodness this year as we build towards that AI growth. And Rob has done a great job of making sure the sales force and services teams are aligned to driving that growth, not just out of the core, but really focused on the AI growth.

Yes, Alex, as you touched on, we were pleased to see DIA come into the first quarter. As Aneel alluded to, it was a great quarter for a number of reasons with linearity. We recognized some DIA revenue, not significant, but some DIA revenue in the quarter. And unlike last year, we expect to recognize that revenue over the course of the year. If you recall, last year, it was back-end loaded.

So we're pleased with how we'll recognize that revenue over the course of the year. And then as Aneel mentioned, with a lot of the Flex credit sales and the momentum we have in our sales and in AI, we expect to see those bookings ramp up over the course of the year. So have a larger booking impact into the second half and we would expect because of the recognition of revenue to see that impact FY '28 to a greater degree.

And our next question comes from the line of Brent Thill with Jefferies.

Aneel, for Sana, when does this start to get fully integrated? And when do you feel like this starts to have an impact on deals? And maybe the answer is right now? And a second follow-up with Rob and Zane, just on the quarter, just to follow on on Alex's point. Were there any, were there less changes to the sales go-to-market this Q1 than you've had maybe in past Q1s? And I know you mentioned there are some slip deals, but perhaps there's also less tinkering with the go-to-market team that gave them more time in the field to sell or...

So on the first one, it's available today. It's fully integrated. We need to move more customers on to our equivalent of the innovation services agreement. But the uptake has been super rapid. On the Sana learning piece, that was also a good, we also had a good quarter there. And the rest of Sana is more about what comes next with some of these newer applications. I don't know, Gerrit, if you want to add anything. But it is now the new front end for Workday. I mean that is de facto default that is the new front end for Workday.

Yes. The only piece to add is that at the end of May, we're going to provision Sana for Workday and self-service agent to all of our customers on our current AI terms of service and make it basically the default deployed solution as part of their contract, further unlocking it. So it's going to be a huge surge for us again.

Yes. And on the field, was there less changes year-over-year, I would say we were very prepared for coming into financial year 2027. We had planned this very early on. We knew that we needed to move to a denser model with customer base because of the agents and what we're doing with organic, inorganic agents and agents. So we were super ready for that.

And we had broad-based success on a global basis. North America did really well. EMEA came back strong. Our international business with Europe was very good. Japan was very good. We had a strong net new quarter and a strong large enterprise quarter. So I would say we were ready for whatever changes we put in place, and it was not disruptive, obviously, and we had very good linearity all through Q1.

We will now take 2 more questions. Our next question comes from the line of Karl Keirstead with UBS.

Okay. Great. Maybe, Rob, just sticking with you. Just as investors and I watch the number of risks pick up in the tech sector, and we worry a little bit about seat compression spilling over into the non-tech sector. I just wanted to ask you what you're seeing in terms of seat growth versus module expansion as drivers of that nice overall expansion that you highlighted on the call.

Yes. So I would say we see a long runway with the value sales and the agents and what we're doing with Flex credits, the launch of Sana into the market and broad-based. We see that, and we said early on, I think last quarter, we mentioned that the back half of the year, we continue to see, and that we definitely continue to see that.

On the FSE expansion, I mean, we continue to see expansion in the overall when we look at the amount of customers. As we acquire net new customers, we bring in new customers on board, and we continue to do pretty well in the net new space, and I still think there's opportunity there. But I would say, ultimately, a broader part of our business is going to move to the Flex credit type environment with APIs and consumption.

Karl, I'll just add, we've commented over the last number of quarters on, as it relates to FSEs. And as Rob alluded to, it's been flat or marginally up. And this quarter, I'd say flattish. But to your point on the technology sector, obviously, we've got a diverse customer base. I mean we've seen any declines in the tech sector more than offset in other areas. So there's been a balance. There's definitely been movement. We did see it in the tech sector specifically, but we've been flattish. And as I pointed out in my prepared remarks, we've seen good net expansion more broadly. So it's not a meaningful part of our revenue growth.

Yes. And I think it's really important to recognize that if FTE count does go down, it's being replaced by AI is replacing labor, not software right now. And as long as we do what we are doing right now and continue to execute, we're a beneficiary of the shift to Agentic work.

And our final question comes from the line of Raimo Lenschow with Barclays.

Congrats from me as well. Just a quick one for Zane. RPO, like cRPO, like as we expected, RPO was slightly lower growth. Can you talk a little bit about, is that kind of customers signing shorter contracts or there's a duration effect? Can you just talk to the puts and takes there?

Yes, happy to. I mentioned on the last call as well, we've actually seen real consistency in duration and RPO at the highest level is more driven by the mix of customer base versus net new offerings. And over the last couple of quarters, I've called out that we've been pleased with the growth on customer base as a mix. And the duration for each of those has been pretty consistent. But when you do a renewal, it tends to have a slightly shorter duration than a net new offering. So it's simply been that mix that's driven any difference between cRPO and RPO.

Ladies and gentlemen, thank you for your participation on today's conference. You may now disconnect.

Ladies and gentlemen, welcome to Workday's Fourth Quarter Fiscal Year '26 Earnings Call. [Operator Instructions]

I will now hand the call over to Justin Furby, Vice President of Investor Relations. Please go ahead.

Thank you, operator. Welcome to Workday's fourth quarter fiscal 2026 earnings conference call.

On the call, we have Aneel Bhusri, our CEO; Gerrit Kazmaier, our President, Products and Technology; Rob Enslin, our President and Chief Commercial Officer; and Zane Rowe, our CFO.

Following prepared remarks, we will take questions. Our press release was issued after close of market and is posted on our website, where this call is being simultaneously webcast. Before we get started, we want to emphasize that some of our statements on this call, particularly our guidance, are based on the information we have as of today and include forward-looking statements regarding our financial results, applications, customer demand, operations and other matters.

These statements are subject to risks, uncertainties and assumptions that could cause actual results to differ materially. Please refer to the press release and the risk factors and documents we file with the Securities and Exchange Commission, including our fiscal 2025 annual report on Form 10-K and our most recent quarterly report on Form 10-Q for additional information on risks, uncertainties and assumptions that may cause actual results to differ materially from those set forth in such statements.

In addition, during today's call, we will discuss non-GAAP financial measures, which we believe are useful as supplemental measures of Workday's performance. These non-GAAP measures should be considered in addition to and not as a substitute for or in isolation from GAAP results. You can find additional disclosures regarding these non-GAAP measures, including reconciliations with comparable GAAP results in our earnings press release, in our investor presentation and on the Investor Relations page of our website. The webcast replay of this call will be available for the next 90 days on our company website under the Investor Relations link.

Additionally, the prepared remarks of this call and our quarterly investor presentation will be posted on our Investor Relations website following this call. Our first quarter fiscal 2027 quiet period begins on April 15, 2026. Unless otherwise stated, all financial comparisons in this call will be to our results for the comparable period of our fiscal 2025.

With that, I'll hand the call over to Aneel.

Thank you, Justin, and thanks to everyone for joining us today. It's really nice to be back with all of you. Before I get into my remarks, I wanted to thank Carl for his service to Workday over the past 3 years. He brought the operational rigor and discipline that we needed at the time to make Workday a larger and more global company. That work helped us set the foundation for this next chapter for Workday, and we're all grateful to him.

In terms of chapters, we talk internally about this next chapter of Workday as Chapter 4. First was the founding of the company by David and myself back in 2005, based on the new idea of HR and finance in the cloud and built on a set of core values around employees, customers, innovation, integrity and fun.

The second chapter was a period of hyper growth that led to our success with many organizations around the world and product and technology leadership in HR and finance. The third and most recent chapter, which started in 2023 was all about operational excellence and efficiency as we grew into a Fortune 500 global company.

While Chapter 4 is now upon us and its return to focusing on innovation. When we founded Workday, we transformed the enterprise by reimagining HR and finance in the cloud. Now we have the opportunity to transform it again by reimaging HR and finance with AI, and taking advantage of this new vector of growth.

You've all heard the narrative out there that HR and ERP will be replaced or relocated to the background by AI. I personally just don't see that happening. Our application domains are really, really hard to build. I've been working in the HR and ERP space for over 30 years. These are true systems of record that must process transactions with absolute accuracy and speed in force complex security models and comply with statutory and regulatory requirements all over the world. That kind of complexity is very hard to replicate. No amount of Vibe coding is going to produce an HR or an ERP system.

And importantly, our underlying business processes are deterministic by nature. There is a start and end to a business process. Its goal is to deliver consistent audible outcomes. AI for all of its incredible capabilities is probabilistic by nature, it reasons, predicts and recommends based on patterns and likelihoods. Maybe it'll eventually become a state machine, a system that follows the same steps and gets the same result every time, but it is not there today.

You can't have probabilistic outcomes in running a payroll. It needs to be 100% accurate and completed 100% of the time. So what is the future? It's the marriage of deterministic enterprise apps with probabilistic AI that leads to 3 things: a redefined user experience is prompt based, a greatly improved business process automation and execution platform with work done by agents and humans; and lastly, much deeper AI-generated insights.

Taken together, these changes will lead to much better business outcomes and deliver far higher ROI for our customers. As you'll hear from Gerrit, this hybrid world and architecture is exactly what Workday is building today, marrying the best system of record for HR and finance with the reasoning capabilities of domain-specific LLMs. That's the future. It's like Peter Butter and Jelly, they just go together. And it stall-rooted in the trust we've built with our customers over the past 20 years for managing their systems in their most critical data.

All you have to do is look back at the past year to know that this hybrid world is coming to fruition. We experienced accelerating in agentic AI adoption across the solutions we acquired, [indiscernible] Score, Evisort, Paradox and most recently, Sana. They all had great Q4, and I'm pleased to say that Sana is now seamlessly integrated into the Workday stack. It's very cool.

So as we move into fiscal year '27, what should you expect from us? Our core enterprise apps and HR finance to student will continue to thrive, recognizing that in some areas like HR, we have high levels of market share, so the growth will come from new apps sold to the customer base. The accelerating growth will come from the agents we built on top of Workday, both inorganic and organic.

If FY '26 proved that customers trusted Workday to buy our acquired agents, we believe that FY '27 and beyond will prove that customers will buy our organically built agents that are in early access today. Across the board, these new agents are deeply embedded into the Workday core, are meaningful in their scope and have significant ROI attached to each and every one of them.

Those of you who know me know that I'm an unabashed optimist. I truly believe that our investments in agentic AI will enable Workday to reaccelerate growth increased customer satisfaction and set us up for long-term leadership. I will end by saying that I'm excited to be back. This is a fun time to be a product person.

And now I'll turn it over to my friend and leader of all things ERP and AI. Gerrit?

Thanks, Aneel, and hello, everyone. Anil described the opportunity really well. AI's changing our work gets done, and we are unlocking its transformative power for HR and finance. The foundation for enterprise AI is taking the right action inside a governed business process with the right permissions, oversight and policy configuration, whether that's hiring and onboarding, payroll or the financial close, simply connecting powerful language models directly to enterprise data, well, that risk creating lawless agents that may have vast capability, but they have 0 guardrails.

We are building Workday as a context and tools engine for AI with deep HR and finance data, a business process framework and a strong security model to deliver enterprise great accuracy and business outcomes. Based on this, we leverage AI for entirely new business processes. Be it built for enterprise AI transformation, where, for instance, every employee can have a career coach who develops them along their journey. Every sales team can have an AI contract agent specialized in every engagement. Every candidate can have an AI personal job search agent, every finance professional their personal AI analysts and every employee, their own AI HR business partner agent.

So now let's look at some real customer AI usage and work today. We master every time an AI model produces a result in Workday as an AI action. In full year '26, we delivered 1.7 billion AI actions across the Workday platform and this is all organically developed AI and Workday. You can also see this incredible momentum commercially, in Q4 we generated over $100 million in new ACV from emerging AI products. That's growing over 100% year-over-year and our overall ARR from the solutions is now over $400 million.

We expect AI usage and business impact to continue to expand meaningfully in FY '27. Today, we have 12 new organically developed role-based agents that are now starting to move into general availability for all our customers and more than [indiscernible] customers are already using them and get real ROI. With our self-service agent, early access customers have reduced HR [indiscernible] volume by 25% and increase their employee productivity by 20%.

And with our [indiscernible] release in March, in addition to our self-service agent, planning agent, deployment agent, payroll agent and business process optimize agent are all entering into general availability for all our customers.

