Teradata Corporation Stock

Thanks for joining us for day 2 of the Citi Global TMT Conference here. Today, my name is YC Wong. I'm part of the software analyst team at Citi. We are excited to have Teradata CEO, Steve McMean. Steve, welcome back. I know you've been a couple of years since you joined us.

It's great to be here, YC. Looking forward to the discussion and telling you everything that's been going on at Teradata.

No, that's awesome. I mean this year, definitely a lot has happened since the beginning of the year. Maybe you can just start off with the -- your background, what have you been doing and the company.

Yes. I joined Teradata in June of 2020, really with a mission to look at how do we modernize the company and make it relevant in the cloud space. And so really taking Teradata's fantastic on-premise technology and making it available to customers in the cloud as they modernize their data estates and started using cloud technologies to really support their data platform. And so when I joined Teradata, I said, look, at our core, we're a technology company.

We've been doing a lot of services up until that point. But we had -- we've got so much intellectual property in our Teradata software and the platform that we have that I think that exploiting that for the benefit of our customers is really the core for us. And over that period of time, we actually transformed the company. Now almost half of our recurring revenues are in the cloud. So we made tremendous progress there and developed a really open and connected data platform for our customers. But I think what's been really interesting is if you think of that as Teradata 2.0, we've actually moved into a new phase of Teradata 3.0 when we're looking at AI now. And so that's driven a number of changes for us recently.

Yes. I mean that's an exciting announcement back in May, I believe, when we guys have a big festival out at MISE. So what is the autonomous knowledge platform? Like is it just a repackage of what Teradata has been doing? There's been a lot of changes. Can you kind of help us break down what it is?

Yes. I think really addressing this new world, what we did, we brought in new talent at all layers in the organization. So a refreshed management team to look at the world of AI. We have a new Chief Product Officer that's been with us for 14 months now. And really, the whole team came together not just to repackage what we're doing, but to really think about what is the platform of the future where AI agents and humans can work together and get the most out of their data to really cause business impact.

And so that autonomous knowledge platform is essentially a complete architecture and framework where we've launched new products and capabilities at every single layer of the stack. And by the word autonomous, we're really identifying our technology as well. So not just using agents to code, but actually identifying the entire product stack. And I think nothing symbolizes that more than the very top of the stack, which we think of our workspaces where humans and agents work together.

We have a technology there called Terra, which is a harness that we've developed for AI agents. It means that our customers can use whatever language model that they want. They can use ChatGPT or Claude. But what's becoming more interesting is using smaller language models and working with customers in Europe, looking at some of their requirements around regulatory compliance, use models like Mistral. And what this harness enables the Teradata platform to do is use the right agent at the right time for the right outcome.

And you can really optimize the cost of running your overall environment. And that's just one example of some of the innovation right at the top of our stack. On the very bottom of the stack, if you look at our infrastructure, -- we actually announced a new Teradata factory offering new on-prem technology, GPU accelerated using the NVIDIA product stack built into the data platform so that on-prem, you can run your AI solution and your data platform right next to each other without moving data around and still have all of that great data and financial governance that Teradata provides.

So new innovations at every single layer of the stack. The context work that we've been doing is super exciting in terms of letting AI agents really understand what enterprise data is all about. You can do something like define what a customer is, so you can ask interactive questions around the customer. So it's not just a repackaging. It's a completely new innovative technology set.

Yes. No, it sounds like the whole team has definitely been hard at work over the past few quarters here. But zooming out a little bit more, we would love to talk about like some of how is the enterprise AI agent adoption has been going, like why Teradata like decide to go on this path into the autonomous platform?

Yes. I think we recently did a study across 1,000 or so data leaders in large enterprises across the world. And I think what we're finding is that, that kind of headlong rush to the cloud is kind of slowing down. So we've been thinking much more about how do we grow our overall business, both on-premise and cloud. How do we respond to our customers' requirements? Because it's not just about data modernization anymore, it's about getting value from AI.

And I think what we've proven using our forward deployed engineering capability that we've put in over the last 12 months is we can take those initial ideas and turn them into production reality at scale, utilizing our services capability, utilizing the new technologies that we have inside our data platform. I've got a fantastic example of doing some work for the military in a European country. We've actually been working with them. We started as a pilot to look at camouflage design and using AI models around camouflage design. And we've worked with that military organization to take that from an idea to production scale for their entire military operation, which is a super interesting use case.

Yes. I know there's certainly a lot of opportunity on the public sector as well. But you mentioned FDE. -- like can you give us a sense of everyone has been talking about FTE at this point, like Palantir kind of started it a few years ago. Salesforce ServiceNow to talk about. Can you give us some flavor of how is your FTE working? And what is the opportunity that you see with FTE?

Yes. I think the great thing about our forward deployed engineers, we had a super consulting and sales and SE team. And it really just formalized the go-to-market structure around working with customers on what the real business problems are. And I think that manifests nowhere as much as in the context layer. So working with customers to actually look at their data models, their business knowledge that has been imbued into their systems over time and then working on a specific business problem.

It may be a customer care problem. It could be a supply chain problem and developing the data products to actually help solve that problem in a very pilot phase. So that's what our forward deployed engineers do. And they're organized by industry, they're organized by solution set, and they bring that knowledge and capability to our customers very quickly.

And then we can use our AI services team to actually scale that out and use our technology to deliver those ideas into production in real time. And that is really the challenge that a lot of the data leaders that I talk to every day are -- their core challenge is how do I move from pilot to production at enterprise scale. And that's the problem that Teradata can help them solve.

Okay. No, there's definitely a lot of different levels how FTE is able to help an organization get more ROI. Is there any internal metrics that you track, this is actually like worth my time to invest in because what we heard like FTE costs a lot of money is an expensive services part of it. Like what are you seeing that makes you want to continue to invest in FTE?

Yes. I think -- so our FTEs usually are developed in some form of proof of concept with the customer. So we track how those proof of concepts are moving into real opportunities, how those opportunities are then translating into incremental ARR. They start off by potentially generating a services engagement to do that implementation and then generating technology or product-based ARR as a result of that. So we have a whole pipeline measurement and management system that gives us those leading indicators of moving from that proof of concept right the way through into technology implementation.

Okay. Is there any other like hard numbers that we can, hey, this is improving my sales cycle, improving my delivery time?

Yes. I think if you looked at our earnings comments over the past 12 to 18 months, we've seen a continuing increase in number of proof of concepts that we've been doing. I gave some of those numbers in our earnings calls. But the really interesting thing is now seeing those turn into fruition. with major automakers, governments around the world, financial services organizations, telcos really taking advantage of the technology now and implementing.

Okay. On -- with FTE, do you see -- like what is the conversion cycle for you to make going services upfront, like what's the return that you're seeing? Is it 6 months out, a year out?

Yes. I think what we see is an enterprise software sales cycle emerge, right? So it starts off with that thought and then it runs through a sales cycle. So 6 to 9 months is a pretty good indicator of that kind of sales cycle. And it's why we knew that we -- as we came into the year, we would have a tremendous amount of innovation.

And you can just see that in terms of the press releases and the capabilities that are going into general availability for us over the first part of the year and our Teradata factory going live, our new dynamic compute engine going live, some of the new context offers becoming available in the marketplace. But it takes time for those to monetize. So as we came into the year, we knew that we returned the company to ARR growth last year.

We knew that we would accelerate that this year. But we didn't bake into our number any large upside from the new products for this year. So as we look out into the future, we see a real opportunity to continue that growth acceleration into 2027.

No, that is definitely takes some time. May we look forward to seeing that trajectory improving. Maybe going towards the product side instead of driving too much finance. Maybe Sovereign AI, there's kind of one thing that has been like being a bigger topic with Teradata factory that you mentioned earlier. Can you kind of give us a sense what is the opportunity with sovereign AI? And what are your -- how is your customer conversation with?

Yes. We see it very clearly, especially in regulated or highly regulated industries or in governments around the world. And I think the important thing is to think about sovereign AI, you can break it down. So there's sovereign infrastructure, so making sure that you have control over your infrastructure. And we've seen a number of customers choose to deploy workloads on-prem rather than deploy in the cloud.

That's one of the reasons why we oriented our investors to look at what's our total ARR growth, not just thinking about how well we're doing in the cloud as an indication of how well we're going to do in the future. cloud is always going to be important and be a key part of our driver. But looking at the total ARR growth for the company, that's really what's going to drive our company forward. So that -- there's an infrastructure choice there.

And Teradata factory gives our customers the opportunity to run AI workloads in their own data center right next to their data platform. And then there's AI sovereignty from a data perspective, enabling customers to choose where they put their data. They can put their data in a cloud, in a private cloud, they can put their data on-prem. And then there's AI sovereignty.

So where does the AI model run? Does it run -- do you run in a general purpose model like Claude on the public web? Or do you run that in a cloud environment? Or do you run those models on-prem? And we've developed our platform to be able to have sovereignty at all layers in the stack and give that capability to our customers.

Yes. Is sovereign AI just kind of mainly a compliance discussion that you're having? Or does it also involve customer wants to make based on better performances, the cost involved or the data gravity of a certain?

Yes. I think the initial discussions are certainly being driven from a compliance perspective. We see a lot of our customers in Europe and in Asia really thinking about that sovereign AI infrastructure and not running on public cloud. However, what we do find is that all of the benefits of the Teradata architecture come to life when we see very high volumes of queries, very high volumes of users, query complexity being very high. That's where the Teradata engine really starts to shine in terms of executing this workload.

So it's not just a regulated industry. It starts to get into the cost of owning and operating these platforms, how much does it cost to run? Because Teradata, we solve complexity with great software rather than scaling out our compute as some of our competitors do.

Yes. Trying to tie into what you're seeing on sovereign AI, especially outside of Americas, how do you see the opportunity going to be potentially impact your ARR number longer term?

Yes. I think as we've looked at it in the past, really our on-prem business, I think, was kind of flat to decline. But I think what we're now seeing is actually, there's -- we can see growth coming from our on-premise instantiations. In fact, just an interesting statistic. Half of our business is on-prem, half is in the cloud, as I said before. But for the 50% of our ARR that's in the cloud, half of our customers that are in the cloud with us have also retained on-prem environments.

And they're creating a fabric across their entire data platform, across the cloud and on-prem to have an integrated data environment no matter where their data is stored. And that's a real advantage that our customers are taking and utilizing to have the best possible data platform for their particular use cases.

Okay. Does that kind of impact how you're thinking? Because historically, we think about cloud transformation project, there's a certain uplift to it. How do you think about balancing customer wants to remain hybrid at this point versus moving to the cloud?

Yes. I think that's the great thing with the Teradata offer. We offer our customers choice. And so when they want to keep that data sovereignty, when they want to keep that data inside a highly controlled environment inside their own 4 walls of a data center, we offer them the capability to do that. If they want to run in a VPC in cloud, their virtual private cloud environment, we can run inside that VPC with them.

If they want a fully managed Teradata SaaS solution, we can run it as SaaS for them. So we offer all of those different types of deployment models. And a lot of our customers are responding really well to that because they see it as a real advantage from a flexibility perspective in terms of if rules and regulations change, how can they dynamically respond to that.

Okay. Yes. That sounds like there's a lot more opportunity like people are definitely talking about hybrid. Maybe just moving -- pivoting a little bit with some of the transition that we are seeing with AI coding too, right? We have Astra launching last week, definitely causing a little bit of still within the software industry. Like curious to see how are you seeing -- because you have Terra coding, you have like a different Terra code, a lot of new product coming out. What are the opportunity on the AI coding, either just helping with modernization use cases or day-to-day work within your customers?

Look, the challenge that I've given to Sumeet, our Chief Product Officer, is to use AI and the identification of the entire Teradata platform as an opportunity to leapfrog the competition. And so Tera transforms the way that agents and humans can interact with the Teradata platform. You can use natural language interface. You don't need to learn how to code in SQL anymore. You can use natural language interface to do administration tasks of the platform and manage the control plane. But one of the really interesting things about our Teradata harness is it actually optimizes and governs the use of agents.

So a lot of our competition is essentially passing through token cost in terms of the revenue model to their customer. We don't do that. We allow our customers to use the right model at the right time, which has been particularly beneficial in countries like France, where the French government are promoting the use of Mistral as an example, as a language model. You can plug that right into the Terra harness and utilize that as your core language model rather than using a Claude or a ChatGPT.

And we're seeing customers create really interesting use cases using that technology and deploying to massive numbers of users inside their environment because it takes away that skill requirement to understand how the data is constructed, what the table schema looks like. It completely leapfrogs the way that you access your data platform. So we think about Terra really as the claude for data, if you can think about it like that.

Yes. No, absolutely, we are seeing a lot of efficiency gain with coding tools, C, CX. -- just from an investment perspective, how -- where do you see Tera could help drive a change within the ARR or even margins, right, help drive better efficiency within the organization?

Yes. So I think a couple of things. One, we use a lot of AI coding tools to really increase the speed of our innovation and delivery. I think if we look at the last 14 months in terms of the product development and product engineering that we've been able to execute, a lot of that has been as a result of using these coding tools. But for our customers, we actually are -- we actually expect Tera to drive significantly more usage of the Teradata platform.

And we see it as a mechanism to allow other agents to drive usage of the Teradata platform. Now one of the great things about the way our platform works and some of the patents that we have is we are designed for AI workload in our active compute. Our massively parallel architecture that we have says we can work with incredible high volumes of users. And so if you think about enterprises of the future, they're going to have tens of thousands of agents. They're all going to be heading the data platform at the same time with queries.

So they're going to have lots and lots of concurrency of usage. And then the complexity of those queries are going to increase over time as the agents develop more and more complex queries that they're going to ask. And if you look at those different parameters around the use case, that's exactly what the Teradata Active Compute engine was designed to address. But we've also just announced in June, our dynamic compute engine, which is targeted specifically to essentially deliver the same kind of workloads as Snowflake and Databricks from an agent.

So these are ephemeral compute engines that an agent or a human can spin up and spin down inside the environment. It's an offer that we can run for a customer, but not only that, they can run it inside their own environment, too. And so we can just essentially sell it to our customer as a software-only solution where essentially, they run it inside their environment. And that's going to be a very flexible pricing model that we're going to be able to take to our customers into the future.

And it's another level of innovation that we're doing in what we call our compute substrate. That's essentially where all of the engines are that interact with the data platform. And so I think as these agents start opening up new queries, new business use cases, they'll drive consumption both to our active compute engine, which we'll do in a very nicely financially governed way, but also start to spin up dynamic compute capability inside the environment. And the agents and the governance that we put around those agents will use the right engine at the right time to deliver the optimal solution for our customer because nobody else in the industry has that active compute engine that's allowed Teradata to work at enterprise scale globally for the past 20 years.

Yes, certain advantage that Teradata has been around for a long time, unlike some of these newer data platform companies that you talked -- you brought up Databricks and Snowflake, like when we were out at Snowflake Summit or Data AI Summit, recently heard a lot about how coding tools help them do faster modernization migration project from legacy platforms, right? What are you seeing in the last few quarters or months from competitive nature between this cloud data native platform?

Yes. Well, I think from our perspective, our retention rates have improved. They improved last year in '25 and they continue to improve into 2026. And so I think like what we are seeing is our customers are using these tools to think about how to get business value out of AI. So -- and modernization of the environment is something that Teradata offers now with our new architecture. And so it's not become as much about the modernization of the data platform. It's turning into a discussion around how best can I solve this business problem.

And we've developed a framework and an architecture from Terra all the way through to our infrastructure layer that enables our customers to solve those business problems in exactly the way that they choose. We don't lock you into a particular language model. We don't lock you into a particular context capability. We are developing technologies in each layer of the stack that gives our customers choice in terms of how they execute.

Okay. It sounds like you are more wheeling instead of just a replacement, they're replacing certain product or you are replacing them, you're more cooperating together at certain use cases where Teradata is better at or Snowflake is better at, right? How does that solution work from a customer perspective? Are they -- do they have to like get more integration needs between -- in order to integrate Teradata or autonomous platform?

Well, I'll give you a good example. In our context layer inside our architecture, our very first announcement from a context perspective didn't just develop context for organizations for data that's stored inside the Teradata platform, it also developed context for Google BigQuery. And what we see inside our customer environments is, especially these very large organizations, they'll have multiple engines and multiple capabilities. what the platforms that will win into the future have to be open and connected.

And that's something that we built in as we designed our cloud-first strategy, we knew that as Teradata, we had to be very focused at what we're good at. We have $110 million or so of R&D. We have to be very focused in terms of where we invest that and the differentiation that we have as a platform. But what we believe is the platforms of the future and the gentic future will enable these agents to choose the right capabilities at every layer in the platform to solve the problem that they're trying to solve. And we believe that in every single layer of the stack, we've got the best technology that can differentiate from our competition. either from a cost per query or a total cost of ownership, but not just that, also the capabilities of the platform.

And I think we'll start to see those agents driving that kind of workload into the future. Not very many people would -- people would be surprised to learn that Teradata appeared for the first time in the AI/ML, Gartner Magic Quadrant. And the very first time we appeared, we ended up as a visionary in terms of the capability that we were looking at developing for our customer set. And those products are starting to come online now, and we believe will help to drive significant growth as we move forward.

Yes. It sounds like the big focus definitely focused on getting enterprise ready to get agent workload into production, right? Is there a specific vertical that Teradata focus are seeing are leading the pack?

Yes. I think we've certainly -- again, I'll talk to our context announcements. financial services, telco and health care have been some of the initial industries where we've been developing that context for our customers. Now you have to put into consideration the fact that we have developed comprehensive industry data models across multiple industries. For those of you that don't know Teradata, we serve all industries from manufacturing to governments to large banks, large insurance companies, and we also do that on a global basis. So we've got great dispersion in terms of where we get our revenues from.

But having a lot of experience in working with these -- the largest enterprise in the world has enabled us to build up these context maps that we can make available to AI agents to quickly get them off the ground to deliver real business value. And we do that through our technology. We do it through our AI services capability and bringing all that together for our customers. But the initial set of industries are financial services, telco, they are really important to us as well as health care.

Okay. I guess now maybe we have like 5 minutes left here. I'd like to see if there's any questions from the audience, a few minutes. One from Joe.

Talk about your relationship with NVIDIA and what the Hugging Face acquisition, what opportunity might mean Teradata?

Thanks, Joe. Yes. So our Teradata factory is a ground-up rearchitecture of our on-prem technology set. It's something that we co-developed with Dell. -- and Dell have actually committed to work with us from a go-to-market perspective to take this capability to market. But it's a GPU accelerated on-prem technology, which also runs on the NVMe, the NVIDIA software stack for running language models. And we have already deployed that technology with customers. There's a large bank in the U.S. where we've deployed that with Hugging Face sitting on top.

We also did it in a bank in Australia. So Hugging Face on the NVIDIA software stack on top of Teradata to solve customer complaints analytics and also customer service interactions. What the announcement between NVIDIA buying Hugging Face is we'll see tighter integration of that software stack -- and as opposed to us integrating it for a customer, it will be a self-serve software stack that you can run on Teradata factory. So we see this as a really exciting opportunity to work with an established partner like NVIDIA to really deploy that on-prem.

Yes. No, the open web model is certainly a big discussion right now. Like how do you see this coos source versus open source model impacting how Teradata communicated LOI with customers?

Yes. I think we are already seeing a lot of our customers wanting to use those open weight models. They're cheaper, they're smaller, they're more efficient, more effective. Also, those smaller language models can be trained very effectively in a particular domain. And that's why we designed our Terra harness so that you could take advantage of the right kind of language model deployed in the right technology, so deployed on-prem or deployed in the cloud.

And so that for us is a key part of our value proposition in terms of enabling our customers with that choice from a language model perspective to really optimize their environment, make sure that they've got token -- their tokenomics working out for them, right? So that's a key part of our value proposition as we move forward.

Yes. I think Terra Harness is that still a preview or it's not officially GA, right, right?

It's in preview just now. And we are actually thinking about given the source code to the harness to our customers because they want to develop their own harness with certain features in it. So we will maintain a code line that is for Teradata, and we will manage and run that for our customers or they can utilize our code base to really look at how they optimize the harness inside their environment.

And so by having that kind of open source kind of layer inside our product stack, we think that will open up the opportunity for lots and lots of customers to ultimately use the Teradata platform as their data platform as that integration, that harness is able to integrate through all layers of the stack.

Yes. I guess we're still very early on it. Every -- all the Frontier Labs data talk about harness layer as well. Like what have you seen from your customer that uses the Teradata harness?

I think they like the fact that it's so open and also the fact that it's focused on data. We're not trying to be -- to use language models or harness to develop applications. We are looking at Tera as the quad for data.

Okay. Is that going to help you drive like faster consumption...

Consumption straight through to the data platform. And also, as organizations implement agents, they know that they can use the Tera agents as their data experts inside their entire infrastructure.

Right. So we have a last minute here. Maybe just talk about the autonomous platform help you go into a different frontier. If you're thinking out a year, 2 years out from here, what do you believe is the next major phase of innovation that Teradata would be part of?

Yes, I think in today's world, it's difficult to forecast more than 3 months out. But I think you had the -- I think the key point there is, look, what we've seen in Teradata over the last 14 months is a tremendous amount of innovation that's allowed us to reposition the technology proposition that we've got and reposition the company to accelerate growth as we move forward. And that's certainly our ambition as we look to 2027 and beyond.

Yes. Great. I think there's going to be a big autonomous conference out in Dallas as well coming up.

November. It's nearly sold out. We just had to move to a different venue. So I'd encourage anybody that's interested to come to come along.

Great. Thanks, Steve. Thanks, everybody.

Thank you.

Good afternoon, and welcome to Teradata's second quarter 2026 earnings call. Steve McMillan, Teradata's President and Chief Executive Officer, will lead our call today, followed by John Ederer, Teradata's Chief Financial Officer, who will discuss our financial results and outlook.

Our discussion today includes forecasts and other information that are considered forward-looking statements. While these statements reflect our current outlook, they are subject to a number of risks and uncertainties that could cause actual results to differ materially. These risk factors are described in today's earnings release and in our filings. Please note that Teradata intends to file the Form 10-Q for the quarter ended June 30, 2026, within the next few days. These forward-looking statements are made as of today, and we undertake no duty or obligation to update them.

On today's call, we will be discussing certain financial measures which exclude such items as stock-based compensation expense and other special items described in our earnings release. We will also discuss other non-GAAP items such as free cash flow, adjusted free cash flow, and constant currency comparisons. Unless stated otherwise, all numbers and results discussed on today's call are on a non-GAAP basis. A reconciliation of non-GAAP to GAAP measures is included in our earnings release, which is accessible on the Investor Relations page of our website at investor.teradata.com. A replay of this conference call will be available later today on our website. And now, I will turn the call over to Steve.

Thanks, Chad, and thanks to everyone for joining us today. We're pleased with our solid performance in the first half as Teradata delivered another good quarter with growth in total ARR, recurring revenue, and meaningful free cash flow improvement. Our total ARR growth reflects our belief that the hybrid capabilities we're delivering set Teradata apart. Additionally, our significant platform innovations, tangible operating leverage, and anticipated incremental gains in our retention rate underpin our confidence in the future. We are reaffirming our outlook for total ARR, total revenue, and recurring revenue. And we are increasing our non-GAAP earnings per share range to $2.65 to $2.73.

We're also increasing the range for adjusted free cash flow to $330 million to $350 million. The global shift to AI is profoundly affecting every major industry as enterprises face growing pressure to move AI into production. We recently surveyed 1,000 senior technology and data leaders around the globe about their use of agentic AI within the enterprise. We found that 90% expect to increase their agentic AI investments over the next year, yet nearly two-thirds have seen only small or emerging positive returns to date. In addition, 40% of technology leaders surveyed say more than 40% of their AI pilots have failed to reach production because their infrastructure was not built to support them. We are here to change that. We set a clear vision for this agentic AI era.

We call it Teradata 3.0, and we have retooled our business for this clear opportunity of autonomous intelligence. Teradata's robust hybrid data foundation, in use at many of the world's leading organizations, is essential to help enterprises deploy the business infrastructure needed to get ROI from their AI initiatives. The mission-critical nature of this work is not discretionary. Enterprises need it. And we believe we have the best data foundation to help organizations achieve real value from their AI initiatives. This brings me to our product innovations in Q2, which I consider one of the most significant chapters in Teradata's history. As organizations increasingly turn their attention to realizing value from AI, our product organization leaned in and accelerated the innovation pipeline to meet the market opportunity. In May, we launched the Teradata Autonomous Knowledge Platform, our foundation to deploy agentic AI without trading control for capability, governance, or performance.

It runs where enterprise data already lives, on the customer's terms, and at costs that reflect how agents actually work. Most infrastructure was built to deliver one of those things at a time. Our platform is designed to deliver all three. It brings together a powerful set of new capabilities for customers, and I'll discuss the four main components. Teradata Cloud is purpose-built for the agentic era. The reality is that AI agents create computing demands unlike anything human users have generated before, and that informs how our cloud offering is designed. Active compute and elastic compute give organizations always-on power for mission-critical workloads alongside on-demand capacity for everything else.

Teradata Factory extends the platform on-prem for organizations where data sovereignty is preferred or required. It delivers private AI and enterprise-grade performance in a single integrated system built with Dell Technologies. And with integrated CPUs and GPUs built in, customers can run the models that fit their needs, including foundation models, entirely on-prem. Their data never leaves their environment while scale and performance remain fully intact. Teradata AI Studio unifies analytics, models, agents, and vector services in one environment, so customers no longer need to source, integrate, and manage those capabilities as separate tools. Combined with our AI services consultants who bring years of domain experience, expertise, and sophisticated analytics, AI initiatives can move reliably from concept to production-grade execution at speed. Trusted enterprise data and built-in governance travel with every project, allowing organizations to scale with confidence. Finally, Terra is our agentic coworker, the natural language interface that gives every user governed access to enterprise data and agents.

Terra includes built-in modes for data analysis, coding, and multi-agent orchestration, giving business users, data teams, and developers a single place to interact with enterprise data and AI. The connectivity that makes this possible depends on open standards. Teradata joined the Agentic AI Foundation, where standards like the Model Context Protocol are being built. Our enterprise MCP server is already in action with customers, and our participation is intended to ensure that real-world enterprise requirements, including hybrid, on-prem, and sovereign deployments, are built into those standards from the start. I'm pleased to report that the Teradata Autonomous Knowledge Platform, including its AI Studio component, reached general availability in early Q3, a couple of months after we announced it. That execution velocity reflects the confidence we have in what we've built and the step change it makes possible for our customers. The quarter brought additional innovations to market as well.

