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DATE

Tuesday, Aug. 4, 2026 at 4:30 p.m. ET

CALL PARTICIPANTS

• Investor Relations - Chad Bennett
• President and Chief Executive Officer - Stephen McMillan
• Chief Financial Officer - John Ederer

TAKEAWAYS

• Recurring Revenue -- $363 million, up 3% year over year (2% in constant currency), driven primarily by the timing of revenue recognition related to on-premise subscriptions.
• Total ARR -- $1.509 billion, representing 1% growth year over year (2% in constant currency), reflecting the company's differentiated hybrid data platform capabilities.
• Public Cloud ARR -- $686 million, up 8% year over year (9% in constant currency), as the company continues its transition to cloud-based services.
• Non-GAAP Diluted EPS -- $0.69, exceeding the high end of the outlook range by $0.12, reflecting the outperformance in recurring revenue.
• Total Revenue -- $410 million, flat year over year and 2 percentage points above the high end of the guidance range.
• Non-GAAP Operating Margin -- 21.5%, a significant expansion from 16.4% in the second quarter of 2025, driven by operational discipline and a higher mix of recurring revenue.
• Adjusted Free Cash Flow -- $127 million, up from $39 million in the prior year period, reflecting improved recurring revenue linearity and a strengthened balance sheet.
• Consulting Services Revenue -- $39 million, down 24% year over year, though project backlog is reportedly growing as the company optimizes its cost structure.
• Net Cash Position -- $323 million at the end of the second quarter, representing a year-over-year increase of $528 million.
• Share Repurchases -- $40 million utilized to repurchase approximately 1.3 million shares, with a target to use 50% of adjusted free cash flow for future buybacks.
• Debt Repayment -- $450 million term loan balance was fully retired during the second quarter, further strengthening the capital structure.
• Fiscal 2026 Non-GAAP EPS Guidance -- Increased to a range of $2.65 to $2.73, up from the previous outlook.
• Fiscal 2026 Adjusted Free Cash Flow Guidance -- Increased to a range of $330 million to $350 million, reflecting strong first-half performance and debt payoff.
• Q3 2026 Recurring Revenue Guidance -- Expected range of -4% to -2% year over year due to front-loaded revenue recognition in the first half of the year.
• Q3 2026 Total Revenue Guidance -- Expected range of -6% to -4% year over year.
• Fiscal 2026 Total ARR Growth Guidance -- Reaffirmed at 2% to 4% year over year.
• Cloud Gross Margin -- Continued to show year-over-year improvement as the business scales.
• Q3 2026 Non-GAAP Diluted EPS Guidance -- Expected to be in the range of $0.55 to $0.59.
• Inventory -- Sufficient inventory exists for the current platform through fiscal 2026 following strategic pre-buying in fiscal 2025.
• Operating Margin Year-to-Date -- 24.5%, up 540 basis points versus the first half of 2025.
• Fiscal 2026 Other Expenses Guidance -- Adjusted to approximately $19 million.
• GAAP Net Income -- $46 million ($0.48 per diluted share), compared to $9 million ($0.09 per diluted share) in the second quarter of 2025.

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RISKS

• CFO Ederer warned of quarterly declines in the second half of the year, stating, "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," due to ASC 606 revenue recognition timing.
• CEO McMillan identified a significant execution gap in the industry, stating, "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."
• CFO Ederer cautioned regarding potential cost increases for the new Teradata Factory platform, noting, "there is where we could potentially see some of the pressures from the supply chain and the increased pricing."

SUMMARY

Management at Teradata Corporation (TDC -3.00%) reported that the company is transitioning to a "knowledge platform" model under its Teradata 3.0 initiative. This strategy prioritizes the deployment of agentic AI through a hybrid infrastructure that supports both public cloud and sovereign on-premise environments. The company completed a significant debt reduction during the quarter and increased its profitability and cash flow expectations for the fiscal year. Executives noted that current market demand is increasingly focused on operationalizing AI pilots and addressing data context challenges that have historically limited production-grade execution.

• CEO McMillan characterized the current strategic phase as "Teradata 3.0," stating the company has "retooled our business for this clear opportunity of autonomous intelligence."
• The Teradata Autonomous Knowledge Platform achieved general availability in early Q3 2026, which includes the AI Studio and the natural language interface known as Tera.
• The company launched Teradata Factory in partnership with Dell Technologies to provide on-premise, GPU-integrated infrastructure for organizations requiring data sovereignty.
• CFO Ederer noted that cloud migration activity has passed its peak from one to two years ago, stating the company is "now on the other side of that bell curve" and is focused on hybrid expansion.
• CEO McMillan identified "context fragmentation" as a primary barrier to AI ROI, noting that 77% of executives report that only "20% or less of their data is sufficiently described for agents to use reliably."
• Teradata was named a "visionary" in the 2026 Gartner Magic Quadrant for AI Platforms for Data Science and Machine Learning in its first year of participation.
• Management confirmed that the majority of total ARR growth is expected to occur in the fourth quarter, consistent with historical seasonal selling patterns.