And here is another real highlight for us the release of Sana Core and Sana Enterprise into general availability. Sana Core brings conversational AI directly into Workday. So employees can get answers and complete tasks using Workday agents. Sana Enterprise extends the same experience beyond Workday by connecting enterprise tools like outlook and Google Drive and so many more.

So employees can find information create agents and automate workflows all in one place. That will create an entirely new way for our 75 million users to engage with Workday. Sana Core and Sana Enterprise went into GA on February 15, which we executed with world-class speed from projects start to finish in just 3 months.

We used AI to dramatically accelerate our product innovation cycle time. We accelerated key API development by roughly 30x on Workday's Core platform using AI. More than 75% of our software engineers are using AI coding assistance and more than 50% of the committed code is AI generated. We have seen an incredible 22% growth in engineering output over the last 6 months, measured by the number of code updates we delivered.

Our strategy is to build new business processes designed around virtually unlimited AI reasoning to automate entire business processes into the background with AI agents and to deliver a beautiful AI first use experience that brings super intelligence to work.

And with that, I'll turn it over to Rob.

Thanks, Gerrit, and hello, everyone. It's great to be on the call today. As we look back at Q4, one thing is very clear. Our customers trust Workday with the parts of their business that have to run flawlessly. On payroll to closing the books, and that trust continues to show up in a high retention rate and in customers expanding the use of the platform year after year.

With over 11,500 global customers, expansions remain our largest growth engine. In the quarter, we expanded with customers like Anthropic, Ally Financial and Otis Elevator. In Q4, AI played an increasingly meaningful role. It was involved in roughly half of our customer-base transactions and expansion deals that included AI were nearly 50% larger on average.

While it's still early days, we've seen great initial traction with Sona, since the acquisition closed in November. We're starting to see customers go all-in on agents and agentic workloads, and Accenture is a great example. They're reinventing HR and recruiting at scale, using our AI solutions to elevate the employee and candidate experience, while driving improvements in productivity, speed and agility.

Accenture has also been a key design partner for us, helping to develop our agent system of record. And with our Flex credit pricing model, customers can better align their spend with the value they're getting. Accenture, Nike and Merck are among the first of nearly 50 customers signing on to use our new model.

We expect Flex Credit adoption to continue to grow as we expand our AI road map and mature the model. We're also investing in our customer base motion, including 4 deployed engineers to activate agents faster and with less friction for our customers.

Turning to net new. We formed several strategic relationships in the quarter, including Boston's Children Hospital, the State of New York Unified Court System and Sargent and Landi. We're seeing particularly strong momentum in net new medium enterprise deals. Any customers drove roughly 60% of net new ACV in FY '26. To accelerate time to value in the segment, we're expanding Workday go globally, helping customers get up and running faster in a more standardized way. At the same time, some net new large enterprise deals are taking longer to close, particularly in Fed, Slade and health care and across parts of the commercial market.

While this impacted the volume of net new deals that closed in Q4, most opportunities remain active in our pipeline and a few have already closed in Q1. As we look at our international business, we see significant opportunities ahead. We're making good progress in Canada, EMEA, ASEAN and Japan. We've been investing in local talent, partners, product localization and new routes to customers with Workday resellers. While there's still work to do, we believe international will become a much bigger part of our growth story over time.

And partners play an important role in scaling. In Q4, about 25% of our net new ACV was sourced through our partner ecosystem. They're helping customers go live faster, expand more efficiently on Workday and enhance the value of our platform. Workday Wellness is a great example of how we're expanding employee services, while creating new revenue streams with partners.

In Q4, we welcomed Lira Health, Empathy and Avid to the program. As we move into FY '27, the team and I are focused on turning all of the innovation Gerrit talked about into tangible outcomes for our customers, faster time to value, broader adoption and deeper platform commitments. We are well positioned to build on this momentum and play an even more important role as customers modernize their HR and finance operations.

And with that, I'll hand it over to Zane to share more details on our results.

Thanks, Rob, and thank you to everyone for joining today's call. As Rob mentioned, our results this quarter reflect the deep trust customers place in Workday to manage their most critical assets. This is creating durable expansion opportunity, particularly as adoption of our AI solutions accelerate.

Turning to results. Subscription revenue in Q4 was $2.360 billion, up 16% and full year FY '26 subscription revenue was $8.833 billion, growth of 14%. Revenue in the quarter benefited from the successful delivery of the DIA contract, which added nearly 1 point to Q4 subscription revenue growth. Total revenue in Q4 was $2.532 billion, growth of 15% and for the full year was $9.552 billion, up 13%.

U.S. revenue in Q4 totaled $1.91 billion, up 15%, and international revenue in the quarter was $626 million, growing 13%. For the year, U.S. revenue was $7.18 billion, up 13% and international revenue was $2.38 billion, up 12%. 12-month subscription revenue backlog or CRPO, was $8.83 billion at the end of Q4, growing 15.8%. Total subscription revenue backlog at the end of Q4 was $28.1 billion, up 12%.

Average contract duration in the quarter was down year-over-year, driven by a higher mix of renewal and customer base activity. Gross revenue retention rates remained strong at 97%, demonstrating the mission-critical nature of our platform and our high customer satisfaction. In addition, net expansion rates remained consistent through FY '26, contributing roughly 60% of our subscription revenue growth for the quarter and the full year.

Non-GAAP operating income for the fourth quarter was $774 million, representing a non-GAAP operating margin of 30.6%. Margin strength was the result of solid revenue growth, ongoing efficiencies we are driving across the business and a slightly slower ramp in hiring. Full year non-GAAP operating income was $2.82 billion, reflecting a non-GAAP operating margin of 29.6%.

Q4 operating cash flow was $1.28 billion, resulting in full year operating cash flow of $2.94 billion, growth of 19%. Free cash flow for the quarter was $1.22 billion and for the year, it was $2.78 billion, up 27%.

We repurchased $1.5 billion of our shares during the quarter and $2.9 billion for the full year. We had $2.9 billion in remaining authorization as of quarter end. We ended the year with $5.4 billion in cash and marketable securities. Our head count as of January 31 was 21,070 workmates around the globe.

Now turning to guidance. We are focused on driving adoption of our agentic solutions, including Sona, Paradox and other Workday agents as well as our Data Cloud, which ramp and availability throughout the year. We expect FY '27 subscription revenue of approximately $9.925 billion to $9.950 billion, growth of 12% to 13%. We anticipate Q1 FY '27 subscription revenue to be approximately $2.335 billion, growth of 13%.

As we mentioned last quarter, this year's sequential performance is impacted by the DIA contract, which added nearly 1 point to Q4 subscription revenue growth and is not expected to continue in Q1. We expect CRPO to increase between 14.5% and 15.5% in Q1. We expect subscription revenue to increase roughly 5% sequentially in Q2. We anticipate FY '27 professional services revenue of approximately $710 million as we continue to leverage our partner ecosystem.

For Q1, we expect professional services revenue of $180 million. We expect FY '27 non-GAAP operating margin of approximately 30%. And for Q1, we expect a non-GAAP operating margin of 30.5%. This outlook incorporates an accelerated pace of AI investment across both product and go-to-market.

We expect the Q1 GAAP operating margin to be approximately 19 points lower than our non-GAAP operating margin and the full year FY '27 GAAP operating margin to be approximately 18 to 19 points lower. The FY '27 non-GAAP tax rate is expected to be 19%.

We expect FY '27 operating cash flow of $3.450 billion, and capital expenditures of approximately $270 million, resulting in free cash flow of $3.180 billion, growth of 15%.

As Aneel mentioned, we are focused on what we believe is a generational opportunity for AI to revolutionize our HCM and finance solutions as well as open new markets. While we remain committed to our medium-term subscription revenue growth targets, we are prioritizing incremental investments in our agentic AI road map to capture a larger market opportunity.

We remain focused on both GAAP and non-GAAP margin expansion, albeit at a slower pace in the near term than what we previously communicated. We believe this investment will drive a more durable growth profile that optimizes for long-term operating profit and free cash flow. We look forward to sharing our progress over the next several quarters.

With that, I'll turn it back over to the operator to begin Q&A.

[Operator Instructions] And our first question comes from the line of Mark Murphy with JPMorgan.

Aneel, welcome back to the CEO role. I'm curious how you -- how are your picture shaping the next chapter for Workday, specifically as it relates to differentiating the AI strategy. And for example, I'm wondering if you see some ways to push a more aggressive pace or more organic AI product road map, maybe trying to achieve a 0 day close kind of a vision or a agentic consolidation or some other type of truly breathtaking outcomes.

Well, it's good to be back Mark. It's good to hear a voice. I'm very optimistic about what we're doing on the agentic front. And you highlighted 2 use cases that we're actually building. I'm going to turn it over to Gerrit in a second.

But when I look at where our business is today, the core is rock solid. We built these great HR and financial applications and they continue to grow. And we have this opportunity to build these agentic solutions on top. We've already shown that the acquired solutions are generating pretty rapid growth.

And as the organic solutions, which are even more deeply embedded and frankly harder for anyone else to replicate as they come to market, and we get the customer adoption we're seeing. I'm very bullish on where we're headed. I'm going to turn it over to Gerrit to talk about those 2 use cases.

Yes. Thank you, Aneel. And as Aneel has said, we have a very big ambition for what we describe as lights out finance. So we are looking at a full automation of all the key processes across our suite, including HR. But since I specifically asked about the finance base, the model that we are looking at is supplying continuous AI to the finance processes.

So think about a compliance autopilot, which continuously test and [indiscernible] and transactions. All based on analysis of all transactions that are coming in and then even optimizing them with our document and contract intelligence, for instance, for real-time bookings, making sure they are set at the right value at the right discount rates with your supply chain.

Those are just a few select examples and I think you can all summarize them under the lights out finance vision. And you heard me earlier mentioning that, but I still want to come back to that one more time, all coming together for the Sana AI user experience. So we are thinking about both back-end automation and AI front-end innovation.

And our next question comes from the line of Kirk Materne with Evercore ISI.

Sorry about that. Aneel, I guess Gerrit outlined a lot of progress you guys have been making on agentic, yet the guide for next year seems fairly conservative a little bit below what people were thinking about. Does that reflect, I guess, just your general view that some of the agentic offerings are going to take a little while to sort of make their way into your account base? Or were some of the execution issues in the fourth quarter, you're trying to account for that in the guidance. I was wondering if you could give us some color, obviously, coming into the opportunity to sort of reset the bar. Just kind of trying to get some perspective on what went into the full year guide.

Yes. I guess, first of all, Kirk, it's good to hear a voice. And I'm back in the side, it's only been a few weeks, I'm pretty optimistic about this year. I would hope that we significantly surpassed that. But I'm an optimist, but I see the opportunities on the agentic front that probably are more second half based in terms of the agents coming into production and being used by customers.

And I love our Flex Credit model, which is moving towards this consumption model. So I'll probably put that over to Zane in terms of where we came out, but I'm very optimistic about this year. And I don't know if you remember me when I was a CEO before, but I do try to be conservative on the guide and then beat it.

Kirk, just to add to that, I mean, we still feel like we've got good momentum the guide hasn't changed materially from what we indicated 90 days ago and I'd say business in general is similar to what we saw. Rob called out a few areas within the quarter. We mentioned, obviously, you're lapping a DIA contract that did have some impact in the fourth quarter, and we still believe in our federal business. and are excited about what that will bring to this upcoming fiscal year.

So not a big shift or change. Obviously, we called out some of what we saw in the fourth quarter, and we expect to see some of those transactions and deals still come to fruition through FY '27. And then as Aneel alluded to, we're excited about Flex Credits, but recognize that's probably more of a second half motion, and then you expect to see the revenue come in ratably beyond that. So that sort of an overview of the guide, but no shift in guidance philosophy other than as you can tell, Aneel's excited about us beating it.

And our next question comes from the line of Keith Weiss with Morgan Stanley.

Excellent. And welcome back, Aneel. It's great to be talking to you again in the CEO role.

In the conversation and talking about the sort of organic innovation, should part of our takeaway be that the M&A strategy going to take more of a back seat. It seemed pretty prominent throughout FY '26 or calendar year '25, should we expect you guys to be moving away from M&A in those and buying the AI technology and moving more towards organic growth.

And then maybe like a follow-up for Zane. Within that 12% to 13% growth that we're looking for in FY '27 on the subscription revenue line. Can you give us any indication on what the inorganic contribution to that number might be?