We made available our enterprise-grade data analyst agent in AWS Marketplace, bringing AI-assisted conversational analytics directly into customers' existing AWS environments. This agent enables advanced multi-step analytics on data that's already there with no costly movement or integration complexity. It also delivered expanded data access through upgraded native open table format support, enabling customers to query seamlessly across more distributed data without unnecessary movement or duplication. But access to data alone doesn't get enterprises to production AI. Our research shows that context fragmentation, data that exists but carries no usable meaning for agents, is the defining barrier holding organizations back. In fact, 77% of executives reported that 20% or less of their data is sufficiently described for agents to use reliably. It's a challenge we hear and one we are focused on helping customers change. We're proud of the broad set of product innovations we brought forth, yet these are just the first in a series of planned announcements we'll have this year.

We're going to be delighted to tell our customers more at our upcoming Autonomous World Tour events. All of these offerings will continue to leverage our differentiated hybrid capabilities and the very real need for production AI that runs anywhere, grounded in governed data and context that is critical for agentic AI. As our teams take our new platform and AI narrative to the market, they are receiving positive responses from customers and support for the need to activate the intelligence across their enterprise. We're hearing that our capabilities with one platform that supports AI, sovereign data, security, and multiple deployment scenarios are generating increasing interest. We have already had early wins from the innovations we announced and from both on-prem and cloud environments. I'll touch on a few examples. A major telecommunications company in South Asia selected Teradata Factory to power its broad AI modernization initiative.

The customer deployed GPU-enabled infrastructure and Teradata AI Studio to support advanced analytics, vectorization, and RAG workloads. This demonstrates Teradata's growing ability to lead enterprise AI transformation conversations across emerging markets. [indiscernible] platform, but foundational to our customers' AI ambitions. One of the largest banking groups in Japan and a longstanding Teradata customer implemented a cloud modernization project, selecting Teradata Cloud, AI Studio, and AI Services to enhance its profitability simulation and planning workloads. We expanded our relationship with a federal tax authority in Asia Pacific as it renewed its Teradata Cloud environment and balanced flexibility with the resilience and performance requirements of this critical government platform. This reinforces Teradata's ability to align customer success with long-term platform growth, positioning us to support future workload expansion driven by legislative change.

One of North America's largest financial institutions also expanded with us, incorporating Teradata AI Studio to accelerate AI adoption and demonstrate measurable value through use cases aligned to the bank's strategic priorities. And a major U.S. healthcare company expanded its on-prem production system in support of government regulations. Our increased engagement in the agentic AI space has not gone unnoticed. Gartner published its 2026 Magic Quadrant for AI platforms for data science and machine learning, and Teradata was named a visionary in our first year of participation. We view it as validation of Teradata as a safe haven, a serious player in the AI platform market, and note that this evaluation did not even yet include our latest product announcements. As I hand the call to John, I'll close on this. This quarter we set out a clear vision for the next era of Teradata, Teradata 3.0, anchored by our new Autonomous Knowledge Platform built for the agentic age.

And we backed that vision with delivery, bringing key components of the platform to general availability within a quarter. Our hybrid capabilities and our on-prem strength in particular continue to resonate with customers running the most demanding and regulated workloads where a solid data foundation is not discretionary. That combination of a differentiated platform and disciplined execution set the foundation for a solid first half and gives us confidence in our outlook for the year. John will cover in more detail, including the areas where we are raising our expectations. We remain focused on converting this momentum into durable, profitable growth and lasting value for our shareholders. Now, over to you, John.

Thank you, Steve, and good afternoon, everyone. We delivered solid financial results in the second quarter, highlighted by continued improvement in recurring revenue, profitability, and free cash flow. Recurring revenue grew 3% year-over-year, marking our third consecutive quarter of positive growth. We also drove meaningful expansion in non-GAAP operating margin to 21.5% compared to 16.4% in Q2 last year, reflecting our continued focus on operational discipline and profitable growth. In addition, adjusted free cash flow was $127 million in the quarter, significantly higher than a year ago. At the midpoint of the year, we are pleased with the improvement we are making and believe these results reflect continued progress against our financial objectives and demonstrate our focus on driving sustainable shareholder value. In terms of our detailed financial results for the second quarter, total ARR grew 1% as reported and 2% in constant currency, while cloud ARR grew 8% as reported and 9% in constant currency.

As we have said previously, our focus remains on driving total ARR growth, and we may see variance from quarter to quarter in the mix between cloud and on-premise growth. Second quarter total revenue was $410 million, flat as reported and in constant currency, which was 2 points above the high end of our outlook due to higher recurring revenue. Second quarter recurring revenue was $363 million, up 3% year-over-year as reported, and 2% in constant currency, which was 3 points above the high end of our outlook. The outperformance was primarily due to the timing of revenue recognition related to our on-premise business. Second quarter consulting services revenue was $39 million, down 24% year-over-year as reported and 23% in constant currency. While this was a softer quarter from a revenue standpoint, we have had improvement in our consulting services bookings and project backlog is growing. Additionally, we are continuing to optimize the cost structure to return the business to a low double-digit margin percentage.

Looking at profitability and cash flow, please note that I will be referencing non-GAAP numbers for expenses and margins and a full reconciliation to GAAP results is provided in our press release. For the second quarter, total gross margin was 60.5%, which was up 220 basis points year-over-year, driven by a higher mix of recurring revenue. Recurring revenue gross margin was 67.8%, which was up 30 basis points versus Q2 '25, driven in part by continued year-over-year improvement in our cloud gross margin. While recurring gross margin was lower on a sequential basis from Q1, this was in line with expectations due to the higher upfront revenue in Q1 '26. Consulting services gross margin was flat. As noted, consulting services revenue came in lower than expectations, which impacted the margin in the quarter. Operating margin improved significantly on a year-over-year basis, coming in at 21.5% versus 16.4% in Q2 last year.

On a year-to-date basis, operating margin is at 24.5%, which is up 540 basis points versus the first half of 2025. The margin expansion was driven by a return to revenue growth, higher gross margin, and a more optimized cost structure. Non-GAAP diluted earnings per share were $0.69, exceeding the top end of our outlook range by $0.12. The outperformance was primarily driven by higher recurring revenue. We generated $127 million of adjusted free cash flow in the quarter. This increased our net cash position to $323 million at the end of Q2 '26. On a year-over-year basis, we have increased our net cash position by $528 million.

Finally, we continue to return value to shareholders repurchasing approximately $40 million or about 1.3 million shares in the second quarter. We continue to target to use 50% of our adjusted free cash flow for share repurchases, which excludes the benefit from the SAP settlement. Also, we paid off the remaining $450 million balance on our term loan. Given the strengthened balance sheet, this will enable us to make future strategic investments in AI as well as continuing our stock buyback program and being opportunistic on strategic M&A. Before turning to our financial outlook, I'd like to provide some additional context. For total ARR, we expect modest sequential dollar growth from Q2 to Q3. We continue to anticipate the majority of our growth will come in Q4. For recurring revenue, we saw improved linearity over the first half of the year compared to our initial expectations at the beginning of the year.

As we discussed on last quarter's earnings call, this is a factor of revenue recognition under ASC 606 and recognizing more upfront revenue related to the on-premise portion of the business. Our guidance for the year remains unchanged. We did experience higher growth over the first half of the year and expect slight declines on a quarterly basis over the second half of the year. Now, turning to our annual outlook for 2026, we reaffirm our ranges for total ARR, total revenue, and recurring revenue. For non-GAAP earnings per share, we are increasing the range to $2.65 to $2.73. For adjusted free cash flow, given the strong first half of the year, improved recurring revenue linearity, and the benefit of paying off the debt, we are increasing the range to $330 million to $350 million. For the third quarter of 2026, recurring revenue is expected to be in the range of -4% to -2% year-over-year. Total revenue is expected to be in the range of -6% to -4% year-over-year. And non-GAAP diluted earnings per share is expected to be in the range of $0.55 to $0.59.

In terms of some of the other modeling assumptions, for the third quarter, we expect the non-GAAP tax rate to be approximately 23% and the weighted average shares outstanding to be 96.7 million. Also, we now anticipate FY '26 other expenses to be approximately $19 million. In summary, we are very pleased with the first half of the year and remain confident in our ability to achieve our full year objectives. We significantly strengthened our balance sheet, generated very strong free cash flow, and continue to execute our profitable growth strategy. By driving operational efficiencies while maintaining targeted investments in innovation, we are positioning the business to benefit from meaningful operating leverage as growth accelerates, supporting further margin expansion over time.

Now let's open up the call for questions.

[Operator Instructions] Your first question comes from the line of Erik Woodring.

And I just have one other quick follow-up. So I guess, John and Steve, it's a combined question for you guys. And just you sound really positive on the kind of environment Teradata is operating in right now. Obviously, a number of key product launches in the second quarter, many of which go GA or have gone GA this quarter. As I think about your guide, just help us understand why the kind of shape of the year is first half growth versus second half declines when we're in this kind of really strong environment with new products coming out. We'd just love to get a little bit more context because I would think the direction of the year would go the opposite direction.

You could see accelerating growth. Just help us understand some of the moving pieces that maybe would make us feel more at ease understanding the shape of the year. And then a quick follow-up, thanks.

Yes, hi, Erik. I'll just talk to the customer and the demand environment that we're seeing in the market. We're seeing really great interest in terms of the Teradata value proposition and how we can process data workloads, especially in the world of agentic AI. Our first half product launches were really designed to capitalize on that. And I'll talk a little bit about our Teradata Factory, which is our new architecture for delivering AI workloads on-prem designed from the ground up. What we're seeing is customers with Teradata are able to make a choice. They can either deploy those workloads in the cloud or they can deploy those workloads on-prem, and as they are evaluating our new technologies, they are making those choices so that our overall total ARR is in a good position, and that's why we reaffirmed our guidance for the full year.

Q4 continues to be our strongest quarter from a selling perspective. And from a market perspective, we do expect to have great interest in the new product launches. Although we haven't factored a lot of those new product upside opportunities into our guide so far. John, do you want to talk a little bit about that?

Yes, Erik, let me just add maybe a couple of points of clarification around the guidance specifically. So first off, if you look at the full year expectations, whether that's for ARR or revenue, we've been very consistent on those full year outlooks and feel like we're right in line and on target with achieving those. What has changed this year has been the linearity on the revenue side in particular, and even more specifically the recurring revenue side. And so due to the nature of ASC 606 accounting, which we talked a little bit about on the Q1 call, and again, in our prepared remarks today, we did see more upfront revenue coming from the on-premise subscriptions over the first half of the year. That means there's a little bit less revenue to be recognized in Q3 and Q4. So we are seeing, I'll call it a displacement almost, of revenue recognition more in the first half versus the second half, and that's reflected in our revenue guidance, but otherwise for the full year, total revenue and ARR are tracking very nicely with our initial ranges.

Okay, I appreciate that color, guys. Thank you. And then John, maybe just a quick follow-up. You just beat 2Q by $0.14. I think the full year earnings guide went $0.09 higher. Just what are some of the earnings headwinds that I guess you're encountering in the second half? Because inherently, if 2Q is beating by more than you're raising the full year, second half EPS needs to come down a little bit. So just what are the incremental headwinds we need to be taking into account? Thanks so much.

Yes, Erik, thanks for the follow-up. It's a little bit of the same answer, to be honest. And so when we look at the revenue performance over the first half, particularly the incremental recurring revenue coming in, that provides a big boost on the earnings side as well. And so as we balance that out, as we move through the year, again, our annual targets are generally going up for the earnings per share. We raised that again, but the timing of when those impacts hit has shifted on us.

Your next question comes from the line of [ Roddy Salton ].

First for Steve, I wanted to drill into Teradata Factory a little bit more. Can you just walk through customer conversations there? And then I'm curious in like how you expect that to drive pull-through to other parts of the business? And how do you see it impacting this sort of competitive outlook in some of these shared accounts where maybe your cloud-native competitors obviously don't have on-prem offerings, and how that kind of impacts the retention outlook there. Thank you.

Roddy, thanks for the question. We certainly see Teradata Factory and our ability to execute these workloads on-prem as a really differentiating point against our competitors. Just to level set everybody, Teradata Factory is our next-generation architecture. It's got GPUs built in from the ground up. Now, what does that mean? It means that AI workloads can run natively on both the GPUs and that infrastructure, but also on the CPUs and our massively parallel processing architecture. So that expands use cases and the footprint that we have. It allows organizations to run AI workloads right next to their data, and they can do that on-prem, which has got great use cases.

For example, where data sovereignty is important, and some of the customer examples I gave in the prepared remarks point straight to that. The other great thing about Teradata Factory is it's been built in partnership with Dell, and building on those Dell Technologies not only gives us access to their advanced technologies, it also gives us access to their go-to-market. So even though Teradata Factory is still to go GA in the second half of the year, what we're looking at is we've already seen orders and interest for Teradata Factory, and working with the Dell teams, we expect to have a very successful offering in the marketplace that gives customers true choice. And that's why, as we look at the overall business, what's important to us is total ARR. So when customers make the choice to deploy on-prem or in the cloud, we can capture that growth with them.

Got it. And then just a follow-up for John. The balance sheet is obviously in a great place post the SAP settlement, the debt paydown. Could you just walk through how you sort of stack rank highest ROI uses of capital here, you know, stock buyback, bolt-ons, R&D, especially given, you know, the product launches? So let's just dig into your thinking there as you think of capital from here.

Yes, sure. Roddy, appreciate the question. And yes, you know, our balance sheet is in great shape. It's very strong following the retirement of our debt in the second quarter and also the strong free cash flow that we had over the first half of the year. So from a capital structure standpoint, I feel like we're in a very, very good position. In terms of the current allocation priorities, I would stack rank the ones that you mentioned with organic R&D first, followed by our stock buyback program, and then strategic M&A. I guess I'll also throw in the caveat that of course we always reserve our right to change our priorities in the future, but currently if you look at the model, we're investing quite a bit in R&D this year and we're also continuing to do 50% of our free cash flow towards the buyback.

Your next question comes from the line of [ Yi-Chun Wang ].

Definitely good to see some of the call-outs among your AI use cases getting some traction for your customers. We certainly heard of rising concern from coding tools out there from your peers, like helping drive faster AI monetization and migration. With the launch of the autonomous platform GA recently, could you kind of help us think about how these tools are helping your customer conversation and conversion within your base, and then why the AI monetization seems to lag behind what your peers are seeing with accelerating growth recently.

Yes, thanks for the question, YC. I think there's a couple of factors coming into play. One, I think our vision and the architecture that we have for a fully agentic and autonomous knowledge platform for AI is really resonating with our customers. And what that means is we're actually agentifying our entire stack and changing the way that customers can interact with our platform. We're also really excited about the work that we're doing from a context layer perspective, which really provides context around business data to these AI agents so that they can query the platform successfully. What we see in terms of a revenue model, and we will certainly be looking to monetize some of the new products that we have coming in the stack. But what we're really going to see is increased utilization of the existing Teradata platform.

And so the lag essentially is as organizations utilize these new capabilities in the platform. It's essentially utilizing capacity and capability that they've already bought from Teradata. But not only that, one of the advantages of running these workloads on the Teradata platform is that costs and expense don't spiral out of control as these agentic workloads deploy on top of the platform. That's a unique competitive differentiation, but it does give a lag to the growth that we see from an ARR perspective, but certainly the opportunity is there. Our customers are excited about the offerings. We've had a great first half in terms of innovation, and we plan that to continue into the second half. And we'll certainly be looking to monetize that as we go along.

That's helpful, Steve. John, I have a follow-up for you. Cloud ARR seems to came in a little below expectation given the double-digit guidance is out there. And then with this shift in, like some of your peers reported kind of shift in AI budget over the past couple of weeks, are you seeing any shift in your customer budget or any incremental impact from like the elongation of the Middle East situation? And then maybe get an update on kind of the stage migration from a year ago, any changes from that front? Thank you.

Yes, so there's a couple of topics in there, so I'll try to hit them all. But I think the first was really around cloud ARR growth. And you talked about the target that we had for double-digit growth there. As we've been saying for probably about a year now, I would say our focus is much more on total ARR growth, not just cloud growth. We are still seeing faster growth for cloud versus on-premise subscriptions, but in any given quarter, the mix of those deals may vary a little bit. And so we still think that low double-digit growth target is the right range and the right trend line growth for our cloud business, but again, there may be some quarterly variability. We continue to believe that the hybrid approach is resonating with customers as Steve just described, and that's reflected in the return of total ARR growth that you've seen in the model.

And that's really what we're ultimately trying to drive towards. You also, I think, asked about migration activity. We are seeing less of that this year. We factored less migration activity into our model, into our forecast for this year. I would say peak cloud migrations was probably a year or two ago, and we're now on the other side of that bell curve. We'll still continue to see some of that activity, but much less going forward.

Your next question comes from the line of Patrick Walravens.

Steve, I just want to get a sense for, and John, I guess, whoever wants to address it, forget the revenue recognition for a second. I mean, Steve, were you satisfied with the performance of your sales organization in the quarter? And does the fact that Teradata Factory, I'm sure people are excited about it, but it's not available yet, does that play into how you actually ended up doing?

Look, I think as I look through the quarter, our operational execution and discipline was really good. And you can see that in the results, Pat. From a go-to-market perspective, the teams have really embraced these new offers and new capabilities, are proactively taking them out to our customers. We're getting really good feedback about Teradata Factory, as we said. It's some early announcements and it's going GA. The sales teams are excited. They're energized to take these messages to our customers. I think they see the opportunity that that's going to unlock. Especially if you look at it from an on-prem perspective and the workloads that we can uniquely offer and deliver on-prem from a GPU with the NVIDIA partnership, being able to run local language models.

This is a whole new area for our sales teams to get involved in. And as they're taking these messages to our customers and exploring what they can do with the Teradata platform, with all of these new announcements, it's certainly opening up opportunities for us.

Okay, and then if I could ask a follow-up, I mean, it does seem like as enterprises are rolling agents out across more and more parts of their businesses, there's pressure to consolidate on a single data platform so you don't have to define things over and over again. And then at the same time, you know, there's just a lot more consumption of data. How is that playing out for you guys? I mean, are there situations where, you know, companies are like, oh, sorry, we're just going to standardize on Databricks across this entire thing, or we're just going to standardize on Snowflake across this entire thing? Where does all that sit?

Yes, I think what we're seeing is that organizations don't want to get vendor lock-in. So whether it's vendor lock-in to an individual cloud provider or vendor lock-in to particular data providers, as they look at the AI stack that they are implementing, we think there are certain control points, if you will, or certain points of differentiation inside that stack. One is the agent harness so that organizations can utilize the right language model for the right workload. The second is the context layer within the AI platform or the AI stack. We believe that we can provide real context and business context to data that's inside our customer's ecosystem better than anybody else. And then finally, to your point, Pat, these agents generate a set of workloads unlike any other workloads that we've come across before. But the pattern is clear. They're massive in terms of size and volume.

They're massive in terms of concurrency, and they're massive in terms of query complexity. And just looking at those factors, the best platform in the world to solve them is Teradata and our advanced massively parallel processing architecture. And that's our differentiation when we go in on our customers, that's what's going to enable us to win.

Thank you.

Your next question comes from the line of Matthew Hedberg.

I guess, you know, maybe for John, you know, there's been a lot of talk, obviously, on memory price, storage, hardware, the likes, and given some of the strength that you're seeing, I'm just sort of curious of your perspective on any supply chain thoughts as we head into the second half or even calendar year '27.

Yes, sure, Matt. So a couple of things on the hardware side, and I'll split my comments between our existing platform and then the new Teradata Factory that we've just rolled out or are about to roll out. So, on the existing platform, we actually have sufficient inventory for this year. We had actually pre-bought some inventory as we finished up fiscal '25. And so we're in good shape from a supply chain standpoint on the current platform. And as I look forward on Teradata Factory, there is where we could potentially see some of the pressures from the supply chain and the increased pricing. What we are very focused on is making sure that our pricing is adjusted to end customers so that we protect margins. And so we've got good visibility on how that's tracking. It's early today. And so it won't have a material impact on FY '26, but we're very focused on that as we head into '27.

Got it. Thanks. That's helpful. And then, you know, I guess, you know, from a vertical perspective, obviously, you guys, you know, are well entrenched in the Global 2000. Can you talk about, you know, sort of like, you know, obviously, you talked about kind of on-premise strength in the first half. Can you talk about sort of thoughts on verticals, you know, be it financial services, government, and then, you know, how should we think about those in the second half? And I guess if that has any implication on, you know, potential on-prem cloud mix.

Yes, Matt, I think there's no doubt that in highly regulated industries, our Teradata offering shines through. The other thing that's becoming very apparent, and you can see it from the examples I gave in the prepared remarks, are, you know, in the international marketplace, a lot of organizations are looking at how they can deploy these technologies without using a public cloud infrastructure. And we see that as a massive opportunity for us in terms of utilizing Teradata Factory to solve the data sovereignty challenge. So solve the fact that customers want to have data under their control and inside their environment. Solve the operational challenge of making sure that they control and own the infrastructure that their data and AI solutions are sitting on, and that they can run that effectively, just as they could in a public cloud environment. And that's certainly the offer that we can take to these customers in these, not just the regulated and highly regulated industries, but also in those international marketplaces where they may be selecting different use cases that don't involve public cloud.

Your next question comes from the line of J. Derrick Wood.

First, Steve, back on the hardware component costs. Just are you seeing any change in buying behavior, whether kind of a change in timing of hardware purchases or even a rethinking of migrating to the cloud versus staying on-prem? I mean, I know you guys haven't started pushing out any big pricing changes yet, but how are you seeing customers reacting to these elevated hardware costs in the market today?

Yes, in fact, we have adjusted our pricing for both our existing platform and of course, our new Teradata Factory has a new pricing model associated with that as well. But what our customers are really looking for at the end of the day is price performance. One thing I would say is we completely understand the buying habits of our customers, and we don't really see any change with respect to the Teradata platform. You know, we don't require like large capex investments from our customers. Our recurring revenue model and our commercial model with customers give us some advantage in terms of how we're contracting and the offer that we're taking to those clients. I would say as well is just expand upon the supply chain point and just say that the partnership with Dell has actually meant that we can leverage Dell's buying power when it comes to some of this componentry. And indeed some of the early orders that we've got for Teradata Factory has meant that, you know, we've actually been able to expedite delivery to some of our customers into this year. So from a number of different factors, Derrick, we've got a good handle on what's happening inside our customers.

We're protecting our operating margin. We're delivering price performance at the same time. And the partnership with Dell, we look to is generating some significant value for us.

Great, helpful color there. And John, one quick one for you. I don't know if it's in supplemental disclosures here, but can you give us a sense around kind of your assumptions around FX impact to Q3 and full year?

Yes, I think we do have that posted up on the site, Derrick. And rather than quote the numbers here, I'll just direct you to that document.

Got it. Okay. Thank you.

Yep. Thank you.

Your next question comes from the line of Raimo Lenschow.

Can I stay on that subject of hardware prices and buying behavior? If you look at some of the other players in the market like IBM, there was a big theme of customers trying to buy stuff early to get ahead of price increases coming down the lane and kind of etc. Is that something, John and Steve, that drove the Q2 outperformance or can you just maybe explain one more time to us like why Q2 and then hitting you in Q3?

Yes, I'll let John talk to the linearity again, but just from a market perspective, you know, we are early days in Teradata Factory. So we're excited about the future opportunity that we have with the platform. It didn't drive incremental revenue from that perspective into Q2. So that wasn't the reason for the outperformance, but Raimo, anytime you recognize that we've had good revenue performance and good recurring revenue performance in the quarter, I'll definitely take that. But we're really convinced that the Teradata Factory offer and the hardware refresh that we have, combined with what we've done from a forward buy perspective, means that we've got margin protection and we can offer a great choice of capabilities to our customers. John, did you want to talk a little bit about that too?

Yes, not a whole lot more to add other than the comments that we've already talked about with regards to recurring revenue. I guess, Raimo, to answer your question specifically, hardware was not a meaningful factor in the revenue upside in either Q1 or Q2. We did have an opportunity to increase our pricing on the existing platform at the end of Q2, but that would be more of a go-forward event for the second half of the year.

Okay, perfect. Thank you. And then if you think about the new products, a lot of activity in Q2 and I'm excited to see more there. How should we think about the rollout in terms of like, do we need to think there is going to be some early customers and everyone is going to wait how they are doing and then you have like more broad adoption next year? Or how do you think about the lifecycle there? Thank you.

Yes, I think if I look and characterize the innovation that we've had in the first half, although I've talked a lot about Teradata Factory on this call, you know, most of our innovation is actually in the software. It's actually in the brains and the approach and the overall architecture that we have. And we believe that we've got some real differentiating capabilities and capabilities that are making customers think about Teradata in a very different way. I use the term on the prepared remarks, Teradata 3.0. So not just being an open and connected multi-cloud data platform, which gave us some real differentiation, but really thinking about Teradata as a knowledge platform. And that's really all based in the fantastic software that our product team is creating every single day.

And that's really going to make the difference in terms of the positioning that we have with our customers. And it will go through the usual product launch cycles in terms of how we're going to monetize that. We certainly see some of our customers picking up those capabilities early on in terms of, you know, the agentic platform that we've got out there. And also in terms of our AI Studio and the capabilities that we have at the front end are generating some real interest, but it's early days. So it didn't really have a material impact to our very solid first half, but we're looking forward to it having some impact as we move into the future. Thanks for the question, Raimo.

Perfect. Thank you.

Your next question comes from the line of Wamsi Mohan.

Steve, for the early AI wins discussed, are customers generating incrementally new spending? Are they expanding existing commitments? Are they reallocating current heritage spend to AI Studio and related products? Would love some color over there and I will follow up.

Yes, in Q2, we actually, I would say we had all of those bars, Wamsi. We actually, we got some new logo wins. We had the expansion in terms of workloads that we were delivering. We had expansions on-prem and in the cloud. So we were very happy with the variety of wins that we get from the AI platform. And again, I think, just reflecting back to one of the very first points that we had in Q&A, that's a unique differentiator for us. Being able to run these AI workloads close to the data, right next to the data, both on-prem and in the cloud, has given our customers some great choice. And it points to, again, the point that John made in terms of, our growth is really what we're focused on.