INDUSTRY GLOSSARY

• Agentic AI: An advanced form of artificial intelligence involving autonomous agents capable of independent reasoning and multi-step task execution.
• Teradata Vantage: The company's flagship data platform designed to integrate and analyze large-scale enterprise data across multi-cloud environments.
• ASC 606: The accounting standard governing revenue from contracts with customers, which often requires upfront recognition for certain on-premise subscription components.
• Total ARR: Annual recurring revenue, representing the total annual value of all active and contractually binding term-based contracts at period end.
• Teradata Factory: An integrated on-premise infrastructure solution developed with Dell Technologies that includes GPUs to support private AI workloads.
• RAG (Retrieval-Augmented Generation): An AI framework that retrieves specific data from an external knowledge base to enhance the accuracy of large language model responses.
• Model Context Protocol (MCP): An open standard for building connectivity between AI agents and the data sources or tools they interact with.

Full Conference Call Transcript

Chad Bennett: 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 SEC 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 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.

Stephen McMillan: 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've 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. 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 expertise in 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, Tera is our agentic coworker, the natural language interface that gives every user governed access to enterprise data and agents. Tera 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. The agent enables advanced multi-step analytics on data that's already there with no costly movement or integration complexity. We 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. We're not just a data 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, while 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 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.

John Ederer: 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 variability 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, primarily 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. On 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. While 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. Thank you all very much for your time today, now let's open up the call for questions.

Operator: Your first question comes from the line of Erik Woodring.

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.

Stephen McMillan: Yes, 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?

John Ederer: 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.

Erik Woodring: Okay, I appreciate that color, guys. 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?

John Ederer: 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.

Operator: Your next question comes from the line of Radi Sultan.

Radi Sultan: 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.

Stephen McMillan: Radi, 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 that'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 conjunction and 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.

Radi Sultan: 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, stock buyback, bolt-ons, R&D, especially given the product launch cadence? I would love to just dig into your thinking there as you think about uses of capital from here.

John Ederer: Yes, sure, Radi. Happy to. Appreciate the question. And yes, 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.

Operator: Your next question comes from the line of Yitchuin Wong.

Yitchuin Wong: Steve, definitely good to see some of the call-outs among your AI use cases getting some traction for your customers. Like we certainly heard a lot of like 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?

Stephen McMillan: 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 it's 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 monetizing that as we go along.

Yitchuin Wong: 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?

John Ederer: 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 still continue to see some of that activity, but much less going forward.

Operator: Your next question comes from the line of Patrick Walravens.

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?

Stephen McMillan: 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. And the sales teams are excited. They're energized to take these messages to our customers. And 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 with them what they can do with the Teradata platform, with all of these new announcements, it's certainly opening up opportunities for us.

Patrick Walravens: 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, there's just a lot more consumption of data. How is that playing out for you guys? I mean, are there situations where 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?

Stephen McMillan: 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. And 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 front of customers, that's what's going to enable us to win.

Operator: Your next question comes from the line of Matthew Hedberg.

Matthew Hedberg: I guess, maybe for John, 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 on-prem, 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?

John Ederer: 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.

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

Stephen McMillan: 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, 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.

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

James 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?

Stephen McMillan: 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. 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.

What I would do 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 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.

James Wood: 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?

John Ederer: 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.

Operator: Your next question comes from the line of Raimo Lenschow.

Raimo Lenschow: Congrats from me as well. 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 et cetera. 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?

Stephen McMillan: Yes, I'll let John talk to the linearity again, but just from a market perspective, 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 Q2?

John Ederer: 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.

Raimo Lenschow: Okay. Perfect. 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 now 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?

Stephen McMillan: 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, 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, 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.

Operator: Your next question comes from the line of Wamsi Mohan.

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 have a follow up.

Stephen McMillan: 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 my total ARR growth is really what we're focused on. I've said in the past that over half the number of customers that we have in the cloud with us operate in 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. And that 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.

Wamsi Mohan: Okay. And I think in your opening comments you cited anticipated incremental gains in 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?

Stephen McMillan: 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 renewals 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.

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

Stephen McMillan: 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.

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