Well, so in terms of acquisitions, I'm not going to say we're not going to do any but we're leaning in pretty heavily on organic development and organically built to agents. And I'm super bullish. It's not that I'm new to what we've been doing. I have been closed with Gerrit over the last 18 months and I'm really excited about what's coming out to market. So that is our primary focus, but we'll be opportunistic if we see another company that's exciting like Asana or a Paradox or Hired Score, we might do it, but that's not -- our focus really right now is on the organic development of agents.

And Keith, as it relates to the guide, similar to how we framed our guide in the past, I'd say not a material component of that is inorganic. As Aneel alluded to, we're focused on organic growth and Were there to be anything more significant, we'd call it out similar to what we did last year as far as its impact on our overall growth trajectory. But not much expected in the FY '27 outlook as we have it presented today.

Excellent. Super helpful, guys.

And our next question comes from the line of John DiFucci with Guggenheim.

I have a lot of questions for Gerrit, but I'm going to ask a question because it wasn't asked yet for Zane and I think it has to be addressed. On the last conference call -- oh, by the way, welcome back, Aneel, it's good to see you.

On the last call, you said there'd be a $15 million in nonrecurring revenue in the fourth quarter, but your guide implies a $25 million sequential decline in subscription in 1Q, which doesn't really seem to make sense for a subscription model. I mean you did say it's a full -- even if it was a full 1% impact to subscription in the first -- in the fourth quarter, that would be $20 million, still $20 million and a $25 million decline. I don't know, can you just help explain what's going on there because I know I'm going to have to do that.

I'll help you out. Yes, as we called out in the fourth quarter, we had the DIA contract, which is not included in our forecast for Q1, so sequentially, there is an impact there. As you note, as with any sort of year that we have less days in Q1 as well, which brings sort of a natural seasonal component to our typical Q1.

And then in addition to that, Rob called out some of the deals that pushed from Q4. Many of them closed in Q1, but a lot of them also are expected to close through the course of the year. So nothing material beyond what I called out with the DIA contract that clearly had a benefit in Q4 and is not expected to continue in Q1.

Yes. But that's just -- that's -- let's say, it was $20 million instead of $15 million. It's a $25 million decline and a subscription model, I don't -- unless you -- some people just didn't renew this quarter at the end of the quarter, but I think somebody said in the prepared remarks that I think it was Rob that the retention rates were high as they always are for you guys.

So I just -- I don't know, maybe it's just prudent, but it doesn't make sense that excluding the DIA deal, even the 2 days delta between the fourth and the first quarter, I don't mean to dwell on this, it's just important. It's just numbers here. Is it just prudence? Is that what we should be thinking?

No, I mean, look, I mean, we haven't changed our guidance philosophy. The days do matter as you think about the sequential growth as I called out with DIA, I'd actually say we've seen good consistency on the renewal on the renewal side as well. So gross retention remains at 97%.

And then obviously, we're focused on executing well in Q1. So we'll continue to focus on that, but nothing more than that as you think about the sequential decline, at least that you're calling out this year.

And the next question comes from the line of Brad Zelnick with Deutsche Bank.

Great. And welcome back, Aneel. It's great to have you back to the party. My question for you, I appreciate the '27 guidance and the need to invest given the moment. But specifically, any finer details you can provide as to where those dollars are going? And how much time do you envision that it takes to stabilize growth overall.

I think in response to Kirk's question, you talked about in the back half, seeing agentic adoption kick in. But I think investors at this time are really focused on total company growth across all app software, and just any insight you can provide on seeing the agentic offerings, particularly the organic ones translate to overall acceleration.

So I think the business is very stable right now. What I'm very focused on is reaccelerating growth. And you don't get many chances in the career to go through 2 technology waves where I was there at the start of the cloud. I was actually there at the start a client server. I'm old enough. That was there for that, too.

And AI is just a huge opportunity for Workday to reaccelerate growth. The Core is stable. It's more about getting to higher growth rates. So I'm pretty optimistic. And as I've seen what Gerrit's building, I do see the organic agents really coming to market. They're in early access right now. But there are consumption-based model, so there's a delay before we see the actual revenue from it.

I think we end this year, the second half of this year really strongly, and we set up a really amazing following year where we turn into a consumption platform just like the hyperscalers. And that's a material change from the FT model we've had for the entire time I've been part of the company.

And I'm really excited to get to that place where it's -- and it won't just be our agents, it also be all the third-party agents that get built that leverage our APIs that will also be based on that Flex Credit consumption model, too. So there's a lot of upside that I see coming forward.

But I would just start with or end with what I started with, the Core is very stable. Our systems are embedded in our customer sites. We have long-term contracts. It's our opportunity now to build on top of that.

And our next question comes from the line of Raimo Lenschow with Barclays.

Perfect. And Aneel welcome back as well from me. Quick question on -- for Rob, actually, like your -- one of your mandates was to kind of think about more international, international build-out. Can you talk a little bit about what you've seen there in terms of progress?

Yes, Raimo. Look, we continue to see progress in our European business. We've had a couple of really solid quarters. Asian been solid as well in growth. So the Southeast Asian model. We've actually opened up India where we've closed 1 or 2 deals already. And our Canadian business is actually doing really, really well. So I feel like we're doing a really focused job on driving those markets, and we'll continue to see that benefit come through in 2027.

And my expectation is that these organic agents will actually help us reignite as well in our customer base in Europe and in Australia, New Zealand and parts of Asia as well, including Japan.

And our next question comes from the line of Michael Turrin with Wells Fargo.

Great. It seems one of the key questions on Workday seems to be whether you're able to offset just the lower seat growth environment, if that's the world we're in with more product expansion. I think Gerrit mentioned $400 million now in emerging AI ARR. I was just wondering if there's anything else you can tell us around how that impacts the economic profile of those customers who are adopting our expansion rates your observing great or any quantification around how much? And just as a small second part on Rob's comment on 4Q deal elongation. I'm wondering there's any way for us to size any impacts on CRPO there.

Yes. Look, I think some of the deals that moved from Q4, as I said, we see in closing. We don't see them moving out of our pipeline. We just see them elongated. I think we're covering that pretty well with these new products that we sold into the nonorganic agents, which were a significant part of our Q4 business. And as we bring the different releases of organic agents on board, we already have the consumption Flex Credit model in action in Q4.

We saw some success with customers I mentioned in my script. And we'll continue to see as we launch more of these organic agents that the consumption model will actually apply and that's why we're pretty positive about the back half of the year as well.

When we see on the AI agent side, on the economic equation, you can basically see it in 2 key models, if you will, on the one side, the agents are really delivering efficiency gains and to a large degree, transferring labor costs into software costs. We just talked about self-service agent, which we have just put into general availability in 3 months and our early access customers have already seen a more than 20% reduction in case volume, right? So those are not people anymore who have to answer these cases, but the self-service agent processing them autonomously payroll agent, which is now going into GA, one of our big organically developed agent, a payroll compliance, payroll corrections.

It's a huge back-office spend doing that automated and highly accurate. It's a huge efficiency gain for these companies. So that's basically category #1.

Then you have category #2, right? A lot of the agents that we are doing are really leveraging AI to solve unsolved business problems. Think about contract intelligence, document-driven accounting. The reality is that customers don't have an army of lawyers and contract experts matching every transactions against all of their supply chain contracts. But now with our AI model, they can basically make sure they optimize their spend in [indiscernible] and have real net savings based on having full contextual awareness of all of their commitments, all of their supply chain and the transactions happening in real time.

So those are delivering ROI than on basically true business returns. And we have both of these agents, right, back-end automation and new value scenarios.

And our next question comes from the line of Karl Keirstead with UBS.

Okay. Aneel, welcome back to the arena. I had a question for you, maybe zooming out a little bit. So this is a broader question. Anil, you were the disruptor 20 years ago, and you and others forced incumbents at the time, Oracle and PeopleSoft, et cetera, to react. And in many cases, it took them years to actually pivot and some, frankly, didn't make it.

So I just wanted to ask you whether you think a number of SaaS companies are going to have to do something similar and rearchitect their cores, AI enable their cores. And how challenging do you think that process might be, and is the period 20 years ago that you live through a good analogy.

It's a great question. I think it's -- I do think it's different. So in the transition from client server to cloud, it was basically thrown away the old architecture and building a new architecture. In this move from cloud to AI, the difference is AI is built on cloud, right? Every cloud company out there is moving towards AI, but every AI company is actually built on the cloud.

By the way, every -- one of these AI leaders actually runs Workday just for what it's worth, Anthropic, Google and OpenAI all run Workday. So it's orthogonal to that last transition because it's about the data, not about the process. I think that the keys for all the enterprise apps companies are #1 to make sure that they have the right data model to inform the large language models and make sure they're getting the best reasoning results. And in order to do that, it's a big investment in APIs, and we're pretty far along on that path, but I think that's going to be the case for all the SaaS companies.

The second piece is identifying where the savings are going to come for from customers because every technology transition is about ROI and productivity gains. If there's no ROI or productivity gain, there was no technology transition that really amounts to anything. And so we're working really hard to figure out how do we improve business process execution for our customers at a lower cost. And I think that's where the agentic model fits in. What what can agents do to replace human labor. And then obviously, longer term, we've got to figure out what we're going to do with those the humans that are displaced. I think that's an important thing to think about.

But it's a different mindset. It's a role-based mindset as it relates to these agents, what roles are going to get replaced by agentic solutions, and how will that improve the way work gets done. So -- but it is different than the last generation because cloud is not getting replaced is getting built on top of.

Our next question comes from the line of Brent Thill with Jefferies.

Zane, on the operating margin guide, I think -- the Street was looking for perhaps a little more move up? I know you mentioned go-to-market and AI. Is there anything else that we should consider on the guide on op margin? Why you're not seeing any operating improvement on margin?

Yes, Brent, obviously, as you've heard, we're focused on the investments in particular, with AI thinking through both the engineering side, the delivery adoption side and all of the go-to-market elements and I think with Aneel coming in, it gives us a chance, we've made good progress over the last 3 years. We're not done yet. We'll continue to focus on margin and efficiencies and growing that number.

But with this year, we really want to anchor and we think this is the opportunity to dig in and to really grow the business and lean in more on that side, leveraging AI and the capabilities that we have organically. So it's just a focus on that. Again, we feel like we've got opportunities beyond this year to continue to grow it, and we'll just see how the year progresses.

Yes, I'm optimistic on upside to the margin guidance, Brent. By the way, good to hear your voice.

I'm optimistic on that, but it's predicated on believing in our growth story, which I completely believe in and margins will grow with reaccelerated growth. And as we get these organic agents working with our inorganic agents, by the way, the inorganic agents, I don't think we get enough credit for how well they've done in a very short amount of time.

And I'm particularly excited about what we're going to see with Sana, both is our new user experience, prompt-based user experience for all employees in the organization, but also as we move into some new areas that you'll hear about down the road, I think that growth is going to drive incremental margin upside that probably not easy to lock in right now, but I see it coming down the path.

And Aneel, if I can just ask one quick follow-up. Just you've had some departures, Patrick Blair Head of Sales. Can you talk through how you're working through that transition with some of the sales changes in the field?

Yes, I'll turn it over to Rob.

Brent, yes, and Brent, it's pretty simple with Patrick moving on the regional leaders who have real confidence in and have been doing a really good job of over the last couple of years, especially bringing on new solutions and products and driving their business. They'll report directly into me.

And it's all about in AI, it's all about speed of decision-making and urgency. It allows us to move faster and it puts a lot of the decision-making right at the customer where we want it. We're also tying into that, it also allows us to build activation engines for where we're going with for deployment engineers to drive consumption faster, and we want to get that up into the market with incredible amount of speed. And so that's really the focus and around the changes.

Yes. I would just say that I'm excited that Rob has flattened the organization. And in this world, flatter organizations move faster and I'm excited about where the sales organization is headed.

And we will now take 2 more questions. Our next question comes from the line of Alex Zukin with Wolfe Research.

Aneel, welcome back as well from me. maybe a quick tech one for you. You talked about monetizing first-party agents, both organic and inorganic. But I wanted to ask you specifically how you're thinking about monetizing third-party agents you have data cloud as you see more kind of investment construction going across these kind of multi multi-system agent frameworks, how do you guys make sure that you monetize that for the value and the data context that you provide?

And then, Zane, I just really simple one for you. Should we still think about the 35% operating margin targets for fiscal '28 as on the table or not?