You know, I've said in the past that you know over half the number of customers that we have in the cloud with is operating a hybrid environment and we certainly see customers making deliberate choices where they're putting workload, whether they put it in the cloud or whether they put it on-prem. This is especially true for financial services organizations. But we meet customers where they want, and that gives us some opportunity that I think our competitors find it difficult to compete with.

Okay, thanks, Steve. And I think in your opening comments you cited anticipated incremental gains and retention as you go through the course of the year. What is driving that improvement? When should that become maybe more visible and at what level of retention is actually embedded in your 2% to 4% ARR growth outlook?

Yes, I think our retention story for the year is going pretty much as we expected. So we saw, as we've said in the past, continued improvement of our retention rates through FY '25. We saw improvements in the first half of 2026. And we see that continuing into the second half of 2026. Our customer success team is doing a great job. Q4 is our big quarter from a renewals perspective. And it's also the, it gives us the opportunity to expand the relationship we have with our customers in that Q4 period, as we do that at the point of renewal. So that's our opportunity that's sitting ahead of us.

We're confident in our outlook in the year. And I think it's all about disciplined execution to the point I made earlier. And I'm very proud of the Teradata team in terms of how they're executing.

That now concludes today's Q&A session. I will now turn the call back over to Steve McMillan for his final remarks.

Thank you, Operator, and thanks everyone today for joining us. We're really pleased with the first half of the year, and I think you can tell from my comments that we are super enthusiastic about our differentiated hybrid capabilities, and we absolutely remain confident in our ability to achieve our full year objectives. And so with that, I thank you all for joining.

This concludes today's conference call. You may now disconnect.

Good afternoon. My name is Trevor and I will be your conference operator today. At this time, I would like to welcome everyone to the Teradata 2026 First Quarter Earnings Call. [Operator Instructions]

I would like to hand the conference over to your host today, Chad Bennett, Senior Vice President of Investor Relations and Corporate Development. You may begin your conference, sir.

Good afternoon, and welcome to Teradata's First Quarter 2026 Earnings Call. Steve McMillan, Teradata's President and Chief Executive Officer, will lead our call today; followed by John Ederer, Teradata's Chief Financial Officer, who will discuss our financial results and outlook.

Our discussion today includes forecasts and other information that are considered forward-looking statements. While these statements reflect our current outlook, they are subject to a number of risks and uncertainties that could cause actual results to differ materially. These risk factors are described in today's earnings release and in our SEC filings.

Please note that Teradata intends to file the Form 10-Q for the quarter ended March 31, 2026, within the next few days. These forward-looking statements are made as of today, and we undertake no duty or obligation to update them.

On today's call, we will be discussing certain non-GAAP financial measures, which exclude such items as stock-based compensation expense and other special items described in our earnings release. We will also discuss other non-GAAP items such as free cash flow, adjusted free cash flow and constant currency comparisons. Unless stated otherwise, all numbers and results discussed on today's call are on a non-GAAP basis. A reconciliation of non-GAAP to GAAP measures is included in our earnings release, which is accessible on the Investor Relations page of our website at investor.teradata.com. A replay of this conference call will be available later today on our website.

And now I will turn the call over to Steve.

Thanks, Chad, and thanks to everyone for joining us today. I'm very pleased to report that Teradata is off to a strong start in 2026. With solid execution globally and our pivot to AI-led value, we outperformed against expectations in a number of key metrics.

Recurring revenue grew 12% as reported year-over-year. Total revenue grew 6% as reported year-over-year and non-GAAP earnings per share was $0.88, an increase of over 30% versus Q1 2025.

We continue to see solid retention in the quarter and customer interest in our hybrid capabilities drove a healthy growth rate in both total ARR and cloud ARR. We see that security-driven demand for sovereign AI is accelerating. For example, financial services and health care customers are increasingly concerned about shared infrastructure for AI workloads, and this is driving traction with our AI factory offer.

The most demanding regulatory workloads in the world run on Teradata. These are workloads that are least susceptible to disruption. The trend we see is AI moving closer to the data, not data moving to AI, and that plays directly to our architecture.

Every organization is grappling with the same challenge, putting AI to work for them and becoming truly autonomous enterprises. One thing is clear: to win with AI, organizations need to operate at speed and scale that was once unattainable. This is a core competence of Teradata. Our customers have governed data estates with years or even decades of data in their Teradata environment, including codified industry knowledge, entity models and business rules specific to financial services, health care, telecommunications and beyond. This is their institutional memory. The analytics and reporting workflows built on top of that data have been refined over decades. The value of those workflows vastly exceeds the cost of the platform. AI multiplies the value of that institutional knowledge and our platform is designed to execute at the speed AI requires. Our product organization is relentlessly focused on providing the strongest execution engine, reliable, high-performance and always on. Agents never sleep and mission-critical automation requires a platform that never slows down.

In 2026, we are executing against an aggressive product road map and are already taking new innovations to customers. We are seeing market interest in our MCP server. It's an on-ramp to enterprise AI, providing semantic access to the enterprise data in context that can activate real business outcomes. It eliminates friction through a natural language interface that leverages AI agents.

Together, the MCP server and our Agentic framework are designed to enable querying, analysis and management of data with full context.

To address the challenge organizations face of moving from isolated pilots to production-grade agents, we're making it easy for customers to build, deploy and manage AI agents with our agent stack announced earlier this year. This new comprehensive platform is designed to simplify the life cycle of enterprise AI agents. Our Teradata agent stack can help customers reduce the complexity of finding and integrating trusted data and applying enterprise knowledge and context. It can also aid in enforcing governance and maintaining compliance across hybrid environments.

In March, we introduced new capabilities to our enterprise vector store. We added multimodal data spanning text, images and audio, from our partnership with unstructured, and we added more identic features powered by LangChain integration. These announcements demonstrate another significant evolution in our enterprise AI infrastructure. Unifying structured and unstructured data within a single governed platform, capable of supporting billions of vectors and thousands of concurring queries from AI agents.

In April, we announced the availability of our enterprise-grade Teradata analyst agent on Microsoft Marketplace. This brings AI-assisted conversational analytics directly into customers' existing Azure environment. We also recently participated in the Google Distributed Cloud air-gapped center launch. Our platform runs natively on GDC, enabling organizations to operationalize Google's AI capabilities and our own analytics entirely within the air-gapped perimeter. No data leaves. No sovereignty is compromised. This capability is designed to be a real value for defense, intelligence and public sector organizations that require air-gapped sovereign AI. One of our differentiating capabilities is helping customers leverage and get value out of their environments, and that's even more important as they work to get business value from their AI investment.

Here's where our AI services change. Our AI services momentum is growing as we see customers looking to take advantage of the depth of experience that our forward deployed teams have gained from the successful early AI engagements we've executed. We recently issued a press release outlining how our AI services helped a sample of customers from the travel and transportation industry. Every enterprise has data, and that data is the basis of their institutional memory, yet few can turn that institutional memory into action compliantly across varied environments and efficiently at scale. Here, our expertise is driving successful engagements to help customers move from experimentation to production quickly. Third-party validation this quarter reinforces our leadership position. Nucleus Research ranked as a leader in the 2026 data science and machine learning platform technology value metrics, ahead of platforms that have built the reputation on data science.

Our hybrid capabilities are also getting noticed. Constellation Research named us to their 2026 short list for hybrid and multi-cloud analytical data platforms. We were 1 of only 3 vendors selected from a field of more than 3 dozen, reflecting a breadth that competitors structurally cannot match. More broadly, ISG recognized us as exemplary their highest designation across 7 categories and their 2026 AI and data platforms buyers guides. That breadth reflects that we are meeting enterprises wherever they are in their AI journey. This recognition reflects something that takes decades to build the trust of the world's largest enterprises running workloads that simply cannot fail.

Now I'll walk through a few examples of the outcomes we are already helping customers achieve. One of the largest pan-European banks renewed and expanded its Teradata relationship. The goal was to address business critical workloads like financial reporting and regulatory data model convergence, underscoring Teradata's crucial role in the bank's operations. It also launched a customer journey transformation leveraging Teradata AI capabilities, including augmented agent workflows, enterprise LLM integration and AI Studio. This positions Teradata as its emerging enterprise AI platform. The engagement reflects how large financial institutions increasingly rely on Teradata as a long-term strategic platform for both regulated analytics and AI.

A leading global retailer based in EMEA was a win back for us, selecting our platform to replace its existing on-prem platform. After evaluating competitors, the customer concluded that Teradata delivered the best price performance for its analytic workloads. This reflects the durability of our value proposition for mission-critical retail analytics at scale.

A leading Latin American financial institution added our AI services to encompass its enterprise AI operations. The customer recognizes they'll now get continuous oversight, governance transparency and life cycle management of AI models and Agentic applications in a regulated environment. The engagement positions Teradata is this bank's long-term operational partner across the full AI life cycle.

A large government agency in India committed to Teradata as it enters a new phase of digital transformation. We help unify structured and unstructured data at massive scale to deliver real-time comprehensive profiles through its online portal.

Our native object store capability was chosen to simultaneously bridge structured block storage and unstructured object storage at scale, a requirement no competing platform could meet. This example underscores our differentiated position and mission-critical, high concurrency, government and analytics environment. Market data reinforces what we're seeing and hearing directly from customers and a third-party research survey of 1,000 senior technology and data leaders sponsored by Teradata every single organization, 100% is actively pursuing Agentic AI, yet only 17% have deployed it beyond pilots and 99% have already had infrastructure scaling challenges and the attempt to move from pilot to production.

The barriers aren't abstract, performance at scale, cost predictability, always-on agent demands, running new workloads, along with existing production systems and deploying across cloud, on-premises and regulated environments. Enterprises are not facing one infrastructure problem; they are facing all of them all at once. That gap between ambition and execution is something we believe we're uniquely positioned to solve.

On Thursday, we'll be announcing a significant and broad set of innovations that address these challenges, helping our customers move into the next phase of enterprise intelligence while bringing autonomous AI and knowledge to organizations globally. We invite you to join our live stream on May 7 at 10:30 a.m. Eastern Time. You can join directly from our teradata.com website.

We are confident that our new unified platform and integrated AI workspace will help enterprises rapidly move into production AI. We're quite excited about what's coming on Thursday and hope you can attend.

As I pass the call to John, I'll reinforce that we are very pleased with our Q1 results. Even with the current global uncertainties, our business model is robust, demand continues for our capabilities, and we see tremendous opportunity to create incremental value for our shareholders. We have sales momentum, customer interest and an engaged partner ecosystem, and we have a great start to our product innovation pipeline and more coming very soon. We remain focused on driving execution, increasing our differentiation and delivering products and services that lead customers to rapidly deploy Agentic AI into production.

Now John, over to you.

Thank you, Steve, and good afternoon, everyone. We are expecting Q1 to be a strong start to the year, and it proved to be even better than we anticipated with total revenue, recurring revenue and non-GAAP earnings per share all exceeding the top end of our guidance ranges for the quarter.

Additionally, we got off to a fast start with strong free cash flow in the first quarter. The revenue upside was driven primarily by recurring revenue and more specifically, the upfront portion of our on-premise subscription term license business, reflecting continued interest in our hybrid platform.

Non-GAAP operating margin also improved significantly by more than 500 basis points year-over-year driven by higher recurring revenue and a continued focus on operating leverage to deliver profitable growth.

During Q1, Teradata entered into a settlement agreement with SAP. From the settlement, Teradata received a gross payment of $480 million in late March. After accounting for legal fees and other expenses related to the SAP litigation and resulting settlement, the pretax net amount was $359 million, which benefited both operations and free cash flow.

On an after-tax net basis, this is expected to provide a $302 million benefit to free cash flow in FY '26. The settlement also positively impacted GAAP diluted earnings per share by $2.90. Tax payments related to the settlement totaling $57 million are expected to be paid from Q2 through Q4 2026, with approximately half expected to be paid in Q2 and the remaining half expected to be split between Q3 and Q4.

For the remainder of the year, we will also refer to adjusted free cash flow to provide a normalized free cash flow measure for the business.

Adjusted free cash flow will reflect adjustments for the impact from the SAP settlement by excluding gross proceeds, legal and other expenses and taxes specific to the settlement.

In terms of our detailed financial results for the first quarter, total ARR grew 3% as reported and 2% in constant currency while cloud ARR grew 13% as reported and 12% in constant currency. First quarter total revenue was $444 million, up 6% year-over-year as reported and 4% in constant currency which was 3 points above the high end of our outlook due to higher recurring revenue. First quarter recurring revenue was $400 million, up 12% year-over-year as reported and 9% in constant currency, which was 4 points above the high end of our outlook. The outperformance was primarily due to higher upfront revenue from term license subscriptions, which contributed 5 points to the year-over-year growth rate. First quarter consulting services revenue was $43 million, down 14% year-over-year as reported and 15% in constant currency.

Looking at profitability and cash flow, please note that I will be referencing non-GAAP numbers for expenses and margins, and a full reconciliation to GAAP results is provided in our press release. For the first quarter, total gross margin was 63.7%, which was up 340 basis points year-over-year, driven by a higher mix of recurring revenue and improvement in consulting gross margin.

Recurring revenue gross margin was 70%, which was flat with Q1 last year, but up sequentially from Q4 FY '25. The sequential improvement was driven by the incremental upfront recurring revenue, but we are also continuing to make progress improving our cloud gross margins.

In Q2, we expect lower upfront revenue to be a headwind to our recurring gross margin.

Consulting Services gross margin was 4.7%. This was down from a recent high point in Q4 FY '25, but it did improve by over 600 basis points on a year-over-year basis.

Operating margin improved significantly on a year-over-year basis, coming in at 27.3% versus 21.8% in Q1 last year. The margin expansion was driven from recurring revenue outperformance and favorable gross margin benefit from upfront revenue.

For 2026, we continue to anticipate approximately 100 basis points of operating margin expansion. Non-GAAP diluted earnings per share were $0.88, exceeding the top end of our outlook range by $0.09. The outperformance was largely driven by higher recurring revenue and total gross margin. We generated $390 million of free cash flow in the first quarter. This amount includes a $359 million benefit due to the pretax net proceeds from the SAP settlement.

On an adjusted free cash flow basis, we generated $31 million. We now have $816 million of cash and cash equivalents at the end of Q1, up from $368 million in the prior year period. This also returns the company to a positive net cash position of $269 million for the first time since Q4 FY '21.

Finally, we continue to return value to shareholders, repurchasing approximately $34 million or about 1.2 million shares in the first quarter. We continue to target to use 50% of our adjusted free cash flow for share repurchases, which excludes the benefit from the SAP settlement.

Before turning to our financial outlook, I'd like to provide some additional context. Regarding the use of the net proceeds from the SAP settlement, we plan to strengthen our balance sheet by deleveraging. This will maximize our optionality to make future strategic investments in AI as well as continuing our stock buyback program.

On total ARR, we continue to expect our typical seasonality with total ARR stabilizing in Q2 and expanding over the course of the year, showing modest sequential dollar growth from Q1 to Q2. For recurring revenue, we expect upfront recurring revenue and currency to be headwinds to the growth rate in Q2.

On a sequential basis from Q1 to Q2, we anticipate over a 10-point impact to the recurring revenue growth rate due to upfront revenue. And based on the foreign exchange rates at the end of March, currency is anticipated to be approximately a 3-point headwind to recurring revenue growth.

Now turning to our annual outlook for 2026. We reaffirm our ranges for total ARR, total revenue, recurring revenue and non-GAAP earnings per share. For the non-GAAP earnings per share range of $2.55 to $2.65, we anticipate to be at the higher end of that range. For adjusted free cash flow, given the strength of Q1, we are increasing our outlook and now anticipate to be in the range of $320 million to $340 million. And to reiterate, our adjusted free cash flow range excludes the after-tax benefit from the SAP settlement of $302 million.

For the second quarter of 2026, recurring revenue is expected to be in the range of minus 2% to flat year-over-year. Total revenue is expected to be in the range of minus 4% to minus 2% year-over-year and non-GAAP diluted earnings per share is expected to be in the range of $0.53 to $0.57.

In terms of some other modeling assumptions, for the second quarter, we expect the non-GAAP tax rate to be approximately 24% and the weighted average shares outstanding to be 96.3 million. Using the currency rates at the end of March 2026, we now expect minimal impact to the full year revenue growth rate. Also, we now anticipate FY '26 other expenses to be approximately $22 million.

In summary, we were very pleased with the start of the year and believe that we are tracking well towards our full year targets. We significantly improved our balance sheet and generated strong free cash flow, and we're continuing to pursue our profitable growth strategy by finding margin improvement opportunities across the business, while at the same time, preserving investments in R&D to support future growth.

Thank you all very much for your time today. Now let's open up the call for questions.

[Operator Instructions] Your first question comes from Radi Sultan with UBS.

Awesome. First, for Steve, just now that the business is skewing more heavily towards expansions versus cloud migrations, could you just walk through how you position the business, both product and go-to-market to reflect that? And maybe just how do you expect that to impact overall sales productivity throughout 2026?

Yes. Thanks for the question. We're seeing really strong interest in terms of the AI capabilities that we've been launching last year and also the AI capabilities that we're going to talk a little bit more about at our product launch on Thursday this week on May 7. And that's certainly driving expansion for us. I think last year, we saw the trend in terms of a headlong rush to the cloud really starting to decline as an indicator in the market for us. But what we have started to see is a real interest in expansion. We focused our sales force on total ARR growth, and they can get that growth from either on-prem or from the cloud. Our strength in a hybrid environment is a real differentiator for us and is providing a growth lever when we combine that with some of our AI capabilities and the ability to operate and execute AI workloads on-premise. And that's really some of the examples in the prepared remarks were pointing to. As we execute against that, we see sales productivity continuing to improve as well as the sales teams have more and more things to sell and an increased value proposition to take to our customers. Thanks for the question.

Awesome. Maybe just a follow-up for John. I know it's early on with the AI services and the forward deployed engineering practice. Just how do you think about the P&L impact from both top line and margin perspective? And both the near and long term from that growing services practice on the AI side?

Yes, sure. Thanks for the question. In terms of the AI services and the P&L impact for '26, I would say it's pretty minimal. This is a new offering for us and something that we're ramping up this year. Longer term, I could see it contributing more to the P&L, but still ultimately, it's going to be a service component. It's going to be complementary to what we're trying to do on the software side. I would say that I see it as a critical connection point though, and it helps us further develop our proof of concepts that we've been doing with customers, get them into production and then ultimately to drive AI-related ARR.

Your next question comes from Yitchuin Wong with Citibank.

Great to hear the team outperformed the quarter across a variety of crosswinds that we saw over the past couple of months. Historically, this kind of uncertainty like elongates enterprise IT cycle as we heard from a couple of the larger techs that reported last week. However, the enthusiasm that we are seeing with Agentic AI and with your recent GA vector product agent, tons of new AI product announcement with autonomous event on Thursday, excited for that. Are you finding this strategic urgency to deploy AI capability is like overriding the localized macro caution and what are you seeing around those crosswinds that on your deal cycle in the quarter?

Yes. Thanks for the question, YC. I think AI is in every strategic conversation that I and my team have with customers. And we can see that with some meaningful data points. If we look at our pipeline, we see a growing proportion of our pipeline today as the AI attached to it. And so that reflects that every strategic conversation has that AI or analytics edge to it.

Second thing is, as we look at customers, they're having a real challenge deploying AI and production and they see the Teradata platform, along with the announcements we've already made and the upcoming road map that we're going to deliver as a platform that can deliver AI into production for them. And then third, as John was just talking about, even although we are always going to be a technology company primarily, we do have a capability in our services organization and the set of AI services that we have launched is enabling customers to move from those pilots into production. We're not going to pivot the company towards services. It will just be a part of enabling our technology value proposition in the marketplace. But we're certainly seeing that pivot. Everybody wants to get the business outcomes from AI, and they're absolutely focused on doing that as quickly as possible, and we intend to capitalize on that.

That's good to hear. I have a follow-up for John. Like the quarter sounded like hybrid continue to be like a bigger driver, especially with sovereign AI set of things that could be driving higher demand for hardware and we have a refresh cycle upcoming in 2-ish. I just want to touch on that. In Q4, we talked about you'll be able to absorb the memory pricing impact given the long-dated contract. Memory prices have continued to ramp significantly over the last few months. Could you walk us through any incremental impact that you are expecting, especially going into next year as well? Are you seeing customers respond to this memory crunch differently?

Yes. Thanks for the question. I would say that this is definitely a dynamic that we are watching very closely and evaluating near daily, and it's becoming quite pervasive in the marketplace. I would say that for us, from a financial standpoint, it's probably more of an FY '27 challenge and opportunity as opposed to FY '26. We'll talk a little bit more later this week about some of the new products that are coming out, including the hardware refresh. Those will become available this year, but we would really expect more financial impact to occur in FY '27.

Now having said all that, from a pricing standpoint, that's the piece that we're looking the closest at. And the thing that we'll focus on is to make sure that we protect ourselves from a margin standpoint as we go to market with that.

Your next question comes from Erik Woodring with Morgan Stanley.

This is Ralph here on behalf of Erik. I just wanted to ask, are we at the start of an improving recurring revenue gross margin trajectory given you just posted 70% for the first time in a year and the strongest quarter-over-quarter recurring revenue gross margin improvement in years?

Yes. Thanks for your question. I'll start and then I'll hand over to John. Certainly, from an ARR perspective, we returned the company to ARR growth in 2025 and we set the expectation that we will continue to accelerate that percentage of ARR growth into 2026. And we see good path and opportunity for that to continue based both on the expansions that we're generating inside our customer base, but also the incredible interest that we've gotten using the platform for AI type workloads.

And then from an operating margin perspective, we have a number of initiatives in the business that we're looking at to improve operating margins as we continue forward. John?

Yes. Thanks for the question. So gross margins are a little complicated on the recurring side for us. You've got different dynamics at play with both the cloud side of our business as well as the on-prem. In Q1, we did see a nice spike up in gross margin, at least relative to the last couple of quarters at 70% for the recurring. And that was largely driven by the upfront revenue that we also saw in Q1. And so this was a factor of revenue recognition and ASC 606 and getting more upfront revenue related to the on-premise piece of the business. So that had a spike in margins for this quarter. As we look out to the remainder of the year, we would expect them to be a little bit more consistent with recent quarters that we saw at the end of FY '25.

Now underneath that, we are seeing improvement in our cloud gross margin, and that's a critical factor for us. I know we don't disclose that publicly, but we have been making good, steady progress on that, and we saw some nice improvement in Q1 on cloud gross margins as well.

Great. And if I could just ask a follow-up. Could you help us better understand demand and sales linearity in the quarter? And maybe how the Middle East conflict is impacting sales cycles versus what you're hearing at the micro level as it relates to demand for data prep, unstructured data, et cetera. Just any sense of maybe how these couple of factors are impacting your business?

Yes. I think we're still seeing a very solid demand environment. The challenges in the Middle East haven't substantially impacted our business at all really. And the demand patterns that we're seeing really reinforce the value that organizations want to get out of the investments they're making. As I mentioned in the prepared remarks, the survey that we did showed that despite 100% of the customers that we spoke to in that survey wanting to deploy AI and get the benefit from AI and the vast majority, 99% are having a problem getting from pilot to production. So that really is altering the conversation that we're having with customers as they look at Teradata as a platform and a knowledge platform that can deliver the Agentic AI workloads that they need. So that's resulting in an environment where we can deliver on the expansions that we need to deliver to make our outlooks and actually take advantage of the market opportunity that's in front of us.

Your next question comes from Matt Hedberg with RBC Capital Markets.

Steve, as a follow-up to that earlier question, it really does seem like there's -- other question, there's a lot of momentum in AI. And I think we'll hear more about that later this week. The MCP server interest is high. I guess I'm curious, is there a way for you to determine what the actual ARR benefit you're seeing from some of these increases in AI workloads within your base?

Yes. I think what we're seeing is that helping those customers cross the chasm from pilot to production and it's certainly driving usage and capacity usage of the Teradata platform. One of the benefits that we've got in terms of the Teradata platform is Agentic AI workloads with always-on agents are driving a tremendous volume of queries, they're driving a huge concurrency of queries and complexity of queries into the respective data platforms, that's Teradata's sweet spot in terms of how we execute and the technology that we've got. And I think we're seeing customers really take advantage of that. And there's a little bit of a shift from standard BI workloads towards more of Agentic type workloads, but we also see the opportunity opening up to serve both in the cloud and on-premise, those Agentic AI workloads. And we see it as an opportunity for us to drive incremental ARR growth, especially with the new products that we'll be announcing on Thursday this week.

That's great. And then maybe for John, it was great to hear that retention was solid in the quarter. I guess I'm curious, is there anything we should keep in mind regarding large renewals for the balance of this year?

No, I don't think there's anything particular on that front. In general, we're seeing improved retention rates. We actually started to see that in fiscal '25. And we're carrying that through here in '26 and started off on a good note in Q1. So I think in general, we've done a nice job of getting closer to the customers, understanding that process, et cetera, around key renewals and making sure that we're in a good position to do that.

Your next question comes from Raimo Lenschow with Barclays.

This is [indiscernible] for Raimo. During the prepared remarks, you talked about the strong start to the year. You definitely have some tailwinds, security-driven demand accelerating sovereign AI. AI interest seems to be healthy. And I completely understand we're operating in a very dynamic environment. But could you help us understand the puts and takes and maybe any balancing factors that motivated to maintain full year ARR guidance?

Well, I think that if you look at the total ARR number for Q1 and on a reported basis 3%, that's right in line with what we had guided for the full year of 2% to 4%. So I guess I view Q1 as being very consistent with our outlook for the year. And then in general, we're seeing decent demand across the product lines and optimistic about some of the things that we can -- that we'll start to introduce later this week.

Now those won't have a material impact on FY '26. But in general, we're seeing better demand.

Understood. Congrats on the solid quarter.

Thanks.

Your next question comes from Patrick Walravens with Citizens.

Great. Could I start by asking you're commenting about the trouble that clients are getting from pilot to production. Can you drill down on that a little bit? Specifically, what gets in the way of moving to production?

Yes. Pat, I think it goes to the characteristics of the workload and the data platforms that organizations are using. I've used the term before that our competitors solve complexity with incremental compute. We solve complexity with great software. And that enables us to address some of these challenges that our customers are having in terms of spiraling compute costs for their data platform. They have regulatory challenges in terms of making sure that data is well governed. And across all of these different types of data problems we've been solving them for customers for years as they built out some of the most comprehensive enterprise data warehouses and then making sure that those solutions have the right context. And context is built on industry knowledge, industry data models, the codification of business rules. And we've helped customers and organizations span those challenges for years now. And it's just another reinvention of that from an AI perspective to ensure that these AI agents have the right context to give the reliable answers in a production context to really solve business problems today. And that's what the whole new series of offerings and capabilities over the past few months and including what we're planning to launch over the next couple of weeks really brings together in terms of delivering that context to our customer organizations.

Great. And can I ask Steve -- or maybe, John, I don't know who wants to pitch in on this. So other than the financial aspect of the SAP settlement, I mean, can you remind us what was this whole thing about? And is there any fundamental benefit in having resolved this dispute?

Look, I think, Pat, it's always good to clear the deck from a legal perspective and make sure that we're looking forward to what we're actually going to do strategically with that cash. Certainly is on the balance sheet now, and it gives us a lot of strategic optionality as we move forward in terms of how we deploy that. Certainly, it's solidified the balance sheet, as John pointed to, but it gives us strategic options moving forward, and we certainly see it as a vehicle that's going to enable us to increase our return to shareholders as we move forward. So we're pretty excited about it and glad to put it behind us.

Your next question comes from Derrick Wood with TD Cowen.

This is Jared on for Derrick. First, could you comment on domestic and international revenue performance in the quarter? And maybe take apart some of the drivers for each of those markets.

Yes. So in general, if I look back over the last few years, we have seen some differences in domestic versus international. And if you go back a couple of years, the impact of some of the churn was really more felt in the United States as opposed to the international markets. We've also seen some improving trends from a -- even from a new logo standpoint in some of the international markets. And so I think that, that is one area where the hybrid story resonates even more so than perhaps in the United States.

Awesome. Appreciate that color. And off of that regulated industry commentary, could you just talk to some of the different trends you've been seeing in your regulated base versus nonregulated base?

Yes. I think -- and it reflects as well in some of that international workloads that we've been winning. Certainly, governments, financial services organizations, health care highly regulated. We see that as a great competitive moat for us. We are uniquely differentiated to enable those organizations to run Agentic AI workloads against that data. And they can do it in the cloud or they can do it from an on-premise perspective or in a hybrid environment. More than 50% of our customers in the cloud also operate on-prem Teradata systems. And so we've been able to span data across those environments, not move data into different types of solutions as given those regulatory workloads some real benefit in terms of how they can leverage AI and Agentic AI against those data sets.

That concludes today's Q&A session. I will now turn the call back over to Steve McMillan for his final remarks.

Thank you very much, operator. Thanks for joining us today. We're really proud of our strong start to the year and the value we're creating for shareholders. We've got the technology, the expertise and a really strong partner ecosystem. And we believe we're bringing real differentiation to the market with our autonomous knowledge platform. We intend to keep that momentum up as we help organizations build for the Agentic future, moving decisively from AI ambition to sustained business impact. We look forward to updating you again next quarter. Thanks.

That concludes today's conference call. You may now disconnect.

Okay. Cool. Why don't we get started, guys. Welcome to day 2 afternoon of day 2 of the Flagship TMT Conference. My name is Erik Woodring. I lead Morgan Stanley's hardware coverage here. I am delighted to be joined by John Ederer, CFO of Teradata; Sumeet Arora, Teradata's Chief Product Officer. Both of you guys, thank you and welcome to the conference.

Thanks for having us.

Before we begin, let me point everyone to the Morgan Stanley research disclosure website at www.morganstanley.com/researchdisclosures. If you have any questions, please reach out to your Morgan Stanley sales representative. So with that out of the way, this is the first time that I've been able to host both of you at the TMT conference both relatively new to the role that you're sitting in right now.

I'd love just to start the conversation, just quick background, maybe 1 or 2 priorities for each of you as you think about the changes you want to kind of enact in your relative seats, and then we'll go from there.

Sure. Well, I'll kick things off, even though Sumeet predated me by about 30 days. But yes, I joined last May and very excited to be on board. I've been in the software industry for 20-plus years. And before that, I actually started in your chair, I was a research analyst for about a decade before making the jump over. And so spent a lot of time in enterprise software, most recently with a company called Model N that was publicly traded and then joined up with Teradata last spring. As I came onboard, we, as a company, had obviously gone through, I would call it a challenging 2024. And so a big priority for us in '25 was really just kind of getting the business back on track. And there were some things that we felt were really critical. One was getting total ARR back to positive territory. The second was continuing to improve on our operating margin.

Third was really starting to demonstrate durable free cash flow generation. And I think fourth and perhaps maybe the most important was just demonstrating some consistency on a quarterly basis as we went through the year. So I think we were able to do all of that, and that was probably goal #1 coming out of the gates.

Yes. I'm Sumeet Arora, and I'm the Chief Product Officer at Teradata, joined roughly around the same time as John. I have 30-plus years in tech industry have spanned domains. I did Cisco for 20-plus years and built some of the largest routing systems that operate the Internet today. And then I have spent more than spent 5 years at a much, much smaller company, focused on Agentic analytics, natural language analytics way before ChatGPT became popular. And in the last 10 months, I've been at Teradata. My priority is, 1 or 2 priorities.

I think first is to make sure we continue to earn the trust of our customers through our product. That's most foremost Second is really, really focusing on innovation, both foundationally as well as, in some ways, almost like a startup, operate like a start-up in terms of the velocity, in terms of discovering product market fit for some of the newer things that are happening. So it's kind of almost too faceted there, and those are my priorities.

Okay. Great. Now that's a great way to start the conversation. And Sumeet, not everybody gets exposure to you. And so I want to take advantage of this and start with you. And maybe, again, started at a high level, just the demand landscape as we look at Teradata Solutions, especially how they could be changing with generative AI risk around -- risk or opportunities around Agentic AI. What are the solutions that you see right now kind of specifically gaining traction with customers at Teradata?

Yes. I think the landscape I'll just say that the landscape above data platforms like Teradata is shifting. And from traditional applications to reporting, which are still there, but there is absolutely a motion towards Agentic AI, experimentation with that, actual stuff. And I can see that just based on the demand for MCP servers and certain types of queries that show up, right? And I can see that shifting right now. So that's kind of part 1 of the story.

The part 2 of the story is the demand for context. Everybody is talking about that. But what is context? Context is the ability to give a world view to agents so that they can be more enterprise-grade explainable, high accuracy. And Teradata platforms like us have the knowledge of the data, the metadata, also the knowledge of the industries that we have served for more than 4 decades, and our ability to combine these to deliver the right context for the use case for the agent so that agents are useful, actually useful, deliver real ROI is the second piece that I'm seeing in my conversations.

And the third piece is people want AI to be co-located with the gravity of data. There is no AI without knowledge, without enterprise knowledge, enterprise data. And we are known to be that trusted repository. And people want to locate AI where that data is instead of moving the data to where AI is. And that is an amazing opportunity. I see that in all my conversations. And I'll just say that underlying all of these 3 that I outlined is the demand for moving fast with innovation, but minimizing risk. Moving faster with innovation, but like having cost efficiency and cost economics, moving fast with innovation, but really having the governance and the trust. And I think Teradata is really well positioned to deliver on those.

And if I could just tack on to that quickly. If you look back at our business over the last 3 to 4, even 5 years, we were very focused on building the cloud side of our business, and I think we demonstrated a very strong ability to do that. But the emphasis has shifted and whereas even just a few years ago, it was still very much about migrations and getting to the cloud just for the sake of getting to the cloud now that emphasis has really shifted to some of the things that Sumeet was just describing from an AI standpoint, and there's an eagerness to get going on those investments and using the data where it sits today, whether that's in the cloud or on-premise.

Okay. No, good. And we'll get into that kind of Teradata 3.0, so to speak. Before we -- I want to touch on competitive landscape. Before we get there, I'd be remiss if I didn't kind of let you share your thoughts on AI disruption, right? Obviously, kind of a key topic here, a key topic in the market. Teradata should play an important role in enabling in enabling AI. There's broad risk or concern that new LLM tools can kind of disrupt existing software platform. So just maybe lay out how you think about the risk of AI disruption or the opportunity with AI disruption just as it relates to Teradata.

Absolutely. From a Teradata vantage point, if you look at the new enterprise tech stack that is emerging, there is essentially a knowledge fabric, which is the data, the processes, the documents, the important videos and maybe what's in the heads of people, that's the knowledge fabric. That's the true effect of an enterprise. Then there is a layer that essentially uses that to deliver governed context, trusted context. Then there is the agent flare, which is the layer that is kind of approaching or trying to replace the SaaS layer, right? And then there is the interface with the stack itself, which is going outcome centric.

So if you look at that stack and then you look at Teradata, we are absolutely well positioned to play the role of the knowledge fabric and being part of that, both with our structured data capabilities and our absolutely first-class vector capabilities because we can understand unstructured really well. So we have a big part of the knowledge fabric. And I think as long as I and my team and Teradata, we make sure that this is usable by agents, which is the layer above, trusted context, which we are absolutely invested in at Teradata delivering that to agents. And people can build agents in Teradata now. They can deploy agents close to literally in the Teradata environment. They can govern them or if needed, they can build agents elsewhere, but they can come to us through the MCP servers.

So we offer both because we want that Agentic layer to have the flexibility to run on-prem, like John was saying, run in the cloud, run in the cloud and safely access on-prem data. So we are really enabling the Agentic layer as well, both in terms of supporting other parties, but also first-party agents inside of Teradata. So we see us playing a huge role in at least 3 layers of the stack all the way delivering on trust and governance as the primary property.

Okay. And let's touch on kind of the competitive landscape in Teradata's differentiation. 2024 was a year of higher-than-average erosion. You've been able to bring that under control. John, you talked about kind of executing in 2025. I know your focus is on hybrid workloads also continue to move to the cloud. So I'm just kind of setting the stage for -- if we think about these large-scale workloads where Teradata excels in price and performance, is that the impenetrable competitive moat that you believe Teradata has or across kind of product pricing performance, et cetera? Where is that impenetrable moat?

Maybe I'll take a shot at it. I think the first piece is our ability to give choice to our customers. They have the choice to leverage -- leverage the same technology stack on-prem or in the cloud, which is increasingly important -- increasingly important because the deployment type dictates economics and security. The second piece is the choice we provide in terms of storage options. And the reason that's important is Teradata can do both block store and object store well. The advantage of the block store tightly coupled architecture is low latency and high concurrency, which is very amenable to operational workloads increasingly being delivered through agents. The same engine is built for the always-on economy. Remember, what my customers tell me is Teradata is the best when the workload is always on or when the workloads are mixed because we have this amazing workload management technique.

Guess what? The cloud story was built with human usage patterns in mind. We go to bed at night, we take time off at weekends -- things shrink in the cloud, and that delivers economics. But now we are entering an agenda -- a time when agents don't sleep, they're rigorous. They're 25x more rigorous in terms of the amount of data they access. So in that era that always on economy, we are the price performance option. So that's kind of one choice we offer. We also offer the elastic compute option, which is amenable for things that come and go, things that are experimental. So they get a choice of 2 types of compute, again, price performance, types of storage, types of deployment environments. So we -- I call it as the best engine, the best context. Remember, we spoke about context earlier in my conversation, our understanding of industries like we understand financial services. We understand telcos. We understand airlines.

We can bring that knowledge and map the crazy taxonomy of data that exists underlying to give a world view to agents that agents can be much more enterprise grade. So best context, best engine. We've built -- I think we have already spoken about this, so I can say it, which is we're building this AI studio capability, which is right next to our data, our knowledge and that allows people to really bring their AI outcomes right there next to the data without data having to move. And that's a beautiful option. So these are some of our differentiations that actually resonate with my customers.

John, you were just going to say something.

No. Okay.

Okay. Great. And Sumeet, maybe just add on to that. When we talk about the innovation coming out of Teradata, these agenetic architectures and protocols, that are very rapidly emerging. What's the criticality of the role they play as we think about Teradata innovation over not just like 2026, but as you're looking out and you're thinking about how Teradata needs to remain the most relevant for their customers or the trusted choice. Talk to us about that a little bit.

Yes, that's a great question. Look, one of the things that innovators forget is the value of distribution. Right? It's important to build great technology. But if it's not easily consumable and it's not distributed well, then you don't get -- derive the value and you're not able to invest in it. So if I look at the innovation we are unpacking this year, whether it's a complete transformation of our hardware, complete like a huge investment in AI, a huge enablement of Agentic workloads. It is also what we are trying to do is trying to make it easy to consume, easy to use and really focusing on some building blocks that allow me to play the market to continuously discover product market fit because I think as companies in this era of AI, we have to almost behave like start-ups every day like days because things just change so rapidly, Erik, like Anthropic drop something and like whole world is like reacting to it, right?

So in this era, you want to have the building blocks in place so you can play the market based on what the emergent needs are. And I think I would characterize my -- our set of innovations this year as also the building block for that. And I think you're going to see us do a lot of partnerships in big ways this year as well, which is another way to drive distribution and leverage.

Okay. Awesome. Going back to the kind of Teradata 1.0, 2.0, 3.0. I've been privy to see all evolutions of that. So IntelliFlex Box is on-prem, Two, we're going cloud first. Now it's kind of the hybrid approach. This could be for you, John or Sumeet, but just talk to us about why this is the approach that gives you kind of that long-lasting competitive differentiation. What sets you up for the most long-term success?

Do you want to talk about it from a product standpoint?

Absolutely. So look, one of the things I get , which is the most pleasure for -- a part of my job is the opportunity to meet customers and prospects around the globe. And there is increasing value attached to the ability to deliver innovation wherever it's needed. It could be an on-prem appliance. It could be a private data center. It could be a sovereign cloud, a local cloud. It could be the public cloud and the Teradata tech stack ships in all those locations. Not only does it shift to all those locations, we ship the same stack, the same set of innovations. The same AI that you can do in public cloud, you can do it in all those areas, on-prem, appliance, wherever it is, you can do it anywhere with Teradata.

And it's not like one lags the other by years. No. Within a few weeks, everything is available everywhere. So that is the velocity at which we are moving. We're making sure that the best is available in all these locations. Customers love that. And not only do we ship these and deploy these in different locations, they can talk to each other. So you have real -- you can mitigate risk, you can put the right economics, you can deliver based on privacy and security requirements. And I think we're really, really well positioned. And that is the conversation that happens around the world. So I feel very, very strongly about that.

And maybe, John, this can be for you as a jump-off point from that is, so what does that mean when we think about the underlying drivers of growth when it comes to new logos versus limiting erosion versus migrations versus expansions? When we talk to this more sustainable ARR growth, where is that coming from if we kind of dissect it across those different avenues?

Yes. I mean you kind of touched on every element there. But I would say what's different in terms of the go-forward view is probably the relative weighting of those things. And so I alluded to this a few minutes ago, if you were to go back a year or 2, there was a heavy emphasis on migration activity, right? And that was used as one, a point to get customers to the cloud, but two, a catalyst to engage with the customer again and upsell and cross-sell and trying to expand the relationship overall. What we're seeing now is really a move towards the adoption of AI, and that is a primary driver for us. And so that drives the increased workloads and that's what fuels a lot of the expansion activity for Teradata.

And so I'd say, going forward, what you would see from us is a much more traditional land-and-expand type of a model, where yes, we will continue to focus on new logos. We'll also look to expand existing customer relationships.

Okay. Perfect. Awesome. Now maybe Sumeet, last question before I turn it over to John and kind of turn this into numbers is just going back to kind of the product set. We've talked about MCP server. You've talked about the kind of NVIDIA partnership that is relatively new. What are you most excited about from a new introduction standpoint, what does this mean for the pace of innovation that's going to come out of Teradata over the next 1 to 3 years? You talked about, I think, it was 150 AI and Agentic engagements in 4Q. Bring that all together for like where is Sumeet getting excited about where I need to push that product to, so to speak.

Yes. I think, look, this is a year where we are bringing to life through execution, raw execution, our vision of an autonomous AI and knowledge platform. We are moving the addressable data for Teradata from structured data to also making sure that we are able to handle all sorts of unstructured information inside the enterprise, whether it's videos, images, documents, whatever it is that you need for AI. We are evolving to the trusted knowledge platform. So that's kind of part 1.

The second piece is we're delivering AI outcomes. Everything starts with ROI with measurable outcomes, work backwards from there. We're delivering AI outcomes right where the knowledge gravity is where data gravity is and in different environments like we discussed. And to support that evolution to the autonomous enterprise, we're delivering our own stack to be fully Agentic and autonomous. So that's kind of the vision and strategy. What am I most excited about? I think this is a big year for us. I think if I look out the next few months up until summer and so on. We have a full transformation of our on-prem platform underway. We'll transform on-prem to an autonomous AI and knowledge platform. We'll enable people's AI factories with knowledge and help them deliver outcomes, right? So that's a big deal.

In terms of cloud, it's going to be an exciting year for us where we combine the low latency, high concurrency, always on system with a femoral elastic compute that delivers both the ability to innovate fast but also deliver price performance for stuff that needs to be always on and proper and structured. I'm very excited about that prospect, both in the cloud and on-prem. So that's the story.

And I'm super excited about our AI studio launch, which is going to bring together -- I know we didn't dwell on it, but I'll take 30 seconds and finish this off, which is the AI studio brings the ability to do entire agent life cycle, build, deploy, govern agents with the MCP server allows the ability to do all sorts of analytics with 150-plus in database analytics functions that we have, allows the ability to run applications that are oriented at specific use cases and outcomes. And last but not least, allows for scalable Python compute to leverage both normal CPU compute as well as accelerated GPU computes in both on-prem and cloud environments. My customers are loving this vision and strategy and the execution, and I hope to bring that to life this year.

Cool, I'll maybe transition more to John now and find out how we're turning that into numbers, so to speak, on the financial statements. So John, as someone that's covered for Teradata for a decade. It's exciting to see stabilization in top line, a modest acceleration in the business, 2% to 4% ARR growth, flat to 2% recurring revenue growth. We've kind of talked through how you expect to get there, so to speak, with a lot -- with expansions kind of primarily the driver. Talk to us about how you see kind of upside and downside risks to that. That could be macro related, that could be company and product related, just up and downside risk.

Yes. I mean, I think that well, look, prior to this week, I would say more focused inwardly on our own execution. Obviously, there's a lot going on in the world today, and that's a very large wildcard for all of us. But I think really, when we look at how we're operating, how we operated through '25 and then how we set ourselves up for '26, it really is about execution for us. And so we did get back to positive territory on total ARR growth last year. That was an important milestone, especially relative to '24 to get us back on track and to start to stabilize the business.

We did launch some products last year. We've got a lot more slated for this year. And we did start to do some things from a go-to-market standpoint to hit the ground running in '26. We talked about on our earnings call, the 150 proof of concepts that we did on the AI side. So we have our forward-deployed engineers out there working very closely with customers, developing use cases, creating these POCs. We've added a services team, our AI services team to come in behind that and take those proof of concepts and spin them up into actual projects and get customers launched and going on this initiative. So those are some of the ways that we're starting to drive -- combine the product side with the go-to-market effort to really start that expansion activity in '26. And so I think if I look at sort of the upside and the downside risk, I do think a lot of it comes down to our own execution in '26.

Yes, yes. Okay. Perfect. And we talked about expansion, again, key driver of growth. If I were to maybe just push on that a little bit, cloud net expansion that's a rate that has been falling. I realize that cloud isn't necessarily that maybe the KPI that it was during Teradata 2.0. This is the hybrid story. But to be fair, cloud is still kind of the primary driver of growth, so to speak. When does that rate kind of stabilize? Or just walk us through where you expect to see these expansions happen.

Yes. No, that rate has been shifting as we've moved through the migration period. And especially if you look at the total ARR growth rate, that was obviously impacted for a few years by migration activity. And now we're starting to come down on the other side of the bell curve of that activity. And so I would say we're close to seeing that normalize. And so what I would expect going forward is a little bit more convergence between that net expansion rate and the total ARR cloud growth rate.

Okay. Okay. Helpful. And then I know you don't -- I know you don't guide beyond 2026. I don't expect you to give that. But it would be helpful for us to better understand if you see 2026 as kind of an inflection year that should enable a more consistent return to growth or even how you guys are thinking about the revenue growth trajectory from here? Because presumably, the fact that ARR is growing this year would set you up for more growth in 2027. But like where are you on this journey from stabilization to potential inflection?

Yes. I mean at the risk of oversimplifying it, we're looking at this journey as a bit of a crawl, walk, run scenario where 2025 was the crawl that was kind of getting us back to a stable business, getting us back to the positive side of growth from an ARR standpoint. '26, we're certainly looking to build on that. And so even just from a total ARR standpoint, we're at 1% constant currency growth last year, 2% to 4% guidance this year. So making some incremental improvement and continuing to build the foundation.

The other thing what we're doing in '26, and we talked about this on our call is that we're really prioritizing our investments. We're still looking to optimize parts of the business, so we can drop incremental benefit to the bottom line but we're also reinvesting some of that. And in particular, we're investing on the product side. And so a lot of the things that Sumeet described and we're working on now and we expect to launch over the course of this year. will become drivers for '27 and beyond.

Okay. and then sorry.

Yes, yes. And so -- we're certainly looking to start to drive that glide path. I'll stop short of giving you guidance for '27, but obviously, we're looking to continuously improve.

Fair. Okay. And then I want to touch on -- I'll ask you kind of 2 questions about margins, gross and op. Just on the growth side, cloud gross margin is still modestly dilutive to the platform, I believe. How do we think about, again, these expansions and kind of the hybrid approach. When does that stabilize gross margins? And then second to that, these initiatives on the cost side, which is reinvesting in innovation but also finding areas of efficiencies and rationalization. What does that mean for the trajectory of OpEx because then we can all kind of back into how we think about op margins can kind of go from here?

Yes. So kind of -- we'll kind of walk down the P&L there. So first, from a gross margin standpoint, and I think -- you kind of mentioned cloud gross margins, but I think it's really the total recurring gross margin, which includes both our on-premise subscriptions and our cloud business. So today, the on-premise subscriptions have a higher gross margin. than the cloud side and cloud has been growing faster. So that presents a bit of a headwind to the gross margin now. We have been incrementally improving cloud gross margin each year. We don't disclose that externally, but we've been making progress. We're very focused on that side of it and particularly for '26 and beyond I feel like we really need to start making some stair-step improvements there to ultimately drive future operating margin improvement.

If you look back over the last several years, we've made great improvement in operating margin over 500 basis points over the last 3 years. But I would say that would be -- that was largely on the backs of streamlining operating lines, right? And we still think there's a path to do that even with reinvesting in R&D in '26. And so our guidance would suggest another point of improvement on the operating margin in '26. But I think to really sustain that and maybe even take that stair steps higher, we really need to focus on the gross margin side of the equation.

Okay. Okay. Perfect. As we want to kind of think about -- let's say it this way execution is key this year, remains key. As we want to hold you guys accountable to say you're executing the way that you intend to execute. In addition to what I imagine is ARR growth, that's kind of one of the most important KPIs. Is it earnings growth? Is it operating margins? Is it free cash flow growth? What are the other KPIs we all should be thinking about that's like, hey, we're going to hold John and the team accountable. These are the metrics we should be tracking?

Yes. No, I think that's fair. I think that, yes. Certainly, from a top line perspective, the total ARR number is the more forward-looking number, right? And so -- if you're thinking about what's going to drive growth in '27, you should be focused on the total ARR growth in '26. Certainly, I think it's valid and important to continue to see how we're doing on the operating margin. Are we continuing to drop incremental benefit to the bottom line. When we talk about profitable growth, that's exactly what we mean. We're looking for ways to invest that will drive future growth, but we also want to do so in a responsible way that we're dropping that incremental profit down.

And then from there, I would probably focus on free cash flow. I think that earnings per share is also a good gauge, although there's some different dynamics at play there. I think if you look at the free cash flow number, I view that as a critically important number. And even again, if I go back to last year, we had given guidance that was roughly $260 million to $280 million in terms of free cash flow for the year. And we had done $277 million in the year prior. And as I came onboard, I was very focused on the amount that we had done last year. And was very focused on making sure we got to that level or higher in '25 and I was pleased that we were able to come out a little bit better than that. So I view that as a critical foundational element for us from a stock standpoint, frankly, and from a valuation standpoint. I feel like that gives us a good floor for investors.

And just on free cash flow, kind of the underlying drivers there? Obviously, we hear about profitability or the expectation for profitability improvements, that's clearly one. You've had some restructuring costs in the model the last couple of years. Are those rolling off? Do we expect more of them? Like what are the building blocks to get that -- this year, I think it's 10% free cash flow growth roughly is the target. But what are the building blocks that get to that more kind of sustainable free cash flow growth as you're kind of outlining it.

Yes. It's -- I mean, certainly, the face of the P&L is a big part of it, right? And so continuing to drive that operating profit improvement and looking at even below that, looking at the EBITDA performance that's your front-end driver to it continuing to be focused on the working capital side. And so doing a good job on managing collections and payables and those elements being diligent with our capital spend, our CapEx. We've generally done a good job at that. Now there may be some investments we make this year particularly around the hardware side of the business. But in general, I think we've done a nice job of managing that. And so we'll focus on all of the elements that ultimately drive them.

Recently, you guys kind of settled with SAP, you got a $480 million gross payment that nets out to, I think it's $355 million to $362 million of kind of net cash. What do you do with that?

That's a good question. Fair question. And the honest answer is still to be determined. And I think that we'll look at our entire capital structure. I think it's strong today. We've got a good amount of cash on the balance sheet. We're generating healthy free cash flow. So we're in very good shape there. We do have a term loan around about $450 million that comes due in June of '27. And so we'll take that into consideration. We're already active in the market from a buyback perspective. We announced a refresh of that program, another $500 million at the end of 2025. And so we're actively in the market and have committed another 50% of free cash flow going towards stock buybacks.

And so we'll take a look at all of those elements, and we'll talk it through with the board in a few months and just leave it at that.