So on the first question, Alex, I think you should think of us as an evolving layer on top of hyperscale and in the same way that they charge for consumption of compute cycles and application cycles. We're going to continue to flex that muscle. There are some vendors out there, including some of our peers that would consider them at some level parasites on Workday. They get a free ride on our underlying system of record, and we're going to put an end to that.

If you run stuff off of Workday, whether it's from our agents or third-party agents, there will be -- there's a consumption model tied to it. And Gerrit's really been the driver of that. So I'm going to ask Gerrit to weigh in on that on that as well as it relates to Flex Credits. And then Zane can answer the second part of the question.

Yes. So -- the model that Anil has described really works that we have a tiered pricing structure for AI or programmatic access to the Workday platform and the way how you should think about that is that, we capture consumption form of API calls. They are monetized on Flex Credits. That's the most basic unit. So if a third-party agent chooses to access that layer, they can basically be capture or recapture the value on our side via simple API calls. If they want to get richer information like you has indicated, we also have data cloud. Data Cloud, again, is available on Flex Credits. It provides richer context and if third parties want to aggregate agents, right?

Because we shouldn't think about APIs like in the old days where you have modern agents and legacy APIs. APIs and agents are eventually one and the same thing, right? Our agents, they're all exposed as APIs because we embrace the open macro system, you can use them in Microsoft. You can use them in a Google Gemini. And those APIs, those agent APIs, they have a premium price tag to them, right, because they complete meaningful work. They are not just a simple [indiscernible] API, and if you know a customer or a partner or a [indiscernible], you have all of these choices, right? You can subscribe to our applications and we capture that on Workday pricing. You can build your own agents and then you can decide whether you want to consume more APIs, data context or highly differentiated agent APIs, which are basically aggregating large chunks of work across HR and finance for you already.

Alex, just to add the framework question that you asked. As we've discussed the intent here with incremental investment, is to move up our growth. And we're holding to the range between 12% and 15% that we highlighted at our last Financial Analyst Day, but we believe these initiatives will move us higher on that range than where we otherwise would have been.

With that, as I mentioned earlier, we're investing more into this fiscal year, and we'll update later on in the year at our next financial analyst update on where we believe, a, the growth would be and then where we believe the accordingly sort of operating margin would be at that point in time as well. If you recall, there is a sliding scale and Aneel's focus is on driving the growth more so than just hitting that operating margin exclusively.

And our final question comes from the line of Gabriela Borges with Goldman Sachs.

Aneel and Gerrit, I wanted to link together a couple of the points you're making. Does [indiscernible] is AI being built on top of cloud and then the potential for work dates to monetize any other vendor or a corporate built tool that extracts return information out of Workday.

My question to you is how do you manage the risk that vendors or customers build solutions next to Workday that leverages all the domain experience that you've built, but ultimately, Workday becomes part of this biggest sack such that the incremental value is being accrued in the intelligence way, which would be outside Workday. Maybe just talk to us a little bit about how you manage and mitigate against that type of risk?

Well, I'd first of all say that the API layer that ultimately will become the same with the agentic layer, whether we have the apps on top or a third-party have apps on the top, it's our intelligence layer. It's our metadata, it's our security model, it's our data model. It's our business process framework, and people underestimate the power of our business process framework, they're 20 years of knowledge into these HR and financial applications that even with the best AI, it's going to take 5, 6, 7 years to replicate and we're not standing still. So we want to get to a model where we're pretty much indifferent if it's third parties or us building the apps on top, we get compensated either way through the consumption model.

Gabriela, I think it's a great question. So it allows us to really cut through the [indiscernible] I think. Look, the reality is the question is where this intelligence system is being built and what's driving that? And from what we see, I think what research shows today that the idea that you create just a big model and connect it to a database of data, and it just figures everything out. is utterly unviable, right?

It just creates a completely law less AI, which has no understanding of enterprise processes, compliance, determines and repeatability. So you basically have to build an HR and finance system for AI, right? So that's the intelligence layer, right? It's not by modal, smart model and dump data. It's actually about an AI-enabled ERP and that's the intelligence later Daniel spoke about that we are building.

We are opening that up via APIs at the same point in time because we believe in the openness of the ecosystem and the openness of the engagement layer, right, and we are great partners, with all of the AI companies out there. But at the same point in time, the reason why they're working with us and as Aneel put it, why the use Workday is because you need to have an HR AI and an AI finance system. And that's the intelligence that we are building, where we create value and frankly, where we capture value.

And ladies and gentlemen, this concludes our question-and-answer session as well as today's call. We thank you for your participation, and you may now disconnect.

Okay. Welcome to our next session. Really happy to -- I need to get my questions all right. Here we go. Really happy to have Gerrit from Workday. We were joking earlier that we do it in German, but we won't.

Fellow German.

Yes. The 2 Germans talking about the World Cup next year. Just maybe introduce yourself briefly, like you have an interesting background as well, and like introduce yourself and then talk about what excited you about joining Workday.

Yes, happy to. So I'm Gerrit, President of Product and Technology at Workday, other than just being a fellow German. I worked 11 years at SAP, headed up SAP's data-based business, BI business, planning business, HANA, maybe some of you know that piece of technology. After that, worked at Google, here right around the corner. And then from Google joined Workday 9 months ago, 9 months in the making. And what excited me about Workday is that, look, the bottom line is I have seen enterprise application and how they are creating value, and I have seen how planet-scale AI systems are engineered. And for me, it's obvious what's infrastructure and what's value generation. And I think we're now at the point where the pace of being focused on infra model turns over to AI business applications. And I do think it's a time where Titans fall and Titans get created, and I think Workday is in an awesome position to be one of the new Titans. So who wouldn't want to be a part of that?

Yes. No, exactly. Yes. No, that sounds good. And the -- let's start with the core business. Like talk a little bit about the opportunities you're seeing there? And kind of what do you think in terms of innovation to kind of capture some of that opportunity?

Yes. Sounds good. Raimo, I think that's one of the big things that I personally think people are confused about because we say, "Well, Workday is so penetrated, so present and it's such a narrow space in HR and finance." But if you do just simple math, right, the TAM that we're operating in is roughly $200 billion, just do -- you're a smart analyst, do the back of the envelope on Workday's top line, right? We had 5%, 4% market penetration of that, right? So there is an incredible amount of space for us to grow, and we started to aggressively pursue that.

And when you approach a market, you can roughly segment it in 3 major ways. One is expanding the portfolio. One of the big initiatives that we are driving is going into frontline work. So roughly $3 billion work on the planet are falling in the frontline work category. Workday has a very narrow offering in that space. Even Workday customers may use other solutions in that. So for us, very important that we capture that space around our customers and beyond that.

We have other areas like in finance, where we are massively expanding our footprint. We add new services for revenue management, for subscription services, a new expenses module, profitability and cost management. So we are really broadening the suite. That's category number one. And that's going to allow us to just realize much more of the potential that we have right around our core suite.

Secondly, it's all about markets and segments. Workday, as you all know, is a concentrated business when you think about it geographically. In Europe, where you and I come from, right, there is so much potential for us to grow. So we have a focused plan for Europe with country localization, with really bringing our offering fully market ready to the big economies in Europe. We just launched also new data centers in Europe with our EU Sovereign Cloud. We have new local partnerships with local implementation partners.

And even beyond that, geographically speaking, we just launched India with a data center and a sales presence there. So in the second bucket, it's really being focused on tapping into more markets and specifically being super successful in Europe.

And then thirdly, you can also think about the market segments, right? And if you think about roughly the SaaS space, of course, there is the large enterprise space, there is the medium enterprise space, and there is the small enterprise space. Workday is super successful in large enterprises. But then when you now look into the lower down segment, specifically in mid-market, we actually -- we have the same win rates in mid-market that we have in LE, roughly speaking. And that's because if you're a company which is 1,000 employees to 3,000 employees, you are more like a company, which has 5,000 to 10,000 employees than you are like a company with 50 to 500 employees.

So Workday has an incredibly well-fitting product in that space. We just had to simplify our contracting, simplify our services model, simplify basically how we take this to market in a packaged way. We just launched it as Workday GO and now the new Workday accelerated package that will unlock for us much more of the opportunities in medium enterprise space. So expansion of the suite, geographic expansion and laser focus on mid-market are 3 immediate and very actionable growth vectors for us.

Yes. And then if you look at the product or the core products, is there anything on the technology platform that you think you want to change? Or like, I mean, Workday started obviously later than a lot of the bigger ups guys, they are more modern. But if you look at the platform, is there anything you're kind of thinking?

Yes. Look, that's -- the reality is that if you write a line of code today, it's legacy tomorrow. So when we say the technology stack, to a large degree, this is actually the global scale of Workday, right? So when we think about Workday's ability as a cloud-only vendor, you say some of the competitors are newer. Actually, many of them are older, right?

No, no. I meant to say that. Yes, yes.

I, actually, see all of them are like 50-plus years old. And actually, we are not -- I'm not worried as much about it. I'm a technologist. But when we think about technology going forward, we really have to think about it in terms of AI. And when you think about AI value generation, it's much lesser about how the application is written. It's much more about how do you leverage the data set that you have, how much do you leverage the process model that you have, how much are you able to contextualize AI in a certain process setting. And so there are many things which are basically happening outside of how the core application stack is written itself.

But also truth to be told, even before me joining, Workday already was in a major journey to renovate it's core application stack with Kubernetes-based open standard programming languages, all augmented around the core. And one of the people I was fortunate enough to bring with me from Google, Gabe Monroy, he now leads our technology platform. He ran cloud run times at Google. So he's very proficient in that space. And we will still be always investing in our core and maturing it. But then to the core of your question, when we think about innovation at the current technology cycle, that question actually is not really the determinant factor anymore.

Yes. Okay. Makes sense. And then I don't know how much Justin briefed you, but like on our side...

Very little.

Yes, yes. On the investor side, there's like this big debate going on about what's going to happen to these big system of records in this new AI world? What's the future of SaaS? How do you -- like you're more a technologist, like how do you think about that debt debate? And what's the situation you see for Workday there as well?

Yes. Specifically -- I mean, we can talk in general and specifically. So I think what we have to be clear on when you say system of record, system of record is, of course, not an unattractive position, right? So the path is from system of record to system of action. That is the interesting piece, right? So how can I actually drive processes, value creation, user engagement with the data set that I have, right? So that's clearly the path.

What we do at Workday, right? We structured our AI strategy in 3 key ways. The first one is AI is first and foremost going to completely transform the user experience. So AI is going to be the new UI. And I'm sure you have seen we acquired a company called Sana. So we are really quickly moving that space from a completely AI-driven user experience for Workday and beyond.

The second piece of that is that a complete automation of all back-end processes. So when you think about HR and finance department of one almost, right, where you have complete AI-driven automation that is being surfaced through a conversational experience but drives massive efficiency gain and productivity gains at a platform layer. Workday is in an incredible position there because Workday already has 80 GA features out with customers, organically developed. We have roughly 1.2 billion AI actions year-to-date in the core platform already taking place. And we're using all of that to now build purpose-built AI agents to drive this automation. Right now, we have roughly 10 organically, meaning non-acquired agents in the hands of our customers. We have 5x of that already in the road map, launching very quickly. And if you combine that with the acquisitions that we have made selectively in the recruiting space, in the contract management space, we are really having an incredible portfolio together already for the identification of the core system.

And the third pillar of our AI strategy is really centered around that idea of an open platform. Every large platform is an integration platform by definition. In Workday, we have hundreds of billions of API calls towards our platform today. So it's super relevant because it is such a key piece, people and money inside of an organizational context.

So on the third pillar of our strategy, we are now unlocking our platform by making our data objects accessible through standard APIs called Workday Data Cloud. We have a new agent builder where people can build very quickly in a nontechnical way, agentic automation. We acquired Pipedream, which basically supports this with 3,000 connectors into the enterprise fabric. And that allows the CIOs if you think about the CHRO, the CFO, the CIO as the third key persona to innovate on top of the Workday platform. And we feel incredibly good about all 3 because ultimately, it goes back to where we started that the real differentiation in AI comes from data and process context. And because Workday being born in the cloud, we have one data model, we have one process model shared across all tenants, that's a huge advantage.

I wanted to stay on that data comment you made. We just had Salesforce on earlier, and we had Ali from Databricks yesterday.

You had them all. Okay.

Yes, we had them all. What was interesting is like the importance of data came up again and again. And especially like you guys sit on a treasure trove of information that kind of keeps growing. And you said you wanted to be open as well -- we wanted to be open, but kind of maybe talk about that importance of data, what you do with data? How you enable your customers to work better with the data as a kind of a way to...

Yes. I think it also builds back to your question around the risk of being disrupted from a small startup in that space. And I think it really comes from, a, I think when we say data, I think that's incomplete. Now if you are coming from a data company, it's what you have to say is everything is data. And guess what, that was the story before AI as well, right? So everything is data. So in the AI space, it's not just data, it's data, it's context and it's process, right? It's always those 3 things coming together for AI value generation.

And when we think about what we are doing that sets us uniquely apart in an enterprise context is when we say the Workday data advantage, if you will, it really comes from, a, of course, having an incredibly broad and an incredibly deep data set of all functions in HR and finance, which gives us a lot of information that we can use to build and contextualize AI systems.

But the second point is key, right, that much of what's happening in a business process is nothing that you can train a model on, right? It's not like the database is going away. The databases are just getting consumed in the models itself. And the reason for it being is that, one, it's highly churning data, right, the transactions, if you will. They are not just flowing directly into model training because guess what, model training takes very long. It's very expensive.

Secondly, enterprise data, who belongs -- who is the owner of the enterprise? It is the customer, right? You cannot just like in the public domain, upstream it into a big model. It doesn't work that way. Third issue is it's highly proprietary in the semantics, but there is no common definition of what it means, right? It's a customer specific definition of what it means.

And then the third element to that being is that now you need to understand how you take out of your data, the right patterns with the right process context at the right point in time. And this is why you need data, plus context, plus process. And that effectively creates an incredibly high barrier to entry for AI. For AI, it's fairly easy to enter a space where you just draft off the public domain. Coding is a terrific example. Coding is great because the models are incredibly proficient in codes because they are trained on a public web. If you go to HR and finance, none of this applies, right? Because they're not trained on the world's finance data. It doesn't exist in a form, right? And secondly, when you want to run a process like a financial close or supply onboarding, what data means in that moment and what data you need is very different, actually.

And I want to also add one last point to that because I do think there's also one big misconception about data in the enterprise space. There is one #1 criteria which defines the acceptance of AI in enterprise and that's accuracy.

What did you say?

Accuracy.

Accuracy. Yes.

Again, right, we have to see where AI is successful and where it's not. AI is successful in coding because you generate code, the developer understands the code, sees it and corrects it. He understands the output modality and is proficient in it. So if it's 80% or 90%, correct, it's a nonissue. It's great actually, right? Because you have this 80%, 90%. Now you're an analyst. If I were to show you a dashboard, and I would tell you, it's 80% correct. I'm not telling you what's not correct, right? But it's 80% correct. Could you use that?

I'll call Sheldon. Sorry, no. Yes.

Of course, not. It's absolutely unusable, right? Or if you would run a payroll run. And you would say, "Well, the payroll run is 80% correct." I'm not going to tell you which employees I didn't pay correctly. You have to figure it out. But it's 80% correct. It's clearly unviable, right? It doesn't work that way.

And if you now put all of those 4 things together, right, you actually do understand that as a start-up without a data, without the business process platform, without the business process context and without having the ability to guarantee the accuracy of that at 100%, you're practically not playing. And I think that that's why you actually see us innovating. And frankly, not much happening in the space around it. Most people who say, I for finance say better dashboards. And this is not the AI transformation that I'm talking about.

Yes, yes, yes. Yes, it's funny because like in my first life, I was a PwC guy doing SAP systems. Every time someone says like, "Oh, vibe coding can do this." I was like, "You haven't seen processes."

Exactly, [indiscernible] business process. You got to be 100% correct.

Moving on a little bit here, like if you do all this innovation in Workday, you're getting more AI, you get more agents. How do you think about monetization?

Yes, of course, it's added value that we want to capture. And we really want to strike the right balance between very easy to adopt, very transparent, very predictable to budget and of course, giving us a real opportunity to partake in the value creation for AI. And the reality is that when we think about this from a business model that seat-based models have limitations, obviously, right, because a part of the value promise of AI is that actually seat-based monetization has changed from a large spend on people to a software spend.

So what we launched is a concept called Flex Credits. Flex Credits basically is our way for monetizing usage, AI assist in our platform. And so a customer basically gets the opportunity to use AI credits, Flex Credit as part of their Workday system. And they are basically the currency to pay for all of Workday's AI feature. We have AI features that basically then consume Flex Credits as customers are using the AI features and customers have the opportunity to buy more Flex Credits as they expand their usage.

So very simply put, one of the most common cases in AI in HR is employee service delivery. By the way, they're seeing fantastic results with that, right? So customers really reducing their contact rates for their service centers through self-service AI for employee service delivery. And now when the agent is engaging with an employee, right, helping them managing a benefit or another change in their work life, it basically then consumes these Flex Credits as monetized usage. And the way we have structured is, again, right, making it super simple, super transparent, super easy to budget. And the key for us really is to make it universal across any AI.

So what we want to enable our customers with is that once they are using Flex Credits, they can use all of our AI models, all of our AI agents without differentiation. It's simple that way. And secondly, on our side, right, it allows us to constantly introduce new AI features and new AI agents into that model that customers then can consume. So it's really striking a nice balance of customer value and value on our side.

Yes. Okay. And then the -- how do you think about that equation then like that comes up on our side, a lot is like P times Q. So if I think about you guys, historically, you priced on a number of people on the platform, AI might reduce that number. But then, obviously, you're adding a lot more value, and you talked about the Flex Credits there. How do you see about that dynamic? Because on our side, there's that concern, well, less employees, good luck to Workday. But like it does feel like actually with Flex Credit, agents, et cetera, you cannot have a very, very big offset there.

Yes, 100%. It's just basically a shift in where value accrues right? In AI, the value doesn't accrue as much anymore at the user level. It accrues actually at the outcome level that you're driving through AI. And obviously, you need to have a mechanism that allows you to capture the value where you're creating it. So we have both. We're going to have -- we still have our seat-based, FSE-based model for the entire employee base because for many of our products, this is still that the value accrues and it doesn't go away.

From recruiting to learning, there's still so much which the -- the value capture and the value accrual is happening on a per seat basis, the most natural way how customers want to buy, how they perceive value. But when you think about AI, right, it's really about complementing that with an outcome-based model that basically monetizes usage of AI. And since we have both, right, we can strike a very nice balance across the 2. And we are already doing this. Evisort, the company that we have acquired for Contract Intelligence, it very naturally accrues value on a per-contract basis. So that's how it's being sold, right?

And basically, what we do is now allowing our customers to use that on Flex Credits as a currency to pay for it. But from a user -- from a customer perspective, it's the most natural way, right? When we say, for instance, employee case management, right, the most natural way to say, okay, well, it's a number of cases that the system is handling or this is the most natural way for me how to size and describe value for it. So it's about balance having both models because both make sense. And I think the reality is, right, I don't think in these doomsday prediction that it's going to be one or the other, right? I think these are very reductionist views of the world. The reality is that usage-based pricing for us will continuously increase with the proliferation of AI. Seat-based model definitely is going to change in certain domain. But even if you're looking at our global market index in Workday, where we are tracking more people coming on the Workday platform or less, we are still seeing that growth at the same point in time, right?

So the narrative is out there, and I think it will apply to segments for sure. But I don't think it's going to be a title shift, black and white picture of tomorrow. I think, actually, it makes us -- puts us in a strong position that we can serve both modality under one commercial model or one contract with our customers.

Yes, yes. Okay. Perfect. Makes sense. You mentioned a few acquisitions -- a few of the acquisitions that happened for you guys. Talk a little bit, like you kind of walked -- part of that -- you were part of like some of the acquisitions, but talk a little bit about like what you acquired, how that fits in? And what's the path forward for you?

Yes, it's really for us about striking the ideal balance between organic and inorganic innovation, right? So both are things that you want to maximize fully, right? So as I said, right, we have 10 organic agents, 50 on the road map. So there's a lot of stuff happening. And like I said, for payroll, for case management, for planning, an incredible amount of number who our customers are getting tremendous value from. But we, of course, we also look in the market based on our rubric.

Our rubric is quite simple. First of all, does it help us to really make AI the new UI? Secondly, does it help us to drive agentic innovation to really automate big process change? Or thirdly, does it allow us to create an open ecosystem around the Workday platform? Now we acquired Sana because it is truly a leading AI experience that we see already. I'm using it every day, right?

I played with it. It's a cool stuff.

It's amazing. And if you look at their engagement numbers, it's amazing how much engagement they drive. Now connecting it to all of Workday, it truly puts us into a position where we have the leading AI experience on top of Workday. And secondly, put us in a position, right, where we have now a way how we can truly redefine the vast majority of someone's Workday by not only connecting Workday to it, but all of the other enterprise systems underneath it.

Secondly, when you think about the best agents, look, when you look at a company like Paradox, right, they have a fantastic recruiting AI system. It's a perfect complement. They are scheduling tens of millions of job interviews already annually. They are super significant. Now when we think about that capability and think about adding it to the recruiting AI that we have now, recruiting platform, it's just such a strong synergy, right? It would be almost foolish for us to say, "Let's just build this ourselves," right? And why would we, right? It's right there. And it's doing exactly what we needed to do, and it's deeply integrated in the Workday system already. So it's like a match made in heaven. And of course, we pursued that.

And on the platform side, what we acquired was 2 very small assets, Flowwise for agent building and Pipedream for connectivity. And here is the bottom line, right? As I said, right, we have hundreds of billions of API calls against our platform. Many of the workflows that CIO drives today around HR and finance are not yet things they could solve with Workday. For instance, when you hire someone, what do you want to do next? You want to send them a batch, you want to provision a notebook, get them hooked up on a mobile plan, send them to security training, typically what we would call employee onboarding and IT management. That is the process triggered out of Workday.

Our customers are waiting for us to give them an AI agent builder, so we can do the AI first and a connectivity suite so they can build that up across the entire enterprise landscape. And the Flowise and Pipedream, they get exactly that. It's unified with our Workday Extend platform and we have already thousands of apps on it, incredible momentum. And I think this is just going to unlock so many more scenarios for us on the AI platform consumption side. And we're going to remain acquisitive, right? I'm going to push hard on organic innovation as well as if we see something that really makes a marked difference in AI as the new UI, agents for work or an open platform ecosystem, those are things that are going to remain relevant for us.

Yes. And then when you -- it was funny when you joined Workday, I kind of initially felt, I think he got the timing off because...

Why would you say that?

Because I remember like Workday spent compared to the other SaaS guys so much more money on research and development. Like you're very, very technology driven, like research, development-driven organization way more than the others. And then a little bit of the pressure came so that he has to come down. So I was like, "Oh, he comes and his budget gets kind of reduced," maybe, I don't know. How do you think about that dynamic about...

All investors as concerned as you are about my well being. I love it.

Yes. No, no. But how do you think about that dynamic about like having the pressure on -- or like having to deliver like margin expansion, while at the same time, there's so much that needs to be done on your side.

Yes. I -- this is not Workday specific for me. And all of the companies I've worked and I always felt there's that idea that there is a trade-off between innovation and margin efficiency. And I think it all comes down to execution excellence. The reality is we have lots of operating leverage across everything, our entire operating expenses. And you just saw this here, right? We pursued aggressive M&A. We delivered on our margin goals, and we invested into organic innovation.

And I think the net of that is that it's the practice of being incredibly disciplined and executing very well on the top and the bottom line of your business because if you do, there is so much leverage that we have across the Workday business that at no point in time, I felt constraint in the ability to invest in innovation or I felt being tapped out on opportunities to free up more capital to redeploy towards innovation areas. So I'm feeling very confident about.

And it is funny. I think it wasn't in Toyota, like way back then, we actually blasted that myth that you can't innovate and be margin efficient at the same point in time. I truly subscribe that you can. And you can expect us continuing that way next path, right? We are aggressively expanding our investments into AI, into our core platform, as I said earlier, in our expansion and we're going to also increase our margin as we guided in the framework that we gave out by just realizing more of our operating leverage.

Yes Okay. Perfect. That's actually a very good closing statement, and we have 2 Germans on stage, so we need to finish on time.

I like it. Awesome.

Great. Thank you. Thanks for joining.

Thank you for having me. Thank you.

Thank you.

My pleasure.

Welcome to Workday's Third Quarter Fiscal Year 2026 Earnings Call. [Operator Instructions] I will now hand it over to Justin Furby, Vice President of Investor Relations. Please go ahead.