And maybe as we think about that, those are maybe -- as you've outlined, it sounds like those may be the most likely opportunity.

Yes, I think like we're going to look at everything holistically, right? And so you've got debt, you've got -- what are you doing in the marketplace from a share buyback program. Maybe there's reasons to preserve some cash if we want to look at some potential M&A activity. And so I think all things would be on the table.

Okay. With a minute left, I just wondering if you can give you guys the dance for kind of last comment here. The message that you want to leave with everyone maybe what people might underappreciate or undervalue about the story, each of you want to matter, but...

Well, I would just say that Teradata is changing, while keeping the best of what we have done over the decades, we're changing. We are really, really enjoying this market in terms of innovation and really operating like a start-up in many ways. So that's what I would conclude my parts with. But you have few seconds.

Yes. I would just tack on to that and say that it's a business that's undergone a lot of change over the last several years. And certainly, the transition from on-premise to the cloud was a big driver of the business for several years. And when you're going through those types of transitions, it can get a little muddy. The story is sometimes harder to understand. So I guess I would encourage people to take a look and do the deeper dive because I do think a lot of things are starting to tilt our way. I think customers are starting to tilt our way and how people are deploying Agentic solutions, again, is starting to tilt back in favor of Teradata.

Cool. That's a perfect place to end. Thank you, guys.

Thank you, Eddie.

Good afternoon. My name is Victoria, and I will be your conference operator today. At this time, I would like to welcome everyone to the Teradata 2025 Fourth Quarter and Full Year Earnings Call. [Operator Instructions].

I would now like to hand the conference over to your host today, Chad Bennett, Senior Vice President of Investor Relations and Corporate Development. You may now begin your conference.

Good afternoon, and welcome to Teradata's Fourth Quarter and Full Year 2025 Earnings Call. Steve McMillan, Teradata's President and Chief Executive Officer, will lead our call today. followed by John Ederer, Teradata's Chief Financial Officer, who will discuss our financial results and outlook.

Our discussion today includes forecasts and other information that are considered forward-looking statements. While these statements reflect our current outlook, they are subject to a number of risks and uncertainties that could cause actual results to differ materially. These risk factors are described in today's earnings release and in our SEC filings. Please note that Teradata intends to file the Form 10-K for the year ended December 31, 2025, later this month. These forward-looking statements are made as of today, and we undertake no duty or obligation to update them.

On today's call, we will be discussing certain non-GAAP financial measures, which exclude such items as stock-based compensation expense and other special items described in our earnings release. We will also discuss other non-GAAP items such as free cash flow and constant currency comparisons. Unless stated otherwise, all numbers and results discussed on today's call are on a non-GAAP basis. A reconciliation of non-GAAP to GAAP measures is included in our earnings release, which is accessible on the Investor Relations page of our website at investor.teradata.com. A replay of this conference call will be available later today on our website.

And now I will turn the call over to Steve.

Hi, everyone, and thanks for joining us. I'm pleased to report another set of strong results for Teradata. In the fourth quarter, we again exceeded expectations for total revenue, recurring revenue and free cash flow.

Our strong earnings per share and continued total ARR growth reflect the actions we took to improve our operating model. 2025 was a year of revitalized execution. We stabilized the business, meaningfully improved retention and saw customers choosing to expand their use of Teradata with a mix of both traditional and new types of workloads. Engagement with customers remain strong and the business operated well.

We believe we are solidly positioned to continue on our profitable growth path in 2026 with healthy free cash flow generation to deliver value to our shareholders. As we look ahead, we believe the enterprise of the future will be shaped by those who harness agentic AI systems that reason, act and adapt autonomously 24/7.

We remain focused on helping organizations activate the intelligence in their enterprise, ensuring AI agents have the enterprise context they need and can act on it in milliseconds to address continuous decision-making and enterprise scale. This requires a new system of intelligence. One of the unifies data, analytics, enterprise context, governance and AI agents, we believe Teradata is uniquely suited to provide all of this with our autonomous AI and Norge platform.

As we stated throughout 2025, we saw a resurgence of interest in our hybrid model. We're seeing customers want to leverage both on-prem and cloud deployment options to meet their diverse business needs. -- driven by data sovereignty and increased regulatory environments around the globe. Our platform is designed to give customers the opportunity to run a genetic AI at scale wherever that data resides in their business, and we are seeing customers effectively operating across both.

Over decades, we have fine-tuned our platform to address massive scale with performance foundational factors for implementing autonomous AI. Throughout 2025, we saw customer engagement across all regions and industries shift towards AI and elastic compute as they explored AI uses and look to reinvent their Teradata platform for autonomous knowledge capability. Our forward deployed engineers and AI services consultants executed more than 150 engagements with customers, helping them operationalize AI to address high-value use cases.

In 2025, we launched a broad set of innovations as we build foundational capabilities to help customers bring AI into real-world use cases that can drive tangible business value. First, our enterprise vector store cost effectively combine structured and unstructured data with the speed needed to deliver information to agents in real time. We enhanced our model ops capabilities designed to enable models to run directly and save the Teradata ecosystem gaining efficiency. An exciting announcement was our MCP server. It connects AI systems with interactive access to their enterprise data, context and predictive AI capabilities necessary to provide meaningful outcomes.

We believe that the MCP server and the agentic AI solutions that utilize it will increase usage of our platform. To further speed AI adoption, we launched Teradata agent builder and introduced pre-built agents. This broad set of capabilities enables us to deliver autonomous customer intelligence, a set of software and services that embed Teradata agents to help improve the customer experience.

We also launched Teradata AI factory, an exciting announcement that brought AI and machine learning capabilities to on-premise environments. It was designed for organizations in regulated industries or with data solvency requirements or the one to manage and contain their AI infrastructure costs. And to help organizations transform their AI pilots into production-ready solutions, we introduced new AI services. This impressive set of innovations laid a very solid foundation for 2026. And we also have a fantastic set of technology announcements planned throughout this year.

We believe these announcements will strengthen our portfolio in order to help our customers get AI agents into action and operationalize autonomous AI. We have kicked off a strong start to the year with our recently released enterprise agent stack. This comprehensive tool kit is designed to help enterprises rapidly transition from pilot AI projects to production level autonomous agents across diverse environments.

Our agent stack integrates tools for building, deploying and managing AI agents with security, governance and enterprise data utilization. We believe we're delivering capabilities that set Teradata apart from the competition and we're delivering them across cloud and on-premises environments, supporting the hybrid goals of our customers.

As an AI and knowledge platform company, we are the core of a broad system of intelligence that will enable autonomous actions. To ensure customer choice, we maintain our commitment to building and executing partnerships that strengthen our connected ecosystem and extend our capabilities. For example, our new partnership with unstructured brings automated ingestion and conversion of unstructured content, meaning documents, PDFs and images into analysis-ready structured data. that supports our vision of an end-to-end AI ecosystem, helping our customers turn their intelligence in their enterprise into business outcomes.

We have multiple proof of concepts underway in all regions and across all industries. We also just announced the availability of our enterprise-grade data analyst AI agent on Google Cloud Marketplace, giving organizations a secure way to run real-time analytics agentic AI directly within their cloud environment. This prebuilt agent reduces the cost and complexity of moving data and provides a scalable foundation for future multi-agent scenarios on Google Cloud.

Now let me take you through a handful of examples of the ways organizations are leveraging our AI and data analytics capabilities many of which represent the early stages of our customers' long-term AI initiatives. A large U.S. telco added a cloud instance to Teradata estate and now runs a hybrid teradata environment. It's running specific financial compliance workloads on Google Cloud with its other workloads on-prem. This customer is also looking to use our open table format to seamlessly share data across its ecosystem.

A top U.S. airline modernized a high-impact pricing application by migrating it to our elastic compute platform. This unlocks greater scalability and agility for a program that drives significant annual revenue for the customer. A major U.K. bank selected Teradata to move its real-time customer experience platform to the cloud, reinforcing our strength in the highly regulated financial services sector.

Using our AI-powered marketing applications, the bank expects to speed up campaign launches and simplify operations to drive a competitive advantage in today's digital first banking market. We're supporting a high-tech manufacturer in EMEA on a strategic AI initiative, helping embed advanced AI and analytics into complex manufacturing models.

In doing so, we're enabling automated workflows that drive real-time AI-driven production decisions, improving yield, lowering costs and accelerating innovation. These examples from across numerous industries are representative of the team's strong momentum in 2025. And with our continued focus on helping customers get the most out of their AI initiatives, we intend to keep up the momentum in 2026.

As I pass the call to John, I'll summarize that we are entering 2026 on solid footing following our strong close to 2025. We believe we have capabilities no competitor offers and our cohesive open platform and our differentiation is resonating with customers, partners and industry analysts. We remain on our clear profitable growth path, driving operating leverage, free cash flow growth and delivering lasting value to our shareholders.

Over to you, John, to walk us through the details.

Thank you, Steve, and good afternoon, everyone. We closed out fiscal 2025 on a positive note, demonstrating operational discipline and improved quarterly consistency across our key financial metrics.

During the year, we returned total ARR to positive growth of 3% on a reported basis. We continued to improve non-GAAP operating margins to 21%. We drove year-over-year improvement in free cash flow to $285 million, which exceeded the high end of our outlook, and we reestablished a track record of meeting or exceeding quarterly expectations.

Our solid execution in 2025 has provided a foundation for continued improvement in 2026 and beyond. We remain committed to profitable growth in the new year, which we believe is aligned to driving shareholder value. More specifically, we expect continued growth in total ARR, non-GAAP operating margin and free cash flow, while at the same time, investing more resources and product development to fuel future growth.

In terms of our detailed financial results for the fourth quarter and fiscal year, total ARR grew 3% as reported and 1% in constant currency, which was an important milestone in stabilizing the business last year and right in line with the expectations that we set at the beginning of 2025. Cloud ARR grew 15% as reported and 13% in constant currency, and Cloud ARR now represents 46% of our total ARR.

For the quarter, the trailing 12-month cloud net expansion rate was 108%. Fourth quarter total revenue was $421 million, up 3% year-over-year as reported and 1% in constant currency which was 3 points above the high end of our outlook due to higher recurring revenue.

Fourth quarter recurring revenue was $367 million, up 5% year-over-year as reported and 3% in constant currency, which was 4 points above the high end of our outlook. The outperformance was primarily due to higher upfront revenue from term license subscriptions. Fourth quarter consulting services revenue was $53 million, down 4% year-over-year as reported and down 6% in constant currency.

For the full year, recurring revenue was at the high end of our outlook range at $1.445 billion, a decrease of 2% as reported and 3% in constant currency. Total revenue was also within our outlook range at $1.63 billion, down 5% as reported and down 5% in constant currency.

Looking at profitability and free cash flow. Please note that I will be referencing non-GAAP numbers for expenses and margins and a full reconciliation to GAAP results is provided in our press release. For the fourth quarter, total gross margin was up to 62% versus 60.9% in Q4 last year, driven by strong improvement in consulting services margins. Recurring revenue gross margin of 68.4% was down from Q4 24 due to the increasing mix of cloud revenue.

On consulting services gross margin, we made continued strong improvements following cost actions that we took in 2025, driving Q4 gross margin up to 18.9% versus 8.5% in Q3 and 9.1% in Q4 a year ago. Operating margin improved significantly in Q4, coming in at 22.8% versus 17.6% in Q4 last year. On a full year basis, we continue to demonstrate operational discipline, which has resulted in a multiyear operating margin expansion of more than 500 basis points over the last 3 years.

Non-GAAP diluted earnings per share were $0.74, exceeding the top end of our outlook range by $0.17. The outperformance was driven by higher recurring revenue, lower expenses and a lower effective tax rate. We generated $151 million of free cash flow in the fourth quarter and finished the year above the high end of our 2025 outlook at $285 million. This free cash flow performance drove cash and equivalents up to $493 million at the end of the year compared to $420 million at the end of 2024.

Finally, we continue to return capital to shareholders, repurchasing approximately $38 million or about 1.5 million shares in the fourth quarter, bringing our full year total to approximately $140 million or 5.8 million shares.

During the fourth quarter, we also announced the reauthorization of our buyback program for another $500 million starting in 2026 and we will again target to use 50% of our free cash flow for share repurchases. Before I provide our annual financial outlook for 2026, I'd like to provide some additional context. First, to support investors from a modeling standpoint, we will be providing guidance on an as-reported basis.

We will also continue to call out currency impact as we see it during the year.

Second, we do expect to see our typical seasonality for total ARR and cloud ARR. More specifically, Q1 is typically our largest renewal and highest erosion quarter and as such, we expect total ARR and cloud ARR to decline sequentially on a dollar value basis in Q1, followed by stabilization and expansion over the course of the year with the majority of that expansion to occur in the second half.

Third, as noted during 2025, we continue to see customers evaluate hybrid deployment options with some incorporating a combination of cloud and on-premise solutions. As they choose the deployment option that works for them, we have seen this cause variances in the mix between cloud and on-premise subscription ARR which is why our primary focus is on total ARR growth.

Finally, from a recurring revenue standpoint, it's important to remember that revenue recognition standards are different for cloud versus on-premise subscriptions. The cloud revenue follows a more consistent ratable growth pattern, whereas the on-premise subscriptions have a portion of revenue that is recognized upfront and a portion that is recognized ratably over time.

The timing of on-premise deals may cause variability in our reported recurring revenue and corresponding growth rates. For example, we saw some benefit from upfront revenue recognition in the fourth quarter of 2025 and we expect to see this again in Q1 of 2026.

Now turning to our annual outlook for 2026, which again is on a reported basis, Total ARR is expected to be in the range of 2% to 4% growth year-over-year, which is an improvement versus 1% constant currency growth in FY '25. Recurring revenue is expected to be in the range of 0% to 2% growth year-over-year. Total revenue is expected to be in the range of minus 2% to 0% year-over-year. Non-GAAP diluted earnings per share is expected to be in the range of $2.55 to $2.65.

On operating margin, we expect approximately 100 basis points of expansion in 2026. Free cash flow is expected to be in the range of $310 million to $330 million. Regarding free cash flow linearity, we anticipate Q1 to be slightly negative. On the full year outlook, we expect the majority of the year-over-year growth to occur in Q2 and Q3.

Finally, while we are not providing formal guidance for Cloud ARR in FY '26 due to the potential for variances in mix between cloud and on-premise subscriptions we are targeting growth of a low double-digit percentage for Cloud ARR.

For the first quarter of 2026, recurring revenue is expected to be in the range of 6% to 8% growth year-over-year. Total revenue is expected to be in the range of 1% to 3% growth year-over-year. Non-GAAP diluted earnings per share is expected to be in the range of $0.75 to $0.79.

In terms of some other modeling assumptions, for the first quarter, we expect the non-GAAP tax rate to be approximately 25% and the weighted average shares outstanding to be 96.1 million. For the full year, we expect the non-GAAP tax rate to be approximately 24%, which is approximately 1.5 points higher on a full year basis due to a onetime benefit of $5 million in 2025.

Also, we expect our weighted average shares outstanding to be $97 million for the full year. Using the currency rates at the end of December 2025, we expect a slight tailwind to our 2026 revenue outlook. However, we anticipate over 2 points of benefit to our revenue growth rate in the first quarter of 2026.

On recurring revenue, we anticipate upfront revenue to provide more than 2 points of benefit to the Q1 growth rate. However, for the full year, we expect upfront revenue will be approximately a 1 point headwind to the 2026 growth rate. Also, we anticipate other expense of approximately $38 million. To conclude, we took important steps to stabilize the business in 2025 and have built a solid foundation to deliver continued profitable growth.

In 2026, we will be investing more in product development to take advantage of the substantial market opportunity in front of us, while at the same time, driving incremental profitability and free cash flow.

Thank you all for your time today.

Thank you very much, John. Now before we begin Q&A, I'd like to briefly touch on the Board announcement we made this afternoon. The evolution of our Board has always been a focus, and we're looking forward to having Melissa Fisher join us in the coming weeks. She's got a great track record within software as an executive and Board member, and we think should be a strong addition.

We're also working through a search process to bring on a second new independent director later this year to complement some upcoming director retirements. So from a Board refreshment perspective, that was our news. Now operator, let's open the call for Q&A.

[Operator Instructions]. Our first question comes from the line of Erik Woodring with Morgan Stanley.

Congrats on the quarter Steve, I wanted you to kind of take a big step back and help us understand how material you think on-premise AI is today, meaning you kind of get to see both worlds from your seat, cloud instances and non-AI-based workloads for large enterprises, many of which have to keep on-prem. And so just wondering what percentage of your work of your customers are kind of in production today versus going through some proof of concept.

How are they thinking about investing on-premise for Gen AI versus the cloud? Would love just your high-level thoughts and then a quick follow-up, please.

Yes. Thanks, Erik. We see our potential and capability in terms of delivering AI solutions on-prem as something that's going to be a key growth driver as we move forward. And that's why our next generation of our hardware platform will actually have GPUs built right in. So we are definitely going to see AI and AI on-prem as a growing part of our portfolio.

If we look at the POC activity that we executed in 2025, we actually doubled the number of POCs as we come out and a number of those have moved into production on-prem driving workload and usage of the Teradata platform. So we definitely see it as a key growth driver as we move into 2026.

I also have to say, we're absolutely focused on expansion. We'll do that expansion in the cloud or we'll do it on-prem. And again, that's one of the benefits that we have of our customers choose to deploy in cloud, we can do that with them. And if they choose to deploy on-prem, we can also have that as an option.

Okay. I appreciate that color. And then maybe just -- just a quick follow-up for you, John. I believe you're guiding to a little over 10% year-over-year free cash flow growth in 2026. If I just take the midpoint of your guide, really strong. You're effectively guiding to EPS kind of flattish year-over-year. Can you just walk through the puts and takes there? Why am I seeing a bit of a difference change in free cash flow conversion? Just what's burdening EPS, I guess, in that wouldn't burden free cash.

Sure. Yes. The short answer is we had some outperformance in Q4, particularly related to a tax benefit, a onetime tax benefit. That benefited us to the tune of about $0.05 in Q4. And so I think if you adjust for that, you'll see a little bit better comparison in terms of the year-over-year growth rate and earnings per share.

And then I would say otherwise, when we look at some of the other drivers of free cash flow, particularly around working capital and continuing to improve on collections, we'll get a little bit of tax benefit next year in addition to the performance on the P&L side of things, all of those are drivers for the free cash flow.

Our next question comes from the line of Radi Sultan with UBS.

Awesome. And you have great to see the growth there. Maybe first for Steve. Can you just help us a little bit more, like what is going on behind the scenes here as you think about sort of this growth inflection? Like can you just walk through like how much is a better demand backdrop here versus sort of what you've done proactively on the product and go-to-market side? Maybe just help us piece that together a little bit more.

Yes. Thanks, Radi. That's a great question. I think the whole AI marketplace for us is opening up a new TAM -- and that's helping us return to growth in 2025. As John has said, it was a year of stabilizing the performance of the business, and we certainly executed on that. But I think we're also capitalizing on investments that we made through the back half of 2024 and into 2025, certainly improving retention rates as we went through 2025.

Our growing market teams are doing a great job from that perspective. and really driving and returning the company to overall growth for 2025. I think from a product perspective, we had a cascade of product announcements throughout the year, be it our enterprise vector store, our AI model ops capabilities or agent builder capabilities that are really changing the perception of Teradata and really positioning us to take advantage of this autonomous AI knowledge platform. If you think about data and enterprise data, we're probably the custodians of the world's most valuable enterprise data. And that for an AI system is turning into enterprise memory. And we give the best way to access that enterprise memory for agents.

So I think we've seen a number of different inflection points. We also took some time to retailer services business and are now positioned to deliver a whole set of AI services, which we think will drive some ARR growth as we move into 2026.

So I think every aspect of the business came together to deliver growth for 2025 and obviously sets a path for us to be confident in continuing that growth in 2026.

Great. And then, I guess, for John, a quick follow-up. Just on the 2026 outlook, as you think about the business mix shifting more towards expansion versus migration, does that change your fundamental visibility sort of in the outlook? And maybe you could just speak to sort of what are the biggest areas within the '26 guide that areas of uncertainty that you're handicapping there. Maybe just help us think about that.

Yes, sure. In terms of, I guess, the visibility and you're talking specifically about migrations versus expansions. There are a few puts and takes there. But I would say, in general, when you look at migration activity, those tend to be bigger, more complex deals. And sometimes it's really hard to gauge the timing of those. But expansions by comparison with existing customers is a more consistent cadence.

And so when you look at an average of that activity across the entire installed base to get a little bit more consistency there. Now I will say that our typical seasonality will be at play here in 2026. And so and we talked about that in the prepared comments, we typically see more erosion activity in Q1 and then we build ARR through the year, and we have a stronger finish in Q4, and we would expect to see that same type of linearity. But otherwise, I would say between migrations and expansions, it's a little bit of a trade-off in terms of visibility overall.

Our next question comes from the line of Yitchuin Wong with Citi.

Congratulations on the strong close to the year and solid guidance. I guess maybe start with fiscal 4Q results, it showed that much improved execution with some strong large deal momentum across U.S. telco airlines and in a bank. Could you give us any incremental color around the impact of this large deal in the quarter -- and if there's any other updates around like the improvement in deal cycle or erosion that you saw in the last year and then going towards how AI impacting this performance?

Yes. Thanks, I think you touched on quite a lot there. Yes, I think we are seeing strong strength across industry. If we look at the pattern of our business in terms of where we're deploying some of these advanced AI solutions, especially -- we've got use cases across the entire industry set.

And we saw some really good geographical distribution in terms of our wins and deal set, in fact, in our international markets, we're actually seeing really good strength in our on-prem capabilities. Just to give you a little bit of color there. Just from a retention perspective, our team is focused on growth and expansion. And I think we've made material improvements to our retention rates as we went through 2025 compared to 2024, and we expect those improvements to continue into 2026 and and that's based on a couple of things.

One, great execution by Team Teradata, I'm very proud of what we've done. But I think as well, we've got a great product set that's enabling us to deploy in this world of AI, some really high-value solutions that make us more sticky and more relevant inside our customer base. And so that's what we're focused on as we execute that growth agenda for 2026.

Maybe a quick one for John here. It looks like the services line is getting a strong improvement quarter-over-quarter. And then with Teradata ramping, I get benefit from AI services as you see more FT approach across the market shift that you're seeing. Are you expecting this to be an incremental contributor, continue that improvement going into fiscal '26?

Sure. Yes. No, thanks. Certainly, we've made a lot of improvement on the consulting services side of the business, particularly on the gross margin this year. So we -- we started off the year in negative territories. We had some headwinds on the revenue side.

But course corrected through the year, improved in Q3 and then really jumped up in Q4 from a gross margin standpoint to nearly 19%. And so I think we've managed through the transition of this business really well. The thing that is still there, I would say, from a macro standpoint is that historically, what's driven that business has been a lot of migration activity.

We're starting -- we've seen the peak of that activity, and we're on the other side of that bell curve now. And what we expect to take the place of that is the AI services. And so we are starting to ramp that up this year, and that will help offset some of the migration activity in 2026. And so I think by and large, we've stabilized that part of the business.

I think we've got a good strategy for moving forward. The one last thing I would say just from a margin standpoint, I wouldn't necessarily expect that 19% in Q4 to continue at quite that high of a rate. If you look back at '23 and '24 I think you'll see a more normalized rate for consulting services.

Our next question comes from the line of Chirag Ved with Evercore.

Congratulations on the quarter. Great to see the return to positive ARR growth and operating leverage. Steve, you mentioned over 150 AI and agent engagement, can you talk about the typical conversion path from these engagements into revenue and how you think about the time line from initial pilot to material ARR contribution.

Yes. Thanks, Chirag. It's a great question. As you said, we are seeing a significant growth in AI workloads on the Teradata platform. We're capturing that shift of spend and, say, the customer base that's moving towards this more sticky, more relevant advanced set of solutions. And so that pivot to AI is something that we're really benefiting from.

In terms of operationalizing these workloads, that's something that we do every single day with our customer base. Whether it's a bank in Australia that's utilizing their on-prem system, for customer sentiment analysis. You're running that AI workload on-prem, whether it's a customer in Europe using cloud-based technologies for their AI solution. So I think we're seeing those AI solutions, certainly driving capacity and usage of the Teradata platform, and our sales team is now completely focused on growth.

We're not as focused on capturing that ahead long migration rush to the cloud. The teams are focused on growth where they can execute it. And I think this is -- the AI workloads are going to be a key element of capturing that growth as we move through 2026.

.

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

This is Sheldon McMeans for Raimo. You certainly discussed some of the newer AI-related solutions on the call, some of which that you launched during your October event, it seems like many of these are going to be available in 2026, particularly in the back half of the year.

And just when considering your positive growth outlook for the year, how much contribution are you baking in from some of these newer initiatives?

Yes, Sheldon, thanks very much for the question. Look, I think as we've looked to the business and how we're executing against the business, you're absolutely right. A lot of the road map elements that we have start to come in at the end of Q2 and then into 3Q. That's not a stop in our sales team is getting out right now and talking about these capabilities with our customers.

We know what the sales cycle is. We know our customer base, we know how they operate. And we're getting a lot of excitement around those capabilities just now. But from a financial perspective, we haven't factored a lot of incremental ARR from these specific capabilities. Certainly, we see it as the opportunity and I'm certainly pushing the sales team to use that, those new products that are releasing has some upside to the outlook that we have currently in place.

Understood. And a quick follow-up. Could you give a quick update on the hardware refresh in the current stage that is in? And just maybe how much work is needed and do customers right now have enough visibility into the cost in some of the other related considerations to be able to make a decision on that today? Or is there still some more work to be done before customers fully understand that? And then maybe any model impact that we should consider as the hardware refresh.

Yes. Thanks, Sheldon. Yes, we don't expect a new hardware platform to go GA until end of second quarter into third quarter. So that refresh activity, although we talk to our customers about it in terms of how they would like to deploy and utilize these new solutions. It wouldn't really kick in until the last quarter of the year and then into 2027. But doing refresh is always an opportunity to sell more. And especially as these platforms are going to have GPUs built then some of the announcements we've had about using the NVIDIA AI software stack that's going to be embedded into that new platform.

We are really delivering on that promise of the autonomous AI and knowledge platform from an on-prem perspective and I think our sales teams are super excited about what they can see and what they can deliver for their customers through 2026. But again, just from a modeling perspective, we haven't we haven't baked a lot into the second half of the year, but we certainly see it as upside.

Our next question comes from the line of Derrick Wood with TD Cowen.

This is Jared on for Derrick. Heading into 2026, I'm curious what types of investments you're going to be focused on from a headcount perspective? Do you intend to ramp up sales hiring as you address this AI opportunity or maybe Leanne 4 deployed engineers?

Yes, Jared, thanks. That's a great question. We leaned in, in 2025 in terms of restructuring the sales team and the sales force. And I think the leadership team and our go-to-market team across the board have done a great job in that. And that also -- we took the steps to actually refocus investment in current sales head dollars and expense towards -- just to your point, the forward deployed engineering model.

And we see that as a very, very appropriate way to get these advanced AI solutions into our customer. If we think about what we do as a business -- we take that data layer for AI and then add value to it every single day. And so that's our forward deployment engineering capability.

One of the things that we are investing in and where we have carved out dollars is to spend a little bit more on our product engineering and product development process. This is an exciting time to be in this industry as it transforms and as the importance of continues to accelerate. And in order for us to continue to have a great product line, we've supported some key investment areas that we can focus on that are going to make some tremendous differences in terms of the overall product portfolio that we have.

And our new Chief Product Officer, Sumeet Aurora is doing a great job in terms of marshaling that product vision. And we're looking forward to sharing more about that as we move through the year.

Our next question comes from the line of Wamsi Mohan with Bank of America.

Maybe one for John. Can you just talk about the linearity that you're seeing for the year? You obviously gave a Q1 guide, and you mentioned sort of the step down in ARR. But do you expect normal seasonality after Q1? And also as you think about these new initiatives that you're taking on into the back half, and I just heard Steve say that not really baking much into it into contribution from those in the back half of the year. Should we kind of not be thinking about more of an acceleration as you go into the back half of the year? And I have a follow-up.

Sure. Yes. Just on the seasonality point, I guess I would make a distinction between ARR and revenue. And so from an ARR standpoint, both total ARR and cloud ARR I would expect to see our typical linearity, and that's what we laid out in the prepared comments where we have a bit more on the erosion side in Q1, and then we build that up over Q2, Q3 and finish with a strong Q4. And so I would expect that, like I said, very typical seasonality to exist again on the ARR side and with I would say, minimal impact from the new products that we're looking to release through the year, as Steve commented, I would distinguish that from the revenue side of the picture.

And so from a recurring revenue standpoint, we do have some anomalies this year, principally due to the timing of upfront revenue related to the on-premise portion of the business. And so we are seeing outsized growth on recurring revenue in our Q1 guidance. We talked about we're getting a couple of points of benefit from currency, we're getting a couple of points of benefit from upfront revenue recognition in Q1. We expect that to switch somewhat as we look at the full year. There'll be maybe a slight tailwind on the currency side for the full year, but a 1 point headwind on the upfront portion of recurring revenue for the full year.

And so again, we have some timing impact principally related to the on-premise side that impacts the recurring revenue piece versus the ARR.

Okay. Yes, that's helpful, John. And then maybe for Steve, Steve, you mentioned obviously some comments in your prepared remarks about the Board refreshment program. You have been delivering improving results over the last few quarters. And so in some ways, as we think about the involvement here and this agreement with Lynrock rack to the extent that you can comment about it. What are specific areas or changes at the high level that you think that the Board is going to try to implement in working with you?

Yes. Thanks, Wamsi. Yes, Board refreshment is something that clearly is super important to our overall governance process, and it's something that we continue to look at. And we're very happy to work with Cynthia and Lena to identify some candidates and come to an agreement around placing this particular candidate on the board. We're really looking forward to Melissa coming on board. She's got a great skill set, and I think she'll add some great value.

And then as we continue the Board refresh throughout the year, we're going to execute a very structured process. We declare very -- in some detail actually for the skill mixes of our Board members and obviously, we're going to continue that process as we execute through that board refreshment.

Our next question comes from the line of Patrick Walravens with Citizens.

This is Nick on for Pat. Congratulations on the quarter. Steve, one for you then, John, I have a follow-up. So Steve, the biggest question investors are asking right now is what are the characteristics of a software company that's going to make it through the AI transition? If you look back at the transition from on-prem to SaaS 20 years ago, only 40% of those top 20 companies survived. So what do you think those key characteristics are for this next transition that we're seeing from SaaS to AI?

Yes. Nick, that's a great question. So I think about it in terms of Teradata 10 to Territory 2.0, and that was our cloud transition. -- and getting over $700 million of our total ARR in the cloud was a key modernization step that we had to take as a company, and we've achieved that over the span of 5 years, which was absolutely fantastic.

We are looking forward to Teradata 3.0. That's driving this autonomous AI and knowledge platform. We're not a SaaS company. We are the data layer for AI, that system intelligence or enterprise memory -- and if you look back at how Teradata works with clients, we've always built value on top of that data platform. And now we see that, that value is being delivered via agents -- and that's why we are all about enabling these agents to utilize enterprise data at scale.

And we think that, that's going to drive significant market opportunity for us into the future. and help accelerate our growth as we launch these new products, which will take advantage of that and deliver on execution throughout the year. So it's a time of transition, but we believe that the capabilities that we've built up make us more relevant now in this agentic AI space.

Got it. And then as my follow-up, John, you guided to an operating margin expansion in 2026. Can you comment on what the main drivers of this expansion will be?

Yes. At a high level, we're continuing our work on the gross margin side, although as I described earlier, -- we have some offsetting elements there. And then when we look at the operating expense lines, we are looking to invest in product R&D, but continue to find efficiencies across the G&A and sales and marketing lines.

Our next question comes from Matt Hedberg from RBC Capital Markets?

This is Simran on for Matt Hedberg. Congrats on the quarter. Just 1 for me. I'm curious on how increased memory pricing is impacting the business. And if it's providing a boost to 2026 ARR?

Yes. Thank you for the question. Yes, our supply chain team has done a great job in terms of protecting us from the P&L impact in terms of increased memory prices. A lot of our contracts are committed capacity that we've contracted a number of years ago. So the actual uplift from that incremental memory cost is something that we're absorbing with our customers -- but we're tending to -- that tends to enable us to have different expansion conversations with our customers instead of talking about them spending more money on something that they expect to get anyway, we can actually pivot that conversation to invest in innovation on the Teradata platform. And that's really what our sales teams are doing every day. We're absolutely focused on that from a total ARR growth perspective.

There are no further questions at this time. I will now turn the call back over to Steve McMillan for his final remarks.

Thank you, operator, and thank you, everyone, for joining us today. We are really proud of the progress that we've made, and we do believe that we are really very well positioned with our AI and knowledge platform, our AI services expertise and our growing ecosystem of partners -- we're going to continue to drive clear and compelling outcomes for our customers and last in value for our shareholders. Thank you all very much.

This concludes today's conference call. You may disconnect.

Good. Perfect. Hey, welcome to our next session. I'm really happy to have the Teradata team here. John, if you think Q3, it seems like a very good quarter for you guys. Share price reaction was a lot. Congratulations.

Thank you.

To bring everyone up to speed, like can you talk a little bit about what drove the upside of describe the quarter?

Yes, happy to. And thanks very much for the invitation to the conference. It's been a great event for us. And I really appreciate the opportunity to present here today. If I look back at Q3, it was interesting. I would say you almost separate it into the fundamental side of things and then the stock reaction. And from a fundamental standpoint, I think we delivered a really solid quarter. We had total ARR in positive territory, which was ahead of schedule for us. We had improvement on the margin side of things. We had a strong quarter from a free cash flow standpoint from an earnings per share standpoint. So from a fundamental point of view, there was good upside to the quarter, at least relative to the consensus expectations. Now if I'm being honest, and I look at all of that and I say, well, was that an up 30% kind of quarter? I don't know what was that. But -- and so if you separate out the stock reaction, I think coming into the quarter, I felt like we were undervalued.

And I think if you look at our stock on a historical basis on a -- even just on a free cash flow multiple basis, I think we were trading at a level that was heavily discounted. And so I think we've recouped that at this point. With hindsight, I think we started to make a little bit of a move after the second quarter. We had Q1 was in line or maybe a little better than expectations. Q2 was the same. I think initially, we made a little bit of a move after Q2, but then we ran head first into a tough market for software stocks. And I think people kind of forgot until we got to Q3 and did it again.

Yes. Great. That's nice to hear. And then we did also see like -- I see it in my conversation, there's more excitement around Teradata. Again, like from the conversation you had since the quarter ended, like how -- what kind of change in tone do you get from investors?

Yes. There has been a lot more interest for sure. So there's been some nice follow-through on the stock, but also just we've been out on the conference circuit. I think this is our fourth conference this quarter. And there's been a lot of interest. Even if I just -- I've only been around for 6 months or so, if I compare and contrast to about 90 days ago, the level of interest today is considerably higher. And -- and it's been good. It's been focused on the fundamentals of the story and where does Teradata sit in this overall environment for AI. And so there's been a lot of good enthusiasm. And I think the stock movement caught people's attention, and there's been good follow-through from there to get to know the story again.

If you -- and we talked a little bit about the quarter, but like from my perspective as well, the operating profit, cash flow were kind of like the really big highlights for me. Can you talk a little bit about like the initiatives that drove that? What were the factors there that we should be aware of?

Yes, for sure. We are very focused on that side of the equation. And as we sit back and think about how are we going to ultimately drive shareholder value, a very first important step is doing some of the things that I just described. One, get a little bit more consistency in the business from a quarterly standpoint, get total ARR into positive territory. We've continued to focus on the cost side of the equation to make sure that our margins are in line and our free cash flow is in line. And ultimately, at this stage, what we're trying to do is build a solid foundation for '26 and beyond. And I think the very first important piece of that foundation is the free cash flow. If I look at our stock and I want to get a floor in place for supporting the value of our stock, it comes back to free cash flow. And so we're very focused on that. And we -- we've done a number of things over the last 12 to 18 months really to make sure that we're optimizing our cost structure and enabling ourselves to continue to drive margin improvement in free cash flow.

Yes. Okay. Yes, it makes sense. And then the like growth is -- but as you mentioned, growth is kind of going to be the main question because you can't kind of do margins forever. Can you talk a little bit about where we are on that journey?

Sure. I would agree with you that if I think about the stages of what Teradata needs to go through, especially after last year, the first stage was stabilized. And I think we've demonstrated that this year. And then it's built the foundation for continued expansion. And we talked about this a little bit on our third quarter call. We feel confident we can get back to total ARR growth this year. We did it the last couple of quarters. And we've built that foundation to continue to drive ARR -- total ARR growth next year. We're also focused on driving free cash flow growth next year. And so that's building the foundation. We are -- from an investment standpoint, we are prioritizing R&D. And we believe that continuing to invest in product innovation will help drive the next leg of growth for us.

And so I do completely agree. I mean I think there's benefit to be had in our stock over the next 1 to 2 years just by margin improvement and demonstrating durable free cash flow. But then ultimately, as a public company, you need to demonstrate growth, and that's what we're ultimately driving towards.

Yes. And then talk a little bit about like -- at least for me, I sensed a little bit of change in tone like a few quarters back was all about cloud ARR, and now it's more about total ARR, kind of talk a little bit of what you're seeing here in the market that drives that. And maybe it's just me, but or like...

No, I think that's a fair observation. And -- and I would generally agree. I think that when we look at what we're seeing from our customers, there's more discussion now about what should be on-prem versus the cloud. It's not just running to the cloud for the sake of being in the cloud. And so I think that has influenced us a little bit in terms of even just how we're talking about the business. And I will tell you, though, from a financial point of view, when I look at the rest of the model and what's going to ultimately drive profitability and free cash flow, we need total ARR to grow. Cloud growth is important to us. It's the highest growing piece of the business and will continue to be a key driver, but we need the total pie to grow to then drive higher recurring revenue and ultimately higher margins in cash flow.

And then how do you go about -- like if you think about like the different things like in the past, there was cloud -- like people move to the cloud, so I get my cloud ARR number up. Thank you very much. And it's more like a transfer from one. Now if it's total ARR, like how do you -- what are the initiatives that you can see to kind of drive that number?

Yes. I think for several years, the market itself, was all about the cloud. And we were doing the same. We -- 6 or 7 years ago, we launched our cloud product. We started to migrate our customer base to the cloud. In a relatively short period of time, we drove that up over $600 million in ARR. And so we demonstrated that we can be a cloud provider as well. And I still think that's important. But to your point, some of that is left pocket, right pocket. You're migrating customers from on-prem to the cloud, and that was driving some of the exponential growth we saw a few years ago. Today, we're starting to reach a little bit more steady state. And in fact, if you look at our charts on our website, our IR charts, you'll see the breakdown of our ARR between cloud and on-prem. And you'll see over the last 4 quarters that the on-prem piece has started to stabilize.

In fact, in Q3, the on-prem ARR actually increased. And so that piece stabilizing is really important for the whole model because it's a lot easier to grow if that piece is stable versus declining, right? And so for us, we're looking to drive the whole business. And we think that in terms of some of the way customers are engaging with us now, particularly around AI investments, I think there's an opportunity to grow both on-prem and the cloud.

Yes. Okay. And then the -- if you think about it, there -- what's driving -- if you think about the growth factors, so there's like find new customers, there's upsell, better, there's skew management, et cetera? Like talk a little bit about how you think about the different factors here.

Yes. For us, I would say the primary focus is on expansions in the customer base. We are well embedded in the Global 1000 and some of the largest customers in the world, and we've been working with them, in some cases, for decades, and we're looking for opportunities to continue to grow and expand with those customers. That's not to say that we've just thrown in the towel on new logos. We're very interested in driving new logo activity as well. And in fact, have had some success in recent quarters even on-prem with new logos. But I would say the bigger near-term opportunity is expanding with the customer base. And we're looking at AI as a real opportunity to drive that expansion. And so with the Teradata platform today, we started to layer in additional products, things like agent builder, things like AI factory, our MCP server, enterprise vector store, tools that help get the customer up and running on AI.

We've also layered in AI services. We just recently announced this in October at our customer conference. And this -- you can think of this as kind of that forward deployed engineering group that will help enable customers to get projects up and running. We're already doing the proof of concept. This is the next logical step to get a project up and running and get them live.

And then the -- if you think about it, like, obviously, there's a lot of talk about these cloud vendors in your space. But the market has been incredibly broad and it's been very well, aged with so many different players in the market. And I'm just wondering what is the opportunity if you think about new customers around like Netezza, I think IBM put it end-of-life, Vertica is still there? Like how do you think about like customer growth?

Sure. There's -- I mean, there's opportunities on both sides for us. I think that in some ways, we almost compete in 2 adjacent markets because we can compete with the historical on-premise providers. And I think we do quite well in that world. And then we also compete on the cloud side, and then I guess we have the unique opportunity to go after customers that are looking to do both. And so being able to provide that hybrid environment is a unique differentiator for us. And so yes, certainly, as we see changes in the historical on-premise part of the market, those are opportunities for us.

And then you mentioned AI already like -- and I just came out from a start-up session where it's all about like AI is only as good as the data. You always have been like a centerpiece of where customers kind of keep the information which data, clean data, which would be in theory, very valuable. Like how do you think about your role in this world? And what are you doing about it?

I couldn't agree with you more. So I think that I do think data is at the heart of it. And so if you think about historically what Teradata has done, to your point, we've been the place where that data gets stored and then we make it available for the analytics and other elements that come on top of that, including now AI. And as we start to look forward, and think about the opportunity. We're looking at it from really kind of 2 points of context. One is just being the storage for the data. The other is providing the context around that data. And so we have decades of operating with very large customers in every major industry, whether it's financial services, retail, automotive, banking, aerospace, like we've been in those industries for decades. And we've built up industry data models in those areas. And so we think providing that context in addition to the data is critically important in an Agentic world. And so I think that we play a key role in this.

Yes. Okay. Perfect. And then is there -- do you think it's going to be more like playing out in the public cloud. So it's the cloud ARR that comes back in the focus? Or do you think you can kind of be that player on both sides as well on the on-premise side and on the cloud side?

I think it could potentially be in both. Certainly, cloud has been the fastest-growing piece of our business, and I would expect that to continue. But I think there's opportunities in both and there's opportunities from a hybrid perspective as well. It's interesting when you think about some of the historical strengths of Teradata, and really, we were built for the enterprise. We were built for large enterprise, and we were built to operate at very large scale and to do it very efficiently. And that's exactly what you need in an Agentic world. our Chief Product Officer is fond of saying, agents never sleep. And it's true. You think about human interaction with the system and maybe somebody's working 8 or 10 hours a day, you think about an agent who's literally on 24/7 and the capacity that's going to be needed to handle that sort of activity. And so I think that actually bodes well for us because we've demonstrated through our architecture that we can operate at that kind of scale and do it very efficiently for the customer.

Okay. So if I put it together, it's like as a data vehicle, you're kind of really important on both cloud and on-premise and then there's the adjacent products? Like how do you think about productizing this now? Like if I'm a customer and I come to you like how do I buy this?

Yes. I would say continued work and evolution on that front. And our product team is very busy as we speak. And I think there'll be some things that we'll announce over the first half of '26 that will help us in that regard also. And I do think, as all of us, collectively, the market dive deeper into AI. We might have to look at some creative ways to price and package the solutions going forward. Today, it's still largely volume dependent for us. And so we think in terms of capacity and ultimately, customer usage of the Teradata platform and things that drive additional workloads and drive the need for additional capacity result in ARR for us today.

And then with your kind of expanding role in this new AI world, like should that show up as well I saw I'm the number guy.

Sure. I appreciate that.

Should that show up in kind of renewal rates and stuff like that as well as the platform becomes more strategic again or it was always strategic, but you get another layer of strategic on open now with AI. Does that kind of then drive kind of renewal rates, different renewal rates? And can you start seeing that already?

Yes. We've done better on retention rates throughout '25. And I would expect these types of opportunities to continue to help us improve that and to drive overall ARR growth. And to the extent that we can make the platform relevant for these types of workloads, useful for these types of workloads, you should see that in better -- continued improvement on retention side and really on the net expansion side of things.

Yes. Okay. Perfect. Yes, makes sense. And then the -- if you think about it, like -- and that's more like an operational question. If you think about Cloud ARR as a focus, it's kind of one mindset from a sales perspective. If you look at more total ARR, it's another mindset from a sales perspective. Talk a little bit about the evolution of your go-to-market go to market for us. The other thing is also, like at the moment, the growth is not like not quite there where we wanted. How much can sales capacity help you out there as well?

Yes. I think of it may be slightly differently. And so as opposed to having to sell cloud versus on-prem in a lot of ways, it's a similar type of motion because you're ultimately selling the platform, and it's how the customer chooses to deploy it. What I think our sales force needs to continue to do is develop those use cases around AI and be able to sell that kind of capacity, right, that kind of story, if you will, and demonstrate to customers how you can use Teradata in that environment. And so I think that's the evolution that needs to take place. And I think it already is. We have a team that's been dedicated to AI and AI use cases. And they've been working directly with customers, and they're on track to do 150 proof of concepts this year. And that's a very important first step. I mean these are extensive projects that we've done with the customers to go in, really analyze everything that they're doing. And then put together a road map for them to follow to start to embark on this AI journey.

And I mentioned the AI services earlier. That's the next step in this. And so now we've launched this service which can take that proof of concept, actually spin it up into a project and get to something tangible and get to something that can go live. And so we think that the combination of those 2 things will ultimately result in additional ARR for the company.

Yes. Okay. And then the -- you as a CFO, like what are you use as a metric to look out for, like, okay, more sales capacity could work here? I mean, like I don't think in the early stages because it's a lot about upselling, kind of working with the existing customers. But like how do you think about that dynamic?

Yes. We evaluate that pretty regularly. And so in fact, we're in our budgeting cycle right now. And I would say for '26, we're prioritizing more on the R&D side and product innovation. But we are also focused on sales capacity and expansion of the sales force and also developing things like AI services. And so we're placing our bets very strategically and, frankly, looking to optimize other parts of the business so that we can fund some of those initiatives.

Yes. Remind me, what's the -- on that note, like what's the margin framework that you gave out like in terms of like how like margins are evolving from here as part of the journey.

Well, we haven't really given the framework per se. And I would -- and I would admit that maybe we're overdue for something like that. I think it's been quite a while since we've had an Analyst Day. But what we have talked about is driving a profitable growth strategy, which in my mind, means we're doing 2 things. One, we are still investing for growth. And first and foremost, we have to find a way to generate incremental ARR in the business.

But secondly, we want to do that in a responsible way. And we want to do that in a way where we can also drop incremental benefit to the bottom line. And again, it kind of comes back to how are we going to drive shareholder value. When I look at the stages of where we are and stabilizing the business and then expanding from there. At this point, I think we still need to drive a very balanced approach. If I think about how could we get to the rule of 40 someday, it's going to have to be a balanced approach of both growth and incremental benefit on the bottom line, incremental margin. Now if we get to the point it somewhere in the future where we're in a high-growth scenario, I'll come back and reserve the right to change my answer. But today, we're very focused on driving that incremental benefit on the margin side.

Yes. Okay. And you emphasized quite a bit like cash, cash flow, cash generation is kind of important to you, which kind of makes sense at this stage as well. How do you think about the usage of cash? There's buybacks? Obviously, at some point, as growth is returning, it's a question, do you pull back on that one and maybe M&A becomes more important, et cetera? How do we think about that?

We have been very, I would say, almost aggressive in terms of share buybacks over the last several years. This year, I think we're on track to use 50% of our free cash flow towards buying back our own stock. In prior years, we were closer to 70%, 75%. So I think we have been very aggressive on the buyback side. We did just re-up it. And so our buyback was set to expire in December. And so the Board just authorized a new buyback of $500 million that will kick in January 1. And so we intend to continue to buy back stock and support shareholders in that way. I would say we're also open to other opportunities. And so we've got a team that's actively looking at M&A opportunities again.

And I think for us, it would be something that would be much more in the technology tuck-in category. We're looking for things that can accelerate our road map, particularly in AI. And so we could potentially use some of our balance sheet for that. I think we've got plenty of room to do a few things.

Yes. Okay. Yes, it makes sense. And then the -- if you -- if you think about the evolution for you guys, there's -- in this new AI world, there's certain players. If you look at you from a technology perspective, you were always like actually one of the best technology companies out there like the way you kind of work the data was always kind of leading in the industry. If you think about going back to growth as well like now that you're in the cloud, you're well established in the cloud, like how much of that is kind of changing momentum in the market in terms of mind share. And so you talked about R&D, but like there's also then the question is like, is it an R&D problem? Or is it more sales and marketing kind of debate?

Yes. Well, for us, I would say the focus on R&D is about capturing the opportunity that's right in front of us. And again, if I step back the big conversation change has been AI, without a doubt. And if you go back a couple of years ago, it was all about cloud, cloud for cloud's sake, right? Just like let's just get to the cloud. You didn't really need anything more than that. And today, the conversation is a little different. And the conversation is around how do I start to develop and deploy AI solutions? How do I become an autonomous enterprise? And that's a little bit of a different discussion. And I think there's a couple of different paths, a couple of different opportunities. There's one school of thought that is, hey, first, you need to migrate everything, right? And this is kind of -- it's a little bit of deja vu all over again, but it's the original premise of an enterprise data warehouse.

First, let's migrate everything to a data warehouse and then we'll put the analytics on top of that. And so today, you have version 2 of that, which is let's migrate everything to the cloud and then we'll do AI on top of that. That is one approach. The other approach is that you could start your AI journey today. And you can work with the existing data landscape that you have. And Teradata is firmly entrenched in that data estate at Global 1000 customers. And so what we're doing from a product standpoint is building out that tool set and that capability so that customers can start their AI journey on top of Teradata.

Yes, yes, yes. Okay. That makes a lot of sense, yes. Okay. Last question for me is like if you think about it from an organizational perspective, as a CFO, like you're there not so long in the company. Like -- so when you came in like when you walked into the organization, what were the things where you realize, okay, this is where I can help them. This is kind of where I can make a difference.

Yes. I think -- I mean, look, in my role and my job, it's ultimately going to come back to the numbers, and it's going to come back to how do we drive the economic model for Teradata and how do we ultimately deliver shareholder value? And how do we do that over a longer-term period. It's not just a 1-year deal. And so we focus quite a bit on the forecast and the long-range planning of the business and where are some of the key areas where we can drive incremental value. And so cost of revenue is one area that we're very focused on right now. And I think there's -- we actually have already made some good headway on the professional services part of our business. We saw that in the third quarter.

I think there's still more opportunity there. But we're also laser-focused on the recurring side of the business and making sure that we continue to improve margins there. That would give us more capacity, if you will, for operating expenses, right? And give us the opportunity to continue to invest in R&D as well as sales capacity as needed. And so we'll look for ways to optimize the G&A side, the cost of revenue side so that we can invest in the other areas.

So then if it's slightly less cloud and more on-premise that would help G&A though.

It would help a little bit.

No, not G&A, like...

That would help on the gross margin side.

Yes, yes. sure.

And so yes, I think ultimately, I think that's in large part, what the CFO role is about is helping to guide the business towards financial objectives, start to break them down into areas that people can focus on shine some light on areas where we have opportunity and drive value that way.

Perfect. John, that's a great closing statement.

Thank you.

Good to have you. Thank you.

Awesome. Let's go ahead and get started. Thank you, everyone, for being here today at the UBS Global Technology and AI Conference. My name is Radi Sultan. I cover the mid-cap infrastructure software stocks here at UBS. Next up, we have Teradata. John Ederer, CFO; and Chad Bennett runs IR. So first of all, thank you very much for being here today.

Absolutely. Thanks for having us. It's been a great conference for us.

Awesome. Maybe just to kick it off, let's start at a high level. I think you very recently hit your 6-month mark at Teradata. The business has really stabilized. You've gotten into a good cadence of upbeat. So maybe just walk through your biggest learnings, the biggest takeaways in your first 6 months on the job.

Yes, for sure. Thanks again. The first 6 months are always interesting. I think every new company I've ever gone to, there's a lot to learn for a few months, and then you start to get your head up above ground again and you can start to look towards the future, and it's been great so far. I think the thing that's probably impressed me the most has been the people, the team that's at Teradata, including the leadership team, we've got a relatively new leadership team.