Thank you operator. Welcome to Workday's Third Quarter Fiscal 2026 Earnings Conference Call. On the call, we have Carl Eschenbach, our CEO; Zane Rowe, our CFO; and Gerrit Kazmaier, our President, Product and Technology. Following prepared remarks, we will take questions. Our press release was issued after close of market and is posted on our website where this call is being simultaneously webcast.

Before we get started, we want to emphasize that some of our statements on this call particularly our guidance, are based on the information we have as of today and include forward-looking statements regarding our financial results, applications, customer demand, operations and other matters. These statements are subject to risks uncertainties and assumptions that could cause actual results to differ materially.

Please refer to the press release and the risk factors and documents we file with the Securities and Exchange Commission, including our fiscal 2025 annual report on Form 10-K for additional information on risks, uncertainties and assumptions that may cause actual results to differ materially from those set forth in such statements. In addition, during today's call, we will discuss non-GAAP financial measures, which we believe are useful as supplemental measures of Workday's performance. These non-GAAP measures should be considered in addition to and not as a substitute for or in isolation from GAAP results.

You can find additional disclosures regarding these non-GAAP measures, including reconciliations with comparable GAAP results, in our earnings press release, in our investor presentation and on the Investor Relations page of our website. The webcast replay of this call will be available for the next 90 days on our company website under the Investor Relations link.

Additionally, the prepared remarks of this call and our quarterly investor presentation will be posted on our Investor Relations website following this call. Our fourth quarter fiscal 2026 quiet period begins on January 15, 2026. Unless otherwise stated, all financial comparisons in this call will be to our results for the comparable period of our fiscal 2025.

With that, I will hand the call over to Carl.

Thank you, Justin, and thank you all for joining us today. I'm pleased to report that Workday delivered solid Q3 results, with 15% subscription revenue growth and 28.5% non-GAAP operating margin. Our teams executed well, and our value proposition is clearly resonating with organizations around the world. I've been on the road a lot lately, meeting with our customers and prospects, and they're all saying the same thing. They see the potential of AI but they're stuck with disconnected systems, bad data and closed platforms. That's where Workday gives them the ultimate advantage by unifying HR and finance on one intelligent platform, we deliver business-ready AI that helps organizations adapt quickly make better decisions and deliver outcomes that truly matter.

Now let's turn to our customer highlights for the quarter. In Q3, we continued to grow across industries, segments and geographies. In HCM, we added new customers, including Sunnybrook Health Sciences Center Fuji Electric and The Magnum Ice Cream company. For financials also performed well, driving strong full suite adoption. In fact, half of all net new global deals in Q3 included both HR and finance, with key wins such as Ardent Health, Kelly Services and specialized. We also expanded with customers such as CommonSpirit Health, Levi Strauss and Novartis. And consistent with recent quarters, our customers' head count levels continue to grow modestly. And our momentum isn't just from large enterprises. Workday GO is helping us drive strong new customer growth and continued ACV momentum in the medium enterprise. Just last week, we announced a major expansion of Workday GO, including global payroll, an expanded partner network and a new AI powered deployment agent that can cut implementation time by up to 25%.

Customers of all sizes and industries tell us that an investment in Workday is an investment in their AI strategy. More than 75% of our core customers are using Workday Illuminate AI, driving well over 1 billion AI actions on the Workday platform this year alone and adoption keeps growing. More than 3/4 of net new deals and 35% of customer expansions included one or more AI products. Among the standouts, Evisort delivered another record quarter and Extend Pro grew net new ACV by more than 50% year-over-year. Altogether, our AI products added more than 1.5 points of ARR growth this quarter. That doesn't include Paradox, which we closed in Q3 and is already off to a strong start. And with the rollout of Flex Credits early next year, we're making it even easier for our customers to adopt our AI and platform innovation. Our customer footprint spans every major industry.

Tech and media and financial services, 2 of our $1 billion industries were standout performers in the quarter. And in Q3, Healthcare became our sixth industry to exceed $1 billion in ARR with strategic wins like Ardent Health, Ascendian and Northeast Georgia Medical Center. One of my favorites this quarter was a major win back at a large U.S. health insurer. They were a long-time Workday customer that moved to a competitor several years ago and quickly regretted it. Now they're back with Workday in choosing our full suite with a 10-year commitment. Our public sector momentum was also strong in Q3. And despite the weeks long government shutdown, engagement across federal agencies remained high. The Department of Energy's successful go live in Q3 is a great example. There the first cabinet level agency to bring their core HR systems into our FedRAMP authorized cloud. We're also nearing completion of the first phase of our work with the DIA. This opens up an important long-term opportunity, both with the agency and across the intelligence community and Department of War.

In SLED, we welcome new customers, including the county of San Luis Obispo, the City of Concord and Cleveland State University, and we expanded with Cornell University, which added both core financials and student. While we had a number of successes across our Fed, SLED and health care teams, we also saw some isolated impacts within institutions that rely heavily on federal grants, primarily in higher ed. However, when they are ready to move forward, our win rates are very strong, and we're excited by the long-term opportunity ahead. Across all of these industries, we're delivering innovation that's changing how work gets done, and the market is taking notice. Gartner just named Workday, a leader in 3 Magic Quadrants, including cloud ERP for service-centric enterprises, cloud HCM suite for 1,000-plus employee enterprises and the first-ever MQ for cloud ERP finance, giving us the highest placement for both ability to execute and completeness of vision.

If you joined us at Workday Rising, you saw how our organic innovation is only accelerating. We introduced new illuminate agents that tackle some of the toughest challenges at work from performance reviews and workforce planning to financial close. These purpose bill agents are powered by our unmatched HR and financial data and context which is what makes them highly accurate, actionable and trusted. And now we have more than 150 customers, including Target, Accenture and Netflix using our agents and agent system of record in early access. At the same time, we're opening up our platform so customers and partners can create their own AI-powered apps and agents with Workday build.

And with Workday Data Cloud, along with our partners, including data bricks, Salesforce, Snowflake and now Google Cloud, customers can unlock even more insight and value from their Workday data. We're also accelerating our innovation through strategic acquisitions. We just closed acquisition of Sana, an AI-native platform with an incredible team. They're going to help us completely reimagine our user experience for the age of AI. Our vision is very simple and straightforward, make Workday the new front door to work by bringing together enterprise knowledge, AI agents and all the HR and finance processes our customers run every day. This will make it easier than ever to find answers, take action and learn right in Workday. Customer feedback on this vision has been absolutely incredible and Sana Learn brings hyper-personalized skill development and AI-generated content creation to Workday Learning. I can't wait for our customers to get their hands on it.

We're not stopping there. Last week, we announced the intent to acquire Pipedream a low-code integration platform for AI agents with more than 3,000 prebuilt connectors to the world's most widely used business applications like Sana, Jira and Slack. When you combine that reach with Workday's trusted data, deep business context and the capabilities from Sana and Flowise, our agents move from surfacing insights to truly getting work done. So hopefully, you're seeing a theme here. While other vendors confuse the market with thousands of overlapping general purpose agents, we're focused on what we do best, and that is building powerful agents for HR and finance that deliver real ROI and measurable business value.

Turning to international. We delivered solid performance across EMEA, APAC and Japan in Q3. We just wrapped up our largest EMEA rising yet. There we announced the new Workday EU sovereign cloud which will let customers run our AI-powered HR and finance solutions entirely within the EU, keeping their data local, secure and fully controlled. Also in Q3, we established a new AI center of excellence in Dublin, which is one of our major R&D hubs, and we announced a new office in Dubai. A few of the great wins we had across EMEA in Q3 included Bayer, ING Bank and Tandem Bank. APAC also had a strong quarter with wins at Genesis Energy DBS Bank and MGM Grand Paradise. And we continue to build on our success in Japan with new and expanded relationships with Pioneer Corporation, Hoshino Resorts and Eisai. Our partners continue to play a critical role in our success. Once again, in Q3, and more than 20% of our net new ACV was sourced from partners, a testament to the strength of our ecosystem.

In Q3, we brought on new Workday Wellness partners, including Chime, Spring Health and Strata to expand the value we deliver to our joint customers. We also expanded our partnership with Microsoft to help joint customers securely manage their people and agents across both of our platforms. We're living in a new era of work powered by AI and Bill on trust, and Workday is made for this moment. The momentum in our business and the energy I'm seeing across our customer community gives me a ton of confidence in what's ahead. A huge thank you to our global work meats, our customers and our partners for helping us deliver another solid quarter. As we head into Q4, we're focused on finishing strong and setting ourselves up for an even more impactful FY '27.

With that, I'll turn it over to Zane.

Thanks, Carl, and thank you to everyone for joining today's call. Our Q3 results were driven by continued progress across several key growth initiatives as we accelerate innovation throughout the platform and bring exciting AI solutions to market.

Turning to results. Subscription revenue in the third quarter was $2.244 billion, up 15%. Professional services revenue was $188 million, resulting in total revenue of $2.432 billion, growth of 13%. U.S. revenue in Q3 totaled $1.825 billion, up 12%. International revenue totaled $607 million, up 13%. 12-month subscription revenue backlog or CRPO, was $8.21 billion at the end of Q3, increasing 17.6%. We closed the Paradox acquisition in the quarter, which added over a one point of CRPO growth and was not included in our backlog guidance. Excluding Paradox, CRPO came in slightly above the high end of our outlook.

Total subscription revenue backlog at the end of the quarter was $25.96 billion, up 17%, and gross revenue retention rates remained healthy at 97%. Non-GAAP operating income for the third quarter was $692 million, representing a non-GAAP operating margin of 28.5%. We remain focused on making targeted investments to support long-term growth. This includes increasing our AI talent, both organically and inorganically, entering new markets such as the Middle East and India and vesting in the medium enterprise. While we make these investments, we're also continue to drive efficiencies as we scale the business globally.

Q3 operating cash flow was $588 million, growth of 45%, in line with our expectations. As we discussed at our recent financial Analyst Day, we intend to accelerate the pace of our buyback. We made good progress in Q3, repurchasing $803 million of our shares during the quarter and $1.4 billion year-to-date. We plan to repurchase an additional $3.6 billion through the end of FY '27, leading to $5 billion in total repurchases. As of October 31, we had $4.4 billion remaining under our current authorization. We ended the quarter with $6.8 billion in cash and marketable securities. Our head count as of October 31 stood at 20,588 workmates around the globe, including roughly 600 workmates from the Paradox acquisition.

Now turning to guidance. For Q4, we expect subscription revenue of $2.355 billion, growth of 15%, which includes revenue from the Sana acquisition and the expected delivery on the first phase of the DIA contract. We expect FY '26 subscription revenue of $8.828 billion, growth of 14%. Our Q4 subscription revenue guidance is consistent with our view from last quarter, excluding the expected contribution from Sana. While we did see some impact in Fed and SLED tied to fiscal funding, this was offset by strong execution across the portfolio, including the Paradox acquisition. We expect CRPO to increase between 15% and 16% in Q4. This includes approximately 0.25 point of expected growth from the Sana acquisition or about $20 million. And over 1 point of impact from tenants, which we begin to lap in Q1.

For Q4, we expect professional services revenue of $168 million. And for the full year, we expect it to be $715 million. We are executing well against our efficiency goals and expect a non-GAAP operating margin of at least 28.5% for Q4 and approximately 29% for the full year. We're optimistic about the AI-driven growth investments we are making and have ample capacity to continue to invest while we drive further efficiencies, consistent with the framework from our Financial Analyst Day. We expect GAAP operating margins to be approximately 19 and 21 points lower than our Q4 and full year FY '26 non-GAAP operating margins, respectively. The FY '26 non-GAAP tax rate is expected to be 19%. We are increasing our FY '26 operating cash flow outlook to $2.90 billion, and we continue to expect capital expenditures of approximately $200 million, resulting in free cash flow of $2.70 billion, growth of 23%.

Looking beyond this year, as we shared in our recent financial Analyst Day, we are targeting a subscription revenue CAGR of 12% to 15% through FY '28, along with continued margin expansion on both a GAAP and non-GAAP basis. For FY '27, specifically, we continue to expect subscription revenue growth of approximately 13%, also consistent with the view we shared in September at our Analyst Day. We are confident in this growth rate based on the momentum we see across the business as reflected in our Q3 performance as well as our Q4 CRPO guidance. We are optimistic about our growth initiatives and our recent acquisitions and look forward to updating you with formal guidance for FY '27 next quarter. We currently expect our Q1 FY '27 subscription revenue growth to be approximately 14% year-over-year and flat sequentially, reflecting typical seasonality from Q4 as well as the expected revenue from DIA in Q4, which doesn't extend into Q1.