We've had some turnover there in the last year or so. And I feel like we're working together really well and really making the right decisions for Teradata and for the future of Teradata and kind of even at the expense potentially of our own department. So we're really coming together nicely in that way. I think that the organization has a lot of resilience, if you look at the changes in our marketplace over the last, well, gosh, nearly 40 years that we've been at this, we've weathered a lot of twists and turns in the market landscape, and so I see a lot of resilience across the organization.

There's a lot of enthusiasm about what's ahead for us, and I know we'll get into a little bit of this. internally, we're referring to it as Teradata 3.0. And so as we emerge from developing a cloud business and focusing a lot more on AI and what it means to be an autonomous knowledge platform we see a tremendous amount of opportunity ahead. And I think there's a lot of enthusiasm, frankly, around the company right now.

Yes. Awesome. Maybe just drilling into the AI front, I believe AI is being attached to around 1/3 of deals in the pipeline today. So maybe just talk through where are you seeing the most traction? What are some of the biggest early AI use cases where Teradata is getting pulled along?

Yes, sure. So we are starting to see, I'll call them, the early indicators of AI on our business. And we've talked about a few different things. One is the influence that we're starting to see in our pipeline, and that has been growing. So getting more sophisticated about how we track that exactly and then we're starting to see it show up in the pipeline and influencing our pipeline. The second big area is around the proof of concepts that we're doing with our customers, and we're on track to do 150 or so by the end of this year, and that number has been increasing as well.

And we're getting some really good traction in these conversations. And we've got a team that's embedded in our sales organization. that goes in and really lays out a game plan for the customer in terms of how to use the Teradata platform in an AI setting. And so we've been getting into a lot of good discussions. We've developed a wide variety of use cases, frankly. Some of the things that are a little bit more common in the financial services industry. We've done some things around anti-money laundering. We've done some things around fraud detection, in the retail space, we've done some things around customer experience.

And so there's different types of use cases that can be deployed and they all are tailor-made for the customer. And so one of the things that I think gives us a little bit of an advantage in this regard and why we talk about a knowledge platform is that we have the core of it, which is the enterprise data warehouse, and you need to store the data somewhere. But we also have the context around that. And that comes from decades of working in these industries, developing industry data models, and so bringing those 2 things together, I think, gives us a unique advantage.

Awesome. And maybe when you think about the AI products portfolio today, you have enterprise vector store, MCP server, agent builder, like how do you think about monetizing these offerings longer term? And maybe which of those do you see as the biggest needle mover over the next several years?

Yes. I think there -- I mean, all your children are important, right? So -- but it's -- I guess to the heart of the question, how do we ultimately monetize that? There will be opportunities for traditional cross-sell activity with distinct products. But the way this will come together more is in terms of expansion and expanding use of the Teradata platform. And so again, if you think about what's happening in an agentic world, you're now having agents take the place of humans and agents are around 24 hours a day.

And so there's just going to be a much higher level of capacity needed workflow needed to be able to handle that type of an environment. And so where we benefit is by providing these tools and making Teradata a platform with which customers can build AI solutions, we benefit from that increased workflow down the line.

Got it. And a big focus on the last call was around the FTE group that you guys formed. Can you walk through a little bit of the background there, where that group has been most focused, the extent to which it's just AI? Or is it sort of around use cases for the broader platform and maybe any early wins or traction there you could share?

Yes. No, this is another important piece of our strategy. And so we did just a couple of months ago at our customer conference in October, we launched what we call AI services. And it's very analogous to what you've seen at other deployed engineering. And it's an opportunity for us to get more engaged with customers as they're trying to spin up these new types of solutions.

And in a lot of ways, it's really a very natural extension of what we're doing with the proof-of-concept work. And so the team goes in, we developed a proof of concept, which is essentially a road map, a game plan for the customer to go start attacking AI solutions. The AI services team comes in right behind that as the natural next step and actually spins that project up. So now that we've identified a few opportunities, a few use cases, let's spin up the project and actually get it going. And so we think that, that will ultimately benefit us in terms of additional ARR down the road because, again, we get these projects going.

We develop the need for additional capacity, and then we benefit from that.

And I guess you guys already have a pretty substantial services footprint already. How much of this sort of AI services group was the repurposing of your existing services footprint and maybe helping you streamline that versus incremental?

Yes. A lot of it is repurposing and there'll be some upskilling along the way. But if you think about that business, our consulting business, it's been going through a bit of a transition of its own. And a lot of that business was driven by cloud migration activity a few years ago. And as we've kind of hit the peak of the bell curve for migration activity, we're on the other side of that now. we're seeing that same trend in our professional services business, the consulting business.

And so AI services is a new offering, but it's an opportunity to pick up some of that slack on the consulting side. And I think it's something that will start to help our business in '26 and even into '27 and beyond.

And I guess maybe just zooming out when you think about the services business more broadly going forward, like how do you think about that business from a top line and margin perspective going forward?

Yes. So from a top line perspective, first stage is getting it back to flat, right? I mean it's been declining as that migration activity has come down this year. So we need to stabilize that from a revenue standpoint. I think if you zoom out and think about that business I guess, on a relative basis to the rest of our business, we're in the, I think, kind of 12% or 13% range in terms of total revenue today.

So probably something in that 10% to 15% range would be the right range for us. We still think that it's important to have some consulting services, and we believe that it's very complementary to the software business. But it doesn't need to be as big as it used to be at Teradata. From a margin perspective, we did hit a little bit of an air pocket earlier this year. Q1 and Q2, we actually had negative gross margins on the consulting side. And again, that was a lot of that migration activity coming down. We did take some corrective actions in Q2 and Q3. We brought that margin back up to positive territory in Q3, I think 8.5% in Q3. And I think there's a little bit more room to go in Q4. So we are looking for that business to be profitable and a contributor to the bottom line for sure.

Got it. And maybe just drilling down into that cloud migration piece around Q4, specifically, you guys called out a few large customers that were considering on-prem versus cloud and sort of that hadn't made the decision yet. So maybe you could just talk through sort of what are the key sort of decision factors in those customers and how you can ultimately still monetize those customers, whether they're on-prem or in the cloud?

Yes. No, it's an interesting dynamic that's been going on. And so I think if I back up maybe a couple of years ago, it was all about the cloud. How do we get to the cloud? And we were doing the same thing. We were building out our cloud business. We were working very hard to migrate customers over to the cloud. Today, the conversation has shifted a little bit. And as you've all seen at this conference, everybody is talking about AI. And how do I make those AI investments?

And what do we need to do? And maybe more importantly, where do I want to be making those investments. And so we actually have customers that are working through this in real time with us and since we have the capability to provide a hybrid solution. If the customer wants to go on-prem, we can go on-prem with them. If the customer wants to go to the cloud, we can go to the cloud with them.

And we have some customers that are literally considering both. And it may vary, honestly, depending on the type of workload and what they're ultimately trying to do. I think AI has changed the conversation a little bit because some of the old traditional concerns have been brought right back to the forefront. And so things like security and governance and compliance, scalability. Those are all coming back to the forefront of decision-making. And I think that's where we're starting to see some of these situations where -- and we literally have customers that are considering a migration, but they're also considering expanding on-prem.

Got it. So do you think it's sort of very specific to those handful of large customers? Or do you think it's sort of a broader, across your entire installed base, these are sort of themes that you're seeing?

Yes. I mean every situation is unique, of course. But I think that -- let me put it this way. If you think about where all the focus is. And everybody wants to invest in AI. How do we become this autonomous enterprise? How do we have agents everywhere doing things that humans used to do. If you want to embark on that journey, you've got 2 paths. One school of thought is like, okay, you're going to move everything to the cloud first and then start to build your AI solutions on top of that.

Or you can work with the data where it is today and work with the existing data state and get started on AI projects today. And so I think everybody is going to have different approaches to this. I think we benefit from being able to provide that hybrid environment if somebody wants to get going today.

Got it. And maybe just as we think about sort of getting to the other side of that bell curve of cloud migrations following up on an earlier point you made, like is there a go-to-market change that also happens? I mean you mentioned the services piece and how that's sort of adapting. Like is there a broader go-to-market change it also sort of comes along with that?

There is a little bit. I mean, I'll say it's more subtle than dramatic. But again, a few years ago, we used a lot of sales calories on migration activity. And so we have a lot of people focused on that. And I will tell you, having -- not having been here a couple of years ago with this company, but having gone through SaaS transitions before, those migration deals, they always have a gravity to them. They kind of -- they just consume everybody's time and energy and attention. And they're typically big deals, big transactions.

When you free yourself from that and you're in a much more traditional land and expand kind of a motion, it can actually be very freeing for the organization. And so the team has always been focused on expansions as well as new logos. But I would say, looking ahead to '26, there'll be even more so focused on the expansion activity. How do we get adoption with some of these new AI tools that we have developed, how do we start building out use cases with customers and really expanding their activity.

Yes. You mentioned new logos. I think it's a really interesting point that kind of flies under the radar as sort of the new customers that you guys are gaining. And I think that really does speak to the product investment that you guys have made. So maybe you could just talk about sort of that new customer activity you're seeing. I know maybe small from a revenue standpoint, but maybe how you think about that part of your business?

Yes. No, it's a great question. And I would agree that it has flown under the radar a little bit. I don't feel like maybe we talk about it enough. But we are having some success with new logos. And interestingly, over the last few quarters, we've seen new logo activity on-prem. And so I do think there are opportunities out there for us, particularly in highly regulated industries. We've seen some opportunities in emerging markets.

And I think there are some things that we'll do from a product standpoint that would open up the more traditional channels and give us an opportunity to do more there as well.

Is there any theme amongst those customers, like a vertical or sort of, you mentioned regulated industries, like is there any sort of theme amongst those customers of how they're using the platform or theme of what vertical they're in, maybe?

Yes. If there's a theme, I would say it is coming back to folks that are in regulated industries where there's high compliance concerns, governance concerns. So we've seen that with some government contracts and things of that nature. We've seen that in the financial services industry. We've seen it in some of the more emerging markets where an on-prem solution is preferred. And so high level, those would probably be the key things.

Got it. You mentioned government. I know we've talked about federal a lot. The question comes up quite a bit. So maybe you could just quickly speak to sort of the federal exposure you guys have today and sort of maybe the opportunity there because that's a little bit of a bit more relevant.

Yes. I think there is still opportunity there. And again, it comes back to that notion of security and really wanted to control the environment versus having something in the cloud. And so I do think there's continued opportunity there. There's some work that I think we need to do in some cases, particularly in the U.S. federal government. But I think that for some of the other emerging markets, there's definitely opportunity there for us.

Got it. Maybe just shifting gears to competition. Like how do you see the competitive environment changing? Like you think win rates? I mean, I know the overall business is sort of stabilizing, but have you seen win rates from a competitive standpoint, stabilize? And maybe any pockets are you having the most success from a competitive standpoint?

Yes. I do think that stabilization is probably the right word. I think that, again, if you go back a couple of years ago, and it was all about getting to the cloud. And I think we felt like we were in a little bit of a race to migrate our customers to the cloud before somebody else did. And today, I think a lot of that activity has run its course. I mean there will still be migrations. There are still things that we're working on.

But again, I think the dialogue around AI has really changed that conversation. And so hopefully, that's something that starts to move the market back in our direction. And if you think about how and when you're going to be able to deploy these AI solutions, having already being a significant part of the data estate and having that security and control around it. Not to mention the context of the industry data models, I think, gives us, again, an advantage as some of these conversations start to take hold.

And maybe just like on the go-to-market side, like how do you feel about sort of broadly speaking, the go-to-market where it is today? Any big change? I mean you guys have had a lot of changes. So maybe just how do you see sort of over the next 12 months? I mean where there are still pockets of improvement or sort of areas of focus over the next 12 months?

Yes, I think that there was a lot of work done prior to my arrival and new leadership from the top down to even the department leaders. And I think that in '25, what we've seen on the whole is just much better execution. And I think all of you have had a chance to see that in terms of our externally reported numbers and the consistency that we've been able to drive over the first 3 quarters of this year. And so I think that on the whole, the team is just executing better and we've been better organized.

I think that -- I'm excited to see what can happen next year. We will focus more exclusively on expansion activity. We'll also focus on getting the AI services up and running and really start to capitalize on some of the products that we've introduced.

Got it. And you noted you're looking more at sort of the expansion side versus the migration opportunity. I mean when you think about maybe the product and the go-to-market, I think we touched a little bit on the go-to-market, but maybe just on the product side, like how do you position the product portfolio and also go to market, right, to capture that mix shift?

Yes. I would say at a high level, it's some of the themes that we've been talking about. And so what we're ultimately trying to do is position the Teradata platform as a place where you can do this type of activity. And we've built out the use cases we built out the POCs with customers, we're now going to start to operationalize that with AI services. The products that we have delivered over the course of this year, if you think about like enterprise vector store, the MCP server, the agent builder, all of these things are tools that help enable that type of work. And so we're putting all of these pieces together to be able to be that platform for AI.

And still more work to do as always. But I think that we've started to put enough pieces in place where we can have these kinds of conversations and then back it up with the services to get these projects going.

Got it. Maybe the other side of the corn will be on the cost side. As we think about margins going forward, I mean, you mentioned the services piece of the business, but where do you see the most room on margins going forward? And how do you sort of balance that with the product investment that you...

Yes. We're going through our budget cycle right now for next year and also thinking about the longer-term planning. And for us, particularly for next year, our priority is going to be on the product development side of things. And so we're looking for efficiencies across other parts of the business to be able to continue to fund product innovation. I think that there's opportunity for us on the cost of revenue side. I think there's some opportunity for us on the G&A side.

We've done a lot of work already on sales and marketing. And again, like I said, we want to try and maintain investment in -- on the product side of things. And so I think the net of all of that is if you kind of think about what we are trying to do from an overall model standpoint, we are certainly trying to drive growth. And ultimately, that's going to be the thing that carries us forward. but we also want to be able to drive incremental profit and cash flow to the bottom line.

And so even this year in '25, where we had a year where the P&L was challenged a little bit on the top line, we did some things from an expense standpoint to make sure that we could keep margins on par and make sure that we protect free cash flow. And I think that some of the changes that we've made this year will benefit us again in '26 and we'll continue to look for ways to drop incremental profit down. And when we think longer term about like how would we ultimately get to become a Rule of 40 business, it's going to be a combination of the 2. We're going to have to drive growth certainly, but we're also going to have to continue to make margin improvements.

Got it. Yes. I imagine the margin expansion is easier when the top line is...

For sure. It's a lot easier. But look, it's -- I think it's just -- it's something that you have to be dedicated to. And markets ebb and flow. And a few years ago, companies weren't getting "paid" to generate margins.

They were getting paid for growth. That ebbs and flows a little bit. Growth is still obviously very valuable and something that we want to drive as well. But I think there's an appreciation now for also having that profitability and free cash flow.

Yes. And I guess's how do you think there's sort of that sort of -- that cost versus like wanting to have that investment be positioned for growth, but also being able to drive margin expansion at the same time sort of that product investment versus...

Yes. It's kind of as I described, I think for us, we'll focus on opportunities around cost of revenue and other parts of the business so that we can preserve that R&D spending and preserve product development. And we think that when we look at the dynamics of the market around us right now, it's important for us to continue to invest in innovation to ultimately drive growth.

Got it. And when we think about free cash flow, you guys have a very healthy free cash flow profile. I mean, when you think about sort of a buyback versus M&A, sort of other uses of free cash flow, maybe just how do you think through those options sort of why 1 versus the other? And maybe just sort of the process around how you think about deploying free cash flow because it is a very important lever for you guys.

Yes, for sure. Well, I would say historically, over the last several years, we've devoted a pretty high percentage of our free cash flow to share repurchases. And we were just talking about this in another meeting. I think our share count at one point was upwards of 180 million shares, and we're now kind of in the 95 million,$96 million range. And so over the last 5 years, we've bought back a lot of stock.

This year, we committed to using 50% of our free cash flow towards share repurchases. We also just announced that we've re-upped the program. So our program was set to expire in December. We re-upped for another $500 million to go towards stock buybacks. And so we've been very committed to that, and we'll continue to be committed to that as a way to return value to shareholders.

I would say that we're also open to M&A activity. We -- in recent years, we haven't done a ton of that, but I think that we're in a position now to start looking at opportunities and looking at things that could accelerate our product road map. I would expect if we were to do something, it would be more of a technology tuck-in type deal, something that we could use our free cash flow to finance and really be a way to accelerate some of the things we're trying to do from a product standpoint.

Is there any particular area maybe within the product portfolio where you think should have you need that incremental investment or where you think that sort of the M&A bolt-on opportunity could be a little bit more accretive to the business?

I'm going to defer that one to my colleague here who runs Corporate Development for us.

Yes. I mean, I'm not -- I echo John's opinion on tech tuck-in focus and kind of financing those with cash flow and the balance sheet. I don't think I want to go into specific areas, but I think Sumeet, Arora, who's our new CPO, 6 or 7 months ago, laid out a pretty aggressive AI stack and road map a couple of months ago at possible that John mentioned. And I think we're doing a lot of that organically, but I think there's some things to accelerate or gap fill in that stack that -- and it's a very active market, right?

I think you know or everybody knows my inbox gets hit pretty routinely. So we're open to that, right? And I think we're focused on that. And like John said, I think anything that we can do to accelerate the road map, fill gaps and potentially accelerate ARR growth. That's what we're looking at.

Yes. I mean we're not looking to be a roll-up here. We're looking for things that will complement our organic activity and really accelerate some of the things we're trying to do.

Got it. Maybe just one more on the growth opportunity before we wrap it up. When you think about maybe longer term, the business does seem to be stabilizing, gotten to a good cadence here of beats. I mean, so without guiding to next year, like can you just walk me through sort of the key puts and takes as you think about the business next year, the biggest growth drivers, where you see the most opportunity, maybe just lay it all out for us to go up.

Yes. No, certainly. I mean, look, especially coming off of the heels of last year, this year, the very important first step was stabilizing the business. And there were some critical elements to that for us. One was getting total ARR growth back to positive territory. And we were able to do that in Q2. And again, in Q3, albeit with a little bit of foreign exchange benefit, but still got those -- got that metric back to positive territory and our guidance has us in positive territory again for Q4.

So that was an important milestone for us to hit and the turnaround of this. The second thing is that we continue to focus on cost efficiency. We wanted to protect margins and we wanted to protect free cash flow, and we've done those things. I think we ultimately needed to start demonstrating some consistency in the business. And I think we've been able to do that thus far this year in terms of our first 3 quarter reports.

And so that was an important effort just to kind of get us back on the stable ground, put a floor out there for the stock in terms of our free cash flow and give us a solid base to build on in '26. We did make some comments on our Q3 call about '26, and we felt strongly that we could continue to grow total ARR in '26 and we should see some continued benefit from a free cash flow standpoint from some of the things that we've done this year. And so we'll continue to focus on those 2 elements among others, but continuing to make improvement on that would be the next leg of this journey, and ultimately, driving higher growth with some of the innovation that we're doing around AI and other things.

Awesome. I know it's been great to see the business stabilize and look forward to checking back in this time next year. Thank you so much guys for being here.

Thanks again. It's been a great conference. Appreciate it.

Thank you.

Good afternoon. My name is Charlie, and I will be your conference operator today. At this time, I'd like to welcome everyone to the Teradata Third Quarter 2025 Earnings Call. [Operator Instructions] I would now like to hand the conference over to your host today, Chad Bennett, Senior Vice President of Investor Relations and Corporate Development. You may begin your conference.

Good afternoon and welcome to Teradata's 2025 Third Quarter Earnings Call. Steve McMillan, Teradata's President and Chief Executive Officer, will lead our call today; followed by John Eder, Teradata's Chief Financial Officer, who will discuss our financial results and outlook.

Our discussion today includes forecasts and other information that are considered forward-looking statements. While these statements reflect our current outlook, they are subject to a number of risks and uncertainties that could cause actual results to differ materially. These risk factors are described in today's earnings release and in our SEC filings, including our most recent Form 10-K and in the Form 10-Q for the quarter ended September 30, 2025, that is expected to be filed with the SEC within the next few days. These forward-looking statements are made as of today, and we undertake no duty or obligation to update them.

On today's call, we will be discussing certain non-GAAP financial measures, which exclude such items as stock-based compensation expense and other special items described in our earnings release. We will also discuss other non-GAAP items such as free cash flow, constant currency comparisons and 2025 revenue and ARR growth outlook in constant currency. Unless stated otherwise, all numbers and results discussed on today's call are on a non-GAAP basis. A reconciliation of non-GAAP to GAAP measures is included in our earnings release which is accessible on the Investor Relations page of our website at investor.teradata.com. A replay of this conference call will be available later today on our website.

And now I will turn the call over to Steve.

Thanks, Chad, and thanks, everyone, for joining us today. Q3 marked another quarter of solid execution as we beat our revenue and recurring revenue guidance ranges. We delivered non-GAAP earnings per share of $0.72, soundly ahead of our outlook, and we delivered free cash flow ahead of expectations. We posted our second consecutive quarter of total ARR growth ahead of our initial target of the fourth quarter. With a return to total ARR growth ahead of schedule, we have strong conviction in our durable growth path and expect this growth to continue in 2026.

We also expect the return to positive ARR growth, combined with the cost savings and productivity measures we've taken will result in meaningful free cash flow growth. Whether in cloud or on-prem, we are helping organizations build the data foundation and are delivering the enterprise context required for AI solutions, and we see the shift in our business from classic EDW towards the autonomous AI and Knowledge platform. We see enterprises reevaluating how to cost effectively deploy agentic AI. As we have noted for the past several quarters, we are seeing a resurgence of hybrid environments, which reflects a growing understanding of how enterprises can best leverage both on-prem and cloud capabilities. It isn't just about choosing between environments anymore. It's about effectively operating across both to meet diverse business needs.

Our platform is designed to give customers the opportunity to run a genetic AI at scale wherever that data resides in their business and public cloud, on-prem or private cloud. Interest in AI and in particular, Agentic AI continues to grow in virtually all industries. However, most companies are still in the early stages of deploying this technology and Teradata set squarely at the center of this revolution. We believe we provide the enterprise context that AI agents need to deliver trusted, reliable results at scale. Without this knowledge, even the most advanced models can be just a plain wrong. This shift also creates a very specific opportunity because agentic AI, with its 24/7, always on query potential can increase workloads on data platforms by up to 25x and use 50 to 100x the compute resources and what was required by previous modern analytic workloads.

Teradata is uniquely built to handle these mixed workloads and high volumes of tactical queries as enterprises deploy potentially thousands of agents and evaluate millions of relationships across thousands of tables to make a single decision milliseconds matter. We not only manage the critical enterprise data that powers these AI systems but we also can deliver the performance required at the level of performance and scale that AI needs. Teradata was built for these types of enormous workloads based on our massively parallel architecture patented workload management and query optimization that is designed to provide a high-performance environment with predictable costs that can deliver the most complex AI workloads.

Our patented QueryGrid data analytics fabric provides seamless high-performing data access, processing and movement across multiple data sources. Our industry data models are built on decades of working with the Global 1000. And through these, we bring deep context to language models, another area where we can bring unique benefits to our customers. We believe Teradata is the best autonomous AI and knowledge platform for agenetic workloads and that our platform provides the best price performance whether on-prem or in the cloud. In the quarter, we were named a leader in the Forrester Wave data management for analytics platforms and the report noted that Teradata is a good choice for organizations seeking to support hybrid cloud DMA deployments, especially where reliability, scalability and high availability are essential. We're building the capabilities for the future, to enable AI, speed and scale.

Earlier this year, we announced enterprise vector store, a capability that enables organizations to include unstructured data and their integrated Norwich Foundation. We also enhanced ClearScape Analytics with unified model ops capabilities designed specifically for agenetic AI. These provide seamless native support for open source models as well as CSP model APIs. We launched our MCP server to deliver faster context autonomously. And we've recently taken several more significant steps to further our position. In September, we announced Teradata agent Builder a suite of capabilities designed to accelerate the development and deployment of autonomous contextually intelligent AI agents. Now in private preview, it leverages open source frameworks our MCP server and deep semantic access to enterprise data across cloud and on-prem environments provided by our Knowledge platform.

Customers can develop their own agents or use ready to deploy Teradata agents to accelerate implementation and deliver rapid impact. launched at our possible event last month autonomous customer intelligence as a software and services offering that embeds Teradata agents across the customer experience or CX, journey these agents can uniquely leverage 4 decades of Teradata innovation and contextual knowledge from solving mission-critical industry-specific data challenges. Our integrated approach make sure our agents are extensions of the enterprise data platform and broader knowledge ecosystem rather than generic tools that failed to deliver meaningful impact.

To help customers transform AI pilots into production-ready genic solutions that deliver significant business value, we also launched new AI services. These new services are intended to make a genic AI, a reality at enterprise scale by combining embedded experts proven methodology and Teradata's best-in-class autonomous AI and Knowledge platform. Using a sprint-based, use case-driven approach, Teradata AI services offer flexible tiered offerings that meet organizations at any stage of their AI journey from initial pilots to enterprise-wide agenetic deployments. Unlike competitors who offer either consulting or technology, we believe Teradata uniquely delivers both enabling real-time context-aware agent decisioning that leverages our suite of AI tools, trusted data and decades of industry innovation. Working with our partners in an integrated approach accelerates deployment of autonomous intelligence, CX or otherwise, to drive measurable business outcomes.

We have forward-deployed resources with deep expertise and talent. These AI/ML engineers and data scientists are working with customers across the globe positioning Teradata as a leading AI/ML player and helping customers move from proof of concepts to production. This team is on track to complete more than 150 AI engagements with customers this year. We're also seeing a significant turn in our pipeline towards AI fuel projects.

Let's look at a few examples of wins from the quarter. These demonstrate the breadth of our offers in hybrid environments, cloud and on-prem. A multinational automotive manufacturer is expanding its Teradata cloud platform on AWS to support increasing AI/ML workloads as a combat cyber security. Executing approximately 10 million SQL statements per day, the customer is moving beyond rule-based approaches and adopting AI/ML technologies to enhance its analytical capabilities. One of the largest U.S. healthcare providers deepened its strategic alliance with us as it further scaled its Teradata cloud deployment running on Microsoft Azure. This expansion building on momentum from earlier this year underscores the providers continued confidence in our high-performance cloud platform to support mission-critical data and analytics workloads. With this expansion, the organization is further positioned to drive operational excellence and harness complex health care data at scale across its entire system.