We believe that the completion of this first phase sets us up for a larger opportunity with the DIA and the broader defense and intelligence communities. We remain on track and confident in our ability to achieve the financial framework we laid out at our Analyst Day back in September, including subscription revenue growth, non-GAAP margins and stock-based compensation. In closing, I'd like to thank our workmates, customers and partners around the globe that help deliver this quarter's results. We enter Q4 well positioned to close the year with strength and remain focused on our long-term opportunity of driving durable growth while expanding operating margins.

With that, I'll turn it back over to the operator to begin Q&A.

[Operator Instructions] Our first question is from Mark Murphy with JPMorgan.

And I'll add my congrats on a very nice performance. Carl, we're hearing some feedback that the venture-backed VIBE coating startups have started seeing a slowdown or at least as some of them have or elevated churn. And it's happening because companies are finding it's pretty difficult to operationalize them and put them into production use I'm wondering if you're seeing any signs of some of that novelty wearing off for this third-party VIBE coating products. And if so, do you see any accelerated adoption of Workday Extend where presumably, they'd have all the security and all the other infrastructure already in place?

Yes. Mark, thanks for the question. And before I answer, I just wanted to say the following. Q3, Mark, was another solid quarter for Workday reflecting in the strength. And as I always like to say, the diversity and durability of our business. Our customers are seeing clear ROI from Workday, and they're engaging more than ever, and we had more than 1 billion AI actions year-to-date and it's only growing faster and faster. We feel really good about the momentum of the business as we head into Q4 and into FY '27. And I'm truly grateful for all the work, both our partners and our workmates have done to get us to this point in the year. It's been a really good year for us so far.

And Mark, I really appreciate your question. It's similar to what Kash asked last quarter when you talked about all of this potential disruption coming from these AI start-ups to more mature and larger SaaS companies like Workday. And at the time, I said I thought it was a completely overblown narrative, and I thought it was flat out wrong. And quite frankly, fast forwarding 90 days, I think that's playing out exactly like we thought it would. When I spend time with CXOs around the world that both customers and prospects they talk about 3 things that's hindering or slowing down enterprise adoption of AI. It is data quality, it's data integrity and its security. And by the way, none of these are an issue for Workday. As you know, we have one of the largest and cleanest and most highly curated data sets for HR and finance in the industry. No questions asked.

And we have the security compliance and controls in place because today, we onboard a large portion of the world's workforce, and we can apply those same process and procedures to your workforce in the future, both human and digital. And when we spend time with our customers, while maybe they're enamored with these point solutions, they're ultimately coming back to the vendors they trust, who have been in their infrastructure for a long time, had that data set and drives real business outcomes. The narrative we've been hearing in the last couple of quarters is changing, and it's coming back to those who are highly penetrated in the enterprise already providing value and are deeply trusted by our customers. So I agree with what you're seeing, we're seeing it. We're hearing it and it's reflected in customers continuing to be on Workday for their future.

Our next question is from Kirk Materne with Evercore ISI.

Congrats on the solid quarter. Carl, the other narrative that often comes up these days is clients see a big customer laying off people. And I know you guys commented that your customers are growing head count slowly right now. What are the mechanisms that you guys have if a customer were to have to laugh people to be able to keep growing ACV with them? Cross-sell, upsell, are there discounts that go away? I just -- can you just explain that a little bit? Because I think people believe there's sort of a linear relationship between a number on a per seat basis. And I realize it's probably a little bit more complicated that especially at the high end of your business.

Thanks, Kirk. I appreciate the question. And yes, in my prepared remarks, I once again want to articulate and share that on a net basis, the head count of our customer base is up year-over-year. So while there are some layoffs out there, we're still growing head count across our customer base. And what we're doing, use edit. We are selling back into our base, and we're focused not on just seats, but actually revenue per seat. And what we have now more than ever is we have a whole bunch of new solutions, both organically innovative solutions and solutions that we got through acquisition that we're selling back into our customer base, whether it's ever sort it's hired score, now it's Sun and now it's Paradox, now it's Flowwise. We have so much more to sell back into our customer base and that drives strength for us and offset any potential impact we might see from head count reductions in our customers. .

Also, our customers do true-ups with us both annually on their headcount. And we do have floors and minimums that the customer can bring their head count down and that gives us some protection. But overall, we're still seeing growth in head count year-over-year. And we're selling just a lot more back into our customer base because they're betting on our platform, and they're using us as a consolidation platform across all of their point solutions to drive a better total cost of ownership.

Kirk, I'd just add, if you look at the aggregate, it is a net positive, but it's not a significant amount of our growth. So there are lots of elements, as Carl alluded to, that go into that growth number, and this is just one of them.

Our next question is from Keith is with Morgan Stanley.

Congratulations on the solid quarter. I wanted to ask about some of the early success you guys are seeing with your AI solutions. Carl, I think on the call, you said 1.5 points of growth in ARR, all rig coming from the AI solutions. Can you give us any rules of thumb that you're starting to see that could help us maybe model this out a little bit in terms of what type of uplift do you see on a typical deal or for a typical customer when they're buying the AI solutions? Or how broad is this? Like what percentage of your customer base has already bought into the solutions and how far do we have to go? Just something to help us extrapolate that early success into what this might look like in a year from now we are 2 years from now?

Yes. Thanks for the question, Keith. And we gave some of the statistics at FAD just 90 days ago. That's why we called out again this quarter. our AI solutions are adding 1.5 points of growth to our ARR, and we're also trying to give you some color specifically on the strength of our AI solution. So for example, 75% of our new sales included in AI solution, 35% of our sales back to our customer base includes AI. So we're seeing really good traction, and we're seeing really good early indications of demand from some of our acquired companies like Sana and Paradox. So overall, our AI momentum is as strong if not stronger than ever, and it's being reflected in how our customers are buying our product, both at time of new sales as well as our ability to sell back into our customer base. So I couldn't be more excited about where we're at. Things like Evisort had a record quarter. We're seeing an acceleration in growth in Evisort. In Extend Pro, we call that out. It once again grew 50% year-over-year. And then when we sell back into our customers, for example, when we sell something like a higher score recruiting agent, it's a significant uptick over what we would sell our standard recruiting SKU for.

Got it. Any sense on how much of an uplift it is versus the standard?

Yes. On, for example, on hired score, for every dollar of recruiting we sell, we sell about $2.50 of hired score on top of it.

Our next question is from Michael Turrin with Wells Fargo.

I appreciate you asking -- I appreciate you taking the question and I got on the results as well. I guess just a 2-parter for me. I guess just -- I wanted to zoom in on some of the early feedback around Paradox and Sana. Just what you're hearing from customers coming out of rising? And if that can help the Workday business model continued to evolve towards just some of the questions around AI and agent capabilities. that you're offering alongside the Flex Credits program. And then, Zane, maybe just coming out of rising an update on how you're thinking about the trade-offs between growth and margin given some of the recent additions in the product portfolio and some of that feedback there as well.

Yes. So maybe I'll start, and then I'll kick it over to both Gerrit and Zane specifically to follow up on the questions. So first, as you know, we've closed the Paradox acquisition in October. And within 2 weeks, we were already off and selling it and had a small impact in the quarter, a few million dollars over a 2-week period just by our sales force going out and selling that into the market. I will tell you, coming out of rising EMEA. The demand and excitement for Paradox and being a Workday product and selling on our paper was very, very strong.

On Sana, similar feedback from our customers. They see this as an extremely powerful AI solution across multiple dimensions, starting with learning. We can now sell their AI learning platform back into and on top of our 4,000 customers that have Workday learning today. And then obviously, we're going to refresh our UI/UX leveraging the Sana platform going forward. So the early indications, specifically on these 2 recent acquired companies is as strong as anything we've seen when we acquire a company? And maybe, Gerrit, you can talk specifically about Sana because that one is off the charts right now from a demand and from an excitement from our customers.

Yes. And as Carl has said, we are seeing tremendous interest around the 3 main vectors of Sana, one, as Carl has said, the leading AI learning platform. So very natural for us to bring this to our customers, of which we have a very scaled base of Workday Learning customers, which are using an and are excited about Sana as a learning AI experience platform on top of that, very natural, very immediate interest. And secondly, what Carl has mentioned, Sana is also now being developed into the leading UI experience for Workday. So you can think about a complete conversational experience around the Workday platform. Workday being the innovation leader and our customers are tremendously excited about the massive simplification that brings to them. And if you imagine every employee having access to HR and finance AI at scale. What that means in cost reduction.

On the other side, you can see what drives that interest. And thirdly, Sana goes much more beyond that. And I would recommend you look at the big picture with also Pipedream, adding 3,000 connectors to the Sana platform, which now allows our customers to take Sana knowledge management actions and Workday and the actions that Pipedream adds to really drive enterprise-wide AI transformation with that model. And we see very strong customer interest across all of those 3 vectors.

Michael, this is Zane. I'll just add. As you can hear between Carl and Gerrit, we're thrilled with the early success that we're seeing from both Paradox and Sana. So as it relates to our financial framework, I'd say no change at all. We continue to invest in AI, both organically and inorganically and are pleased with the investments we're making there and at the same time, recognizing the efficiencies and scale that we're driving across the business. So we're still driving that within the framework and very pleased with the progress we're making there.

Our next question is from Brent Thill with Jefferies.

Just with Paradox. I know that SAP and other ERP install bases are using that. Is your vision that you can sell this anywhere that you're going to be agnostic to whatever platform is running in the back? How are you thinking about that from a go-to-market?

Yes. Thanks, Brent. We are super excited about the go-to-market capabilities we have around Paradox. Number one, we can sell it back into our customers, right, as an attachment to our already strong recruiting platform including something like hired score. Now we have Paradox, who we have the industry-leading AI recruiting platform out there today. At the same time, this is now a new product that is a land-only product for our sales force who can now go and sell Paradox not only on top of Workday or back into our installed base, but also into our competitors' environment. In fact, a significant portion of their existing customers aren't Workday today. And we're going to continue to leverage that go-to-market model, so it gives us another land product without someone having to decide completely on Workday, HR or finance, they can go just with Paradox. And I've seen that come up multiple times just in the first 60 days of us having this great asset.

Okay. Zane, real quick, just on CRPO, is there anything to consider in the guide that you're maybe highlighting is a headwind, tailwind? Any change to how you're thinking about that in terms of how we should think about modeling it?

No. I mean I think it's fairly clean, Brent. I mean obviously, we feel good about what we saw in the third quarter. I mentioned that Paradox was over 1 point of that. we feel very confident. I mean, obviously, as always, CRPO, the number of factors, both the net new business as well as renewal activity and just the volume that you get in any particular quarter. So we think we've got great strength heading into the fourth quarter. We've got terrific coverage on our expected subscription growth heading into next year, which I alluded to as you think about even between the fourth quarter and the first quarter, so no, we feel good about the CRPO growth as well as the coverage. So net-net, we feel good even on a sequential basis. I did call out how much of that was signed as well, which is a very small impact on revenue for the fourth quarter.

Our next question is from Karl Keirstead with UBS.

Maybe we can just continue that conversation. So if we try to take your 4Q CRPO 15 to 16 and normalize it by deducting maybe some of the onetime stuff. So just so I've got the thinking right, maybe 1 point year-over-year from the tenant contracts, maybe 1 point year-over-year from Paradox and 1/4 from Sana. So maybe 2.25 points from more unusual stuff to back out to get to more normalized. Is that roughly the right math?

Yes, Karl, I mean, there are lots of things you can sort of move around within that COP growth. I mean I think you've got it sort of generally in line. But again, there are other variables within the timing on renewal activity and things like that. One other call out I'll make if you're trying to understand sort of those components between the organic and the inorganic component in the fourth quarter is, I'd say, that both Sana and Paradox contribute roughly 1.5 points to our Q4 subscription revenue growth. So just to help you contextualize that. I mean, as I mentioned, in my prepared remarks, absent Sana, we believe our Q4 was consistent with our view just a quarter ago. So we feel great about the activity there. But that helps you understand sort of the components of Q4 and the CRC RPO growth heading into the quarter and into next year.