A leading Japanese heavy industry manufacturer chose Teradata for his on-prem data platform as it transforms to a data-driven manufacturing entity and improves operational efficiency. Our Central European financial services company, we committed to us through a 7-year partnership with Teradata as a service on AWS. This enhances security provides uninterrupted operations through disaster recovery systems that match production supports monthly innovation testing and meet stringent data sovereignty requirements.

We recently held our annual customer event named possible. It was 3 days of high energy with our people, partners and customers speaking of what they are doing now with data and analytics and what they are looking ahead to do with AI and agentic AI. It was our pleasure to recognize VodafoneThree, Ooredoo and Sicredi at the conference for demonstrating exceptional creativity technical excellence and business impact through the use of AI on the Teradata AI and Knowledge platform. VodafoneThree in the U.K. was recognized for deploying an AI-supported broad detection framework by leveraging AI to detect and medicate fraud that has strengthened customer trust, improve regulatory compliance and enhanced operational resilience. Ooredoo Qatar, a leading dollar-based telco earned this award for its advanced analytical capabilities and AI-powered customer engagement strategy. This strategy is built on Teradata VantageCloud and ClearScape Analytics, which were integrated with, and run on, GCP native services. Sicredi, Brazil's largest financial cooperative was honored for its innovative use of Clearscape Analytics and our cloud platform to transform credit risk management as well as support sustainability initiatives. Most recently, Sicredi has also begun developing an AI agent to support provision analysis under Brazilian banking regulations, further strengthening its governance and risk management capabilities.

We also held our first agent builder workshop at the portable event. This hands-on workshop was oversubscribed and packed with customers keen to build AI agents on Teradata. We're in the process of launching an online agent builder experience to help accelerate the development and deployment of autonomous contextually intelligent AI agents. It will be available from our website in the coming weeks. We held our Annual Partner Forum concurrently with the portable event, and we had strong year-on-year growth in partner participation. Companies that will win in the agentic AI future will be the ones that create the most trusted, interoperable foundation that less every other AI innovation flourish. We believe that's our role in the ecosystem. We strive to be the trusted data foundation that makes everyone else's AI work better with the governance layer that led companies experiment safely. We're partnering across all layers in the ecosystem, and we have strong partner co-sell activity in the third quarter, validating the strength in our ecosystem in identifying and nurturing new opportunities.

While at our event, I hosted a forsade chat with 1 of our partners, ServiceNow. We discussed how together, we can power autonomous operations at scale by combining our enterprise-grade analytics with ServiceNow's workflow engine. Our platforms work together to enable seamless integration, governance and automation. We're collaborating to help customers realize the full potential of the data delivering intelligence and automation at enterprise scale. This is how we enable AI native transformation for our customers, empowering organizations to break down silos unlock real-time intelligence and transform every part of their business.

By combining deep analytics, trusted data and intelligent workflow automation, we're enabling organizations to move from passive data collection to active agentic operations, delivering real-time insights, proactive engagement and measurable business value. exciting stuff, and that was just one of the leading partners that participated with us. We also hosted a number of industry analysts and a comment from Constellation Research summarize our focus on helping provide context to AI, noting that we believe there is no AI without context. That context isn't just data. It's the metadata, business logic and domain know-how that make AI decisions relevant and reliable.

Without business context, even the best algorithms can't deliver the accuracy or explainability needed in real-world regulated environments. They also recognize that we are turning our decades of decision analysis experience into domain and industry knowledge model to give AI agents real context and that our context intelligence framework captures how industries actually operate, so organizations don't have to start from scratch as we help teams build agents faster with enterprise-grade performance governance and trust already built in. Our hybrid capabilities are resonating in our customer base with interest in our recent product introductions, AI factory, MCP server, an agent builder, giving us further conviction that we offer a unique value proposition.

We provide the flexibility to have consistent data, compute models, workloads, outcomes and experiences across a hybrid environment. We have full confidence in total ARR and are affirming our outlook for 2025. In our recent discussions with customers, we have seen how the Teradata Knowledge platform is ideally suited for AI workloads. AI is always on with ever-increasing agents driving massive complex query volumes. That's Teradata's sweet spot. Our ARR mix may vary as we see customers evaluating between cloud and on-prem for where to deploy the workloads as they build for their AI-enabled future. Regardless of the deployment options they choose, customers can rely on Teradata to run a genetic AI at scale and provide the context needed for trusted results. Thank you very much.

Now I'll turn the call over to John.

Thank you, Steve, and good afternoon, everyone. I'm pleased with the progress we are making this year as we've demonstrated a return to consistent execution with our third quarter in a row of meeting or exceeding our guidance metrics. And perhaps as importantly, we expect that trend to continue in Q4 as we are reiterating our guidance for the full year.

Looking at a few of the highlights for the third quarter. Total ARR growth was ahead of expectations, representing the second consecutive quarter of a return to positive growth. We exceeded the top end of our total revenue and recurring revenue guidance. We improved gross margin sequentially from Q2. We delivered considerable upside on our non-GAAP earnings per share and we increased free cash flow on a year-over-year basis for Q3 and the year-to-date. Finally, as Steve commented, we are building a solid foundation this year to deliver continued financial improvement next year. In terms of our detailed financial results for the third quarter, total ARR grew 1% as reported and flat in constant currency. This was our second consecutive quarter of a return to total ARR growth and this was driven by better retention and expansions in the quarter.

At the beginning of the year, our target was to get back to positive total ARR growth by Q4, and we are pleased to be several quarters ahead of schedule. Cloud ARR grew 11% on an as-reported and constant currency basis, and the cloud net expansion rate was 109%. As discussed on our Q2 earnings call, we expected Q3 cloud ARR growth to be below our guidance range for the year due to the pull forward of a few deals last quarter. Total revenue was $416 million, down 5% year-over-year as reported and 6% in constant currency, which was 1 point above the high end of our outlook due to higher recurring revenue. Recurring revenue was $366 million, down 2% year-over-year as reported and 3% in constant currency, which was 1 point above the high end of our outlook. Recurring revenue as a percentage of total revenue was 88%, up from 85% in Q3 last year. Services revenue was $47 million, which was consistent with our recent performance. We are seeing a transition in our services business this year as the team is moving from migration projects to delivering AI services, which we believe will provide improved performance next year.

Looking at profitability and free cash flow. Please note that I will be referencing non-GAAP numbers for expenses and margins, and a full reconciliation to GAAP results is provided in our press release. For the third quarter, total gross margin was 62.3%, which was up 70 basis points year-over-year. On a sequential basis, total gross margin was up 400 basis points, driven by improvements in both recurring and services gross margins. Recurring revenue gross margin was 68.9%, up 140 basis points sequentially. On services gross margin, we took actions last quarter to align our cost with current revenue and we made substantial improvement in non-GAAP gross margin from negative 2% in Q2 to positive 8.5% in Q3. Operating margin for Q3 was 23.6% and which was up 110 basis points year-over-year and up 720 basis points sequentially. Overall, we are seeing improving margins as a result of cost efficiency actions we started last year.

Non-GAAP diluted earnings per share were $0.72, exceeding the top end of our outlook range by $0.17. The outperformance was driven by higher recurring revenue and lower expense. We generated $88 million of free cash flow in the quarter, which was up 28% on a year-over-year basis and provides us with increased confidence in our full year outlook. And finally, in the third quarter, we repurchased approximately $30 million of our stock or 1.4 million shares. We continue to target returning 50% of our free cash flow to shareholders in the form of share repurchases this year.

Turning to our outlook for the remainder of the year. For the fourth quarter of 2025, we expect recurring revenue to be in the range of minus 1% to minus 3% year-over-year on a constant currency basis. We expect total revenue to be in the range of minus 2% to minus 4% year-over-year on a constant currency basis. And we expect non-GAAP diluted earnings per share to be in the range of $0.53 to $0.57. For fiscal '25, we reiterate our previous guidance for total ARR growth, and we are maintaining our range for cloud ARR growth. We have confidence in our total ARR target and continue to see a path to our cloud ARR range for the year. However, there are a handful of deals where customers are still assessing deployment options, which could have an impact on the mix between cloud and on-premise subscription ARR. We also reiterate our previous guidance for recurring revenue and total revenue. Given the guidance ranges that we provided for Q4, we anticipate recurring revenue and total revenue to be at the midpoint of our fiscal '25 ranges.

On free cash flow, due to our strong performance year-to-date, we are narrowing the range to the top end of our initial outlook and now expect free cash flow to be in the range of $260 million to $280 million. Finally, we are raising our non-GAAP earnings per share guidance to a range of $2.38 to $2.42, reflecting our strong performance in Q3. Based on foreign exchange rates at the end of September, we anticipate 1 to 2 points of benefit to our Q4 '25 revenue. For the full year, we do not anticipate any material currency impact. Finally, we expect the non-GAAP tax rate to be approximately 23.1% and the weighted average shares outstanding to be 96.1 million for the full year. Again, please refer to our Q3 earnings presentation on our Investor Relations website for a complete list of our 2025 outlook ranges.

In closing, we are taking actions that we believe will ultimately drive shareholder value. The first important steps were to: one, return total ARR growth to positive territory; two, focus on cost efficiencies; three, drive consistency in the business; and four, stabilize free cash flow all of which are on track to achieve this year. As we start to focus on the objectives for next year, we are prioritizing our investments to capitalize on the substantial opportunity ahead for Teradata as a leading AI and knowledge platform for the autonomous enterprise. We believe that these investments, combined with the continued optimization of our business will enable us to deliver profitable growth and higher free cash flow. Thank you all for your time today.

Now let's open up the call for questions.

[Operator Instructions] Your first question comes from the line of Erik Woodring of Morgan Stanley.

Great. Really nice to see the earnings and free cash flow upside this quarter. I think this is the first time since you began disclosing cloud ARR that we've seen sequentials be negative intra calendar year for cloud ARR. I know you mentioned that it would dip below the target range this quarter, but I guess I'd look at the 11% and say it felt a bit below maybe where you would have expected sequentials. But maybe you could just elaborate on how the quarter transpired for Cloud ARR, when and where we see that net expansion rate bottom. And maybe why we just aren't derisking 4Q a bit, just given some of your commentary around customers assessing where they're going to be deploying with Teradata? And then a quick follow-up.

Yes. Thanks, Erik. So I think on cloud, we did perform to our expectations. As we said in our Q2 earnings, we did expect that linearity to be below the full year outlook. I think as we look at the market, we're not seeing -- we're no longer seeing that kind of a headlong rush to the cloud. It's much more of a nuanced decision of how our customers can accelerate the time to value for the AI workloads that they're deploying in their environment. And we're continuing to see that pattern of customers using our hybrid capabilities. I think I've said in the past that a good proportion of our cloud customers have deployments both on-prem and in the cloud waters, and they can decide across that massive data estate that they run from a Teradata perspective, where to run that workload. And I think that's nicely evidenced actually by the fact that our total ARR growth is ahead of schedule overall, we expect it to return to growth in the fourth quarter. So being ahead of schedule from that perspective and demonstrating that we're growing overall with our customers is a good achievement as we've executed through the year. We do start to see our net expansion rate starting to consolidate. And I think as we look at the overall results for the year in terms of our guidance, we were pretty confident in our total ARR growth. And as we look to 2026, we continue to see a path for continuing ARR growth in 2026.

Okay. And then just a quick follow-up. Your comment on -- I think you used the term meaningful free cash flow growth into 2026 as to me was the most confident I've heard you sound on free cash flow looking forward in a while. Can you maybe just unpack where this confidence comes from? I'm sure it has to do with ARR growth and some of your OpEx initiatives. But just -- I know you're not going to guide to 2026, but any way you can help us think about when you talk about meaningful free cash flow growth, kind of what you're trying to tell us between the lines.

Yes. Thanks, Erik. I think you hit the nail on the head with the 2 points, but I'll just ask John to add any more color.

Yes, I think that's exactly right. I mean I think if you look at how this year is progressing, we've done a nice job on free cash flow relative to where we were at this point last year. And I think we're doing the right things and really focusing on this is a key driver for us, certainly getting total ARR back to growth territory has had a positive impact. And then the cost actions that we've taken last year and this year as well are also supporting that number. And so we feel like we're putting the right pieces in place to continue that improvement next year.

Our next question comes from Radi Sultan of UBS.

First for Steve, last quarter, we talked about -- I think it was roughly 1/3 of pipeline, including an AI component. So I guess, first, like how did that track this quarter? You mentioned the agent offerings, MCP server, like is there any area in particular within the AI portfolio moving the needle? And any way to think about how these AI discussions more broadly are impacting competitive win rates?

Yes. Thanks for the question, Radi. Yes, we're continuing to see that the AI influence pipeline increase saw increases we went through Q3, which is really great to see. We have supported that with a fantastic set of innovation and the leases from a product perspective. Our new Chief Product Officer, Sumeet, is making a real difference there. And in terms of -- we're measuring our innovation releases in terms of time from concept to press release. And I think as evidenced by the discussions we had with our customers at our most recent marketing event, they're really seeing those innovations as something that Teradata can provide in a holistic way to enable them to deploy agentic AI workloads, whether it's from our enterprise vector store capabilities, our MCP server, our agent builder capabilities or model ops where we can include language model capabilities. So all of these, I think, are coming together. And one of our customers actually, I think, said it best where they said, Teradata is one provider in this area who is really putting it all together.

But I think the most interesting thing, Radi, from a technology perspective is that we are seeing that the Teradata technology platform is really built for these AI workloads. When you think about an always-on AI agent, essentially begin to execute thousands of queries and complex queries. So really large volumes of queries executing concurrently inside an environment with different types of workload our architecture and site Teradata or massively parallel architecture combined with our workload management and query optimization allows our customers to run those types of queries and the AI agents that they have developed to run those queries more effectively and efficiently than anybody else.

Awesome. And then second for John, you've been in the seat a couple of quarters now strung together a couple of nice quarters. I guess is it fair to think that your approach to guidance being relatively consistent into join? And maybe are there any leading indicators or KPIs that you're looking at that give you confidence in the outlook, especially around Q4?

Yes. Thanks for the question. And I would say from an overall standpoint, I guess, in terms of guidance and our philosophy on it, we try to call it as we see it. And so we take a look at our forecast. We -- we do have a number of KPIs that we'll look at from a pipeline to our expenses to the revenue model, et cetera. There's a whole bunch of metrics that we'll take a look at and roll all of that up. When you talk about Q4 in particular, you're now getting down to the last few months and we're literally going deal by deal. And so we've got that kind of granularity in terms of how we ultimately roll up the forecast and then our resulting guidance from it.

Our next question comes from Yitchuin Wong of Citi.

Steve, maybe I'll start with you, great to see everyone. I want to just follow on what Radi was asking, like around the competitive age, like the agentic AI strategy with autonomous out as possible and then agent builders like 3D position Teradata like directly against some of this road map of your larger hyperscaler platform and then even compared to the Databricks and Snowflake. Can you kind of help us understand what is really the longer-term durability competitive advantage that you see that Teradata can compete in the space? And is it more the hybrid cloud environment that you've been talking about and then the small enterprise side the IP within your decades of experience, maybe we can start there?

Yes. I think -- thanks for the question, YC. I think fundamentally, what senses our part is actually our technology mode that we have already. as the set of patented capabilities that allow us to execute these workloads in the most effective and efficient way. And we can do that both on-prem and in the cloud. So really being able to deliver that hybrid environment to customers is clearly a differentiator for us. We announced earlier in the year our AI factory, which essentially combines a lot of capabilities together. We partnered with NVIDIA in terms of the development of that AI factory. That gives us a fantastic base for future on-prem capabilities. We're looking forward to the next release of our Teradata technology platform, which will have GPUs built right into the platform. in terms of executing that workload. But our customers are already using their Teradata on-prem platform actually operate and execute AI workloads today in a very reliable way. And we're seeing it both in a real hybrid context, so both on-prem and in the cloud. .

At the end of the day, we see this as being a battle of the query engine, and we believe that our query engine is the best query engine to deliver AI type workloads and to be that true knowledge platform in terms of building enterprise context for our customers and that's built on all of the capabilities and solutions that we've developed over the last 40 years for our customers, we understand the domains around customer experience or supply chain management, and we understand the debate across all of the industries. So all of these things combined together to give us our unique position, and we are really excited about getting that message out to the marketplace and demonstrating that to customers on a day-to-day basis.

Understood. Maybe one for John here. You talked about like the much improved service gross margin to positive have during the quarter. It's great to see an inflection there. Could you kind of help us double quick on some of these actions? I know we heard talk about use the team is starting to leverage more FTE or maybe even AI FTE here within the sales motion, especially with these new AI use cases. Is this something that expected to go forward that could help drive better margin here or even efficiency driving like AI, leveraging AI within the company that you touched on a little bit during possible as well?

Yes. So I think a couple of different questions in there. I think in terms of the services business overall, to be perfectly honest, a lot of that is just rightsizing the organization for the current revenue stream that we've got there. We saw some headwinds this year due to higher migration activity in the prior year. And so for us, in the first couple of quarters, we were a little bit behind in that from a cost structure standpoint, and we fixed that in the second quarter, and we saw a nice rebound in Q3, and we think we've got some room to go in Q4. And so I think, again, there, it's just aligning the costs with the anticipated revenue. In terms of your broader question around margins overall and some of the things that we're doing with AI from an internal standpoint, there's actually quite a bit. And I won't do it justice, but I would encourage you to check out some of the presentations at our possible conference. We had one that talked specifically about some of the things that we're doing internally. And there's a whole work stream around this that's really touching all parts of the business from cost of revenue through the operating lines.

I'll just add to that, is. I think from an AI services perspective, we're seeing customers have a real appetite to deploy real solutions. So with the launch of our customer intelligence framework and also backing that up with low consulting expertise, folks that can actually implement AI solutions inside our customers we're really pivoting our consulting and services capability to delever and something that we see is supply-constrained marketplace in terms of folks that actually know how to deploy the solutions inside our customer base. So our most recent press release in the last couple of weeks around AI services and the capabilities that we have to help enable our customers in this market is super exciting. And obviously, of course, working alongside our partners to deliver those capabilities to the market is super important for us.

Yes. Hopefully, the traction continues.

Our next question comes from Chirag Ved of Evercore.

Following up on one of the prior questions here. I was wondering whether you could speak to the underlying trajectory of progress on-prem at this point over the next couple of quarters even qualitatively. Should we index more on the on-prem side of the business when we're looking out or and perhaps moderating cloud growth? And then any comments you might have on the associated margin and pricing implications, if you could share that?

Yes, I'll start and maybe John can make some comments. So I think -- Chirag, thanks for the query. I think we are definitely seeing that our on-prem is stabilized, and we're seeing a rate of change and improvement and that's due to -- from an on-prem perspective, both retention and expansion of those on-prem environments. On that, we certainly are happy with our retention rates. It's in line with enterprise software overall. But the fact is we'll take growth wherever we see it, right? And we're well positioned to take advantage of growth in this hybrid environment that some of our customers have got. But we're also really well placed to take advantage of on-prem growth for data sovereignty requirements or where the data gravity is on-prem. But we also see the fact that we can grow in the cloud successfully with our customers. We're seeing our expansion rates in the cloud pick up as we've gone through this year in comparison to some of our other years. And we expect that to continue from an expansion perspective. And so I think we've -- we're well placed to take advantage of the opportunity that's in front of us, and we'll see that growth in terms of that hybrid platform that we offer to the market.

Okay. Got it. That's really helpful. Maybe just one more. Great to see more of a focus on AI services, living consulting really speaks to the importance and percolation of this technology. Looking ahead, do you see consulting revenue stabilizing a bit at this point, driven by the focus on delivering AI services? Or is this still a category that you're involved with, but starting to or continuing to shift over to your partner ecosystem?

Yes. I think we've -- at our cool, we're a technology company. We're about ARR growth. We do consulting and services to support technology ARR growth and clearly, the margin profile for that is where we want to operate. We've created that headroom as we've discussed, in terms of creating that space for our partners to operate successfully with us. But I think every great technology organization needs a great consulting and services capability to support that technology value proposition. And it's great to be able to see our consulting and services organization pivot towards these AI services. So the relevance in the marketplace can increase and it can help existing customer base and new customers that we come across deploy these AI solutions, and we see it actually as a great competitive differentiator. We've got a go-to-market motion now that supports a forward deployed engineering model to get POCs and to our customers. But our consulting and services teams and their partners are going to ensure that they take those POCs from that proof of concept into reality and into production. And we've already seen success with the customers in terms of taking real problems and business domains that they have and turning into production-ready capabilities. So really [ tame ] to value from an AI perspective is super important, and we see our AI services capabilities is something that's going to support that.

[Operator Instructions] Our next question comes from Matthew Hedberg of RBC Capital Markets.

This is Mike Richards on for Matt. Maybe just double clicking on that dynamic where customers are assessing the deployment often. Just curious, is that a result of the announcement of the hardware refresh next year, where maybe some customers are seeing the transformation you're bringing to the on-prem offering and now it's a bigger decision of whether or not to stay or move to the cloud and then just any early feedback you've gotten on that decision to have the big refresh?

Thanks, Mike, for the question. No, I would say it's got anything to do with the technology platform that we're coming out with next. I think the technology that we've haven't in place today is actually enabling some of these decisions, both in terms of things like the AI factory, which are available today on the technology stack that we have. It's actually given our customers exactly what they want. They want the choice of deployment. We want to be able to choose where they put the workloads. And we offer our customers a workload first deployment model. So they can choose whether they want to run the workload in the cloud or whether they want to run it on-prem, and so that's the decision making that our customers are going through. And the fact that we offer those technology capabilities in that hybrid environment is essentially giving our customers the choice of deployment.

Our next question comes from Raimo Lenschow of Barclays.

Congrats from me as well on a great quarter. The quick question, Steve, more for you. If you think about the debate of where AI gets that data from there is kind of a big debate kind of is it coming out of the operational data stores and Oracle, et cetera, is making no more out of like the data warehouses like you guys or more out of the data lakes. Can you speak to that, how you see that playing out? Or is that different use cases will have like a different data foundation?

Raimo, you answered the question right at the very end, I think we are actually seeing customers want to get the best out of their data no matter where it sits. That's why we love QueryGrid as our technology to be able to combine all of these different data stores together. So no matter where the data is in the ecosystem, they can take that in a highly governed, reliable way and combine it together, whether it's coming from the data lake or whether it's coming from an enterprise data warehouse, and they can feed that into a language model in a very trusted environment. And that's what we're really delivering and offering to our customers. So I think this is all about -- if you think about AI solutions, they have to be trusted. They have to be ethical. You have to be able to track back through it, and they have to run efficiently and effectively. And that's where the Teradata platform enables our customers to do by combining all of those data sources together.

Our next question comes from Derrick Wood of TD Cowen.

This is for you, John. You guys had nice outperformance on recurring revenue in Q3. But now for Q4, we had been kind of assuming low single-digit growth implied from your guide last quarter to now low single-digit decline. So was there any kind of pull forward of deals from Q4 to Q3? Or what would you call out on the change in the Q4 growth assumptions? And if I could just squeeze one other in on the cloud having kind of dropped to 109. Just remind us what the main drags of this number are? And any color on kind of when and where this could start to stabilize and perhaps move back up?

Yes. Thanks, Derrick. So on the recurring revenue side of things, I think our guidance for the year has actually been fairly consistent on the recurring revenue piece. We did have some variability, if you look quarter-to-quarter, and that comes from the upfront portion of the on-premise subscriptions. And so depending on the mix of that in any given quarter, you might have more upfront revenue which would otherwise throw off your expected linearity. In terms of the net expansion rate, we have seen some consolidation on that. If you look at what we've done historically and even for this year, we're still on track for the same. About 50% of our expansion rate is coming from migration activity and the remainder is coming from expansions with existing customers. And so we see that continuing into Q4 right now, you're seeing those rates consolidate and so the net expansion rate is pretty close to what you're seeing for the cloud ARR growth overall.

Our panel's question comes from Wamsi Mohan of Bank of America.

Yes. I think, Steve, you mentioned sort of cost takeout helping free cash flow into next year. Can you help us maybe think about just the absolute sort of OpEx trajectory going from here into '26, how are you thinking about the route of progression from here? And if I could, just I know federal is not really very large for you guys, but are you seeing any impact at all from the government shutdown?

Yes, I'll take the first -- the last question, first Wamsi. No, we're not seeing any impact to our revenues as a result of the federal shutdown. And then just from an OpEx perspective, clearly, we've taken some fairly major restructuring activities through the year and a lot of them in the kind of June time frame and then into the September time frame. So we are expecting full year of impacts and benefits to essentially -- ultimately our free cash flow position as we move into 2026. So we are expecting that to amplify. And I think in relation to one of the other questions, John head it on the head, we're expecting that free cash flow growth to come from both our ARR growth expectations for '26 and also the operational efficiency effectiveness, productivity measures we've executed in 2025.

And our final question of today comes from Patrick Walravens of Citizens.

Great. John, this ones for you, too. And I know this was a good quarter, but divide your free cash flow by the revenue, you get like 21%. Not putting a time frame on it, I think where can net free cash flow margins go.

Yes. No, it's a good question. I think it's somewhat related to what Steve just commented on in terms of the operating leverage. And if you look -- and just step back and look at what we did this year, with revenue headwinds, we don't guide on operating margin specifically. But I think if you do the math in reverse engineer, you're going to mind that the operating margin has to be pretty flat and comparable with where we were last year. So that means in the face of revenue headwinds, we're still able to capture that margin percentage. And we've done some things from an operational standpoint and a cost efficiency standpoint that will continue to benefit us next year. And so I won't give you a number today. But suffice to say that we've done some things this year that we think set us up well for next year from a margin and a cash flow standpoint.

Thanks, Pat, for the question. And thanks, everyone, for joining us today. We are absolutely committed to show what the AI future holds for our customers and what our differentiated platform and capabilities can deliver. As we continue our focus on execution, we're really confident in our outlook, and we are looking forward to updating you all next quarter. Thank you very much. And operator, you can end the call.

Thank you. This concludes today's conference call. You may now all disconnect your lines.