Okay. And maybe just in the spirit of a follow-up on 4Q, this time on subreps, it sounds like it's embedding a view of reaching those DIA go-live milestones. I'm assuming that given that there's just 2 months left in the fiscal year, you and Carl are feeling pretty good about that. Obviously, the shutdown, I suspect didn't help, but can you just maybe express confidence level in hitting those DIA go-lives?

Yes, it's a great call out. We're highly confident. Just to give you a sense of size on that one, it's a roughly $15 million in the fourth quarter. We feel great about the progress we've been making all year. We're tracking it very closely, and it's embedded in our forecast for the fourth quarter.

Yes. Yes, Karl, we're tracking really well towards the contract requirements that give us that $15 million in Q4, and we're already talking to them about an expansion of taking that platform to the next level, which opens up a whole bunch of different opportunities across a broader Department of Defense or Department of War. We're really excited about the momentum we're seeing with the federal government in this DIA project or the first phase of it is really openings up to a great opportunity going forward. And as I said, we're already negotiating a follow-on to take that platform to the next level with further security requirements they're asking us for.

Our next question is from Brad Sills with Bank of America.

It's clear from all the announcements and what we saw out of the conference was that you're really going for with AI, the Sana acquisition, Paradox, more recently, Pipedream, that partnership with Microsoft I mean, how should we read that? Should we think of this as kind of a year where you're building the foundation for AI and agents and that 1.5% points of growth coming from AI goes materially higher, perhaps in fiscal '21? Or is this more of a '27 event just given where you are with all the great innovation that you're kind of bringing together and the time it might take for that to kind of sink into the sales cycle and pipelines?

Yes. Thanks for the question, Brad. I'm going to turn it over to Gerrit to give some color, and then I'll talk about in the context of growth.

Yes. So I think, first of all, fast this is a continuation. As Carl has said, we have 1.4 billion AI actions already in production in the Workday platform today. So we have been doing this at Workday extremely successfully. And now we are just taking the next steps and leading AI technology to help our customers become truly driven enterprises. And specifically, the vectors of our innovation is with Paradox and in a bigger picture frontline, fully bringing AI automation to the entire hiring journey.

If you put that together with our recruiting agent, Paradox as a candidate engagement agent in connection with each other, it basically builds the AI-driven talent suite. What they're doing with Sana is we're acquiring leading knowledge management in a leading agent orchestrator to be the AI experience layer across Workday. So very important, when we think about adoption that our conviction is, AI is going to be the new UI and that all of the legacy vendors who are not having leading experiences are going to get relocated through that.

And thirdly, what you mentioned about Pipedream, right? Our ambition and our customers' requirements are actually taking us much broader than Workday is in finance and HR and really looking for enterprise-wide orchestration. We think about it as an enterprise AI fabric that we are creating through Pipedream with Sana, as the experience layer on top, built on top of Workday's business process platform.

Yes, Brad, the only color I'd add there is, clearly, we're going all in on AI, and it's for the following reason. We're uniquely positioned versus everyone else out there today. We have the data right? We have the context of the data, and we're built in the business workflow. And our customers are saying, time again, they no longer want to even evaluate point AI solutions. They want to do it on the back of a trusted platform. Therefore, we go when we get something like Paradox, we get Pipedream, we get Sana, last year, Evisort. Before that, we get HiredScore. And it's not just our customers who are saying they believe in our platform, it's partners. To your point, we're partnering with Microsoft. So as they start to build agents, they see the most secure, reliable and trusted way to onboard their agents is through Workday in our agent system of record because no one has more experience in onboarding employees Workday and now we're taking that to the digital worker as well.

Our next question is from Brad Zelnick with Deutsche Bank.

Great. Brad, following Brad. Congrats guys on a good quarter and thanks for taking the question. My question is about Workday GO, where we continue to hear really good things, particularly in MA and emerging enterprise. So it was interesting to see it soon to be more broadly available. Perhaps looking at AI from a different angle, is there anything different Workday needs to deliver from an AI product perspective for downmarket customer versus large enterprise?

Yes. Let me have Gerrit take that, and then I'll talk more about Workday GO and the big announcement we had a rising EMEA last week.

Yes. And specifically, the AI side, Brad, there are 2 things to consider, right? One is that also medium-sized companies want to benefit from the best AI. So of course, they're going to get the full power of birthdays, AI agents also delivered in Workday GO. That's the first part, very important. And secondly, we are specifically innovating around Workday GO with specific models. Think about the whole configuration administration, management of the system, set up complexity. We are working and announced a new deployment agent, which already is slashing deployment time and complexity down by a significant degree. It's a key investment theme for us. and just connecting it back to the broader partner network, specifically with Workday GO to new managed services like payroll, we are working on payroll AI that is equally being connected into our ASO with our partners that are providing these services to also drive payroll automation, payroll simplification, benefits management across the Workday go global partner network, and that's specifically being created. All from that angle to make the mid-market customer run at the scale of birthday, but with unmatched simplicity.

Yes. And Brad, we announced Workday GO, as I call it, 2.0 last week at EMEA rising. And I will tell you, to Gerrit's point, was unbelievable with 3 key components to it. We now offer global payroll, if a customer wants it, by the way, if they don't want to use a managed global payroll service from Workday, they can bring their own payroll. We have a partner network that's going to help us take Workday GO to the market around the world and resell it on our behalf, and then we have that AI deployment agent. Also included in Workday GO is a payroll agent to help people simplify how they're managing their payroll activity across the enterprise. Workday GO, I will tell you, is on fire. People are excited about it. and people are leaning into Workday down market as we aggressively go attack that market segment around the world.

Our next question is from Alex Zukin with Wolfe Research.

Maybe just a quick 2-parter. Carl, first for you, when you think about the commentary for next year, it's great to hear about the kind of reiterating the confidence and the growth rate of 13%. But since Analyst Day, is there anything that maybe you've seen that gives you even more confidence when you're talking with customers around things like budgets or their demand environments as we head into 2026 or propensity allocate more from the AI budget specifically to Workday that you can kind of comment on that gives you that confidence?

Yes. Thanks, Alex, for the question. As Zane said in his prepared remarks, we feel really good about our midterm guide that we laid out for next year. And we think the approximate 13% guide on subscription revenue next year is solid. That being said, we feel really good about all the acquired companies and the momentum we're seeing early on with them as well as the organic innovation that we have coming out of our super strong product and technology organization. We haven't even talked about it, but we're also entering new markets like we've done in the last couple of years in the federal market here in the U.S. taking that to the public sector around the world.

We announced entrance into the Middle East. And next week, we have a strong team led by Rob, our President of Customer Operations, going and launching our efforts in India. So we're really excited about all the growth vectors that we have going into next year as well as all the momentum we have around our AI solutions, both organic solutions and these inorganic solutions that we're getting through M&A.

Perfect. And then maybe just, Zane, as a follow-up, if we think about next year's guide that 13% and the acquisitions that you've made over the last couple of months. A, kind of how much do we think kind of comes from inorganic there? And then the pace of M&A, are we kind of through -- like should we think about this pace continuing at kind of current course and speed of these exciting technology tuck-ins? Or do you need to digest the ones that you've made here over the course of the next few weeks, months, quarters?

Sure. Yes. Look, I'll start with -- as we think about the acquired revenue, I mean, first off, as you know and as you can see here, when we acquire companies, they quickly become part of the broader portfolio. if you look at the acquired revenue, I'd say it probably contributes approximately one point into next year. But as you can tell, there's a lot more that we're doing around it and the whole portfolio benefits. So it's more significant synergy, if you want to think about it more broadly. But on the acquired revenue, I'd call it sort of roughly 1 point heading into next year.

And then we have a high bar on M&A. And as we've talked about all along. I mean, we've kept consistent and think about the technology, the culture the people and how they integrate either -- whether it's through adjacencies or tuck-ins for different reasons. So I'd say no change in how we think about that and no change in how we incorporate that inorganic growth.

Our next question is from Raimo Lenschow with Barclays.

International is a big kind of driver for you. And you mentioned a little bit of that, but like if I look at the growth rate, there's not that much difference between U.S. and [indiscernible], can you talk a little bit what you saw in the quarter? And maybe there was more on the pipeline build, et cetera.

Yes. Thanks, Raimo. I hope you're well. So yes, we were really pleased with our international performance. And when I say international performance, it's across the 3 major regions that we describe as international. Europe, APAC in Japan. All 3 of those markets had a really good quarter for us. We've historically been talking about our performance in Europe when we talked about our international results. But this quarter, we're talking about it in the context of Europe, APAC and Japan because all 3 delivered solid results in the quarter.

I think that's driven by 2 things. Number one, on the product side, we continue to internationalize and localize our product to serve all of these markets. Number two, we're leveraging a strong network of partners out there around the world to enter these markets. And the third is we continue to attract great talent to lead our Workday efforts around the world. The international market had great results and we expect that momentum to continue as we see customers more and more lean into Workday for their platform of choice across HR and finance.

Our last question is from Kash Rangan with Goldman Sachs.

As is my last Workday earnings call is also hitting, so congrats on the Q3 results, Carl and Zane. I wonder it's fair that you guys are seeing quite a bit of AI momentum. And I agree with you AI disruption risk seems to be little overstated. But I think we can look at the numbers and say that AI, there is some tangible contribution your backlog, 12-month backlog growth rate, although it did include that [indiscernible] did do a little better as these acquisitions the anniversary of they are growing very nicely, that should lead to an acceleration of the organic growth as well. But that effect conceptually, you put your thinking on top, you're thinking hats on -- sorry, down of the plate is calculated. If you were to rebuild a company on an AI native stock in HCM company AI native stack today, what would that functionality be able to do? That is what would that stack be able to do that could be disruptive that you can do as a Workday customer with the tools that Workday is providing both organically or through these combinations of acquisition?

Kash, thanks for the question. And let me say thank you. Going all the way back to our founders, David and Neil and all of our workmates over the last 20 years. We just want to thank you for your continued coverage of Workday. I know this is your last call with us. And I just want to say thank you. And Neil said hello, and he also wanted to send this regard as well as do I and everyone else. You've been a great analyst for us, and we really appreciate your support over the years. And we all hope you enjoy your next phase of life, which you're telling us is retirement. I hope that's the case, and you really do go out and spend some quality time with your amazing wife and family. With that, I'll hand it over to my friend, Gerrit, to talk about how he would build a new HCM or finance platform around AI going forward.

Kash, thank you for ending on such a beautiful question. So let's just look at the core principles of building AI systems at scale, right? And let's just look at what it really is. The first thing that you need is a vast set of data, which basically describes the domain, the domain of finance, the domain of HR and you need a vast set of data that basically codifies how their data is being used, right? That is ingredient number one. If you look at AI at scale, it's about learning and using parents. So you need to have that global database.

Secondly, you need to have strong semantics and clarity about what data we present. So you need to have both a data model that defines. What data element represents what entity in the business? What do they relate on? And what are the rules for these business entities because data is not created equal they have integrity, they have meaning, they have purpose. And you need to have a business process system, which basically tells you how to activate this data in a way so it can drive towards a business outcome. Even more so, you need to have clarity on what that business outcome is. Those are the basics of building a successful solution.

Now take a look at Workday. We are the only scaled SaaS and [indiscernible] in the cloud with a consolidated data set. Our 50 million to 75 million users that we have contribute to a uniform data model, which is completely clean. We have all of the process data in a pharma business process description codifying 70,000 core business process architypes which are instantiated across all of our customers and thousands of variations. We have ample data of usage and how these processes are being used in the business and most importantly, the domain knowledge to specify what are the target outcomes to drive. So if you were to build a system that is built for enterprise AI at scale, it would look like Workday. And what we are doing right now specifically is that we're opening up our core and basically integrate reasoning models and AI systems to automate these processes [indiscernible] or Sana on top to lead the experience AI innovation on top of that. And if you look at all of that in aggregate, it truly is the AI stack for the enterprise of the future.

Thank you. This concludes our question-and-answer session. Ladies and gentlemen, thank you for your participation on today's conference. I'll now turn it over to Mr. Eschenbach for final comments.

Thank you, operator, and thank you, again, for all of you who joined us today. Thank you for those who will continue to look into Workday and watch our results and provide guidance and input to everyone out there in the market. For those celebrating, I want to wish all of you a Happy Thanksgiving. Close by once again expressing my depreciation to all of our work made to our customers and partners for their continued commitment to Workday. We'll see you all next quarter, if not before. And again, for those celebrating Happy Thanksgiving.

This concludes conference. You may disconnect your lines at this time. Thank you again for your participation.