Q2 2026 Teradata Corp Earnings Call

Speaker #1: 2026, Q2 earnings call. All lines have been placed on mute to prevent any background noise. After the speakers' remarks, there will be a question-and-answer session.

Speaker #1: If you would like to ask a question during this time, simply press * followed by the number 1 on your telephone keypad. If you would like to withdraw your question, press * followed by the number 1 again.

Speaker #1: Thank you. I would like to hand the conference over to your host today, Chad Bennett, Senior Vice President of Investor Relations and Corporate Development.

Speaker #1: You may begin your conference.

Speaker #2: Good afternoon, and welcome to TERADATA's Q2 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.

Speaker #2: 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.

Speaker #2: 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.

Speaker #2: 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.

Speaker #2: 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.

Speaker #2: 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.

Speaker #2: And now, I will turn the call over to Steve.

Speaker #3: 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.

Speaker #3: 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.

Speaker #3: 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, where also increasing the range for adjusted free cash flow to $330 million to $350 million.

Speaker #3: 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.

Speaker #3: 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.

Speaker #3: 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.

Speaker #3: We are here to change that. We see a clear vision for this agentic AI era. We call it TERADATA 3.0, and we have retold our business for this clear opportunity of autonomous intelligence.

Speaker #3: TERADATA's robust hybrid data foundation and 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.

Speaker #3: 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.

Speaker #1: 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 is not built to support them.

Speaker #3: 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.

Speaker #1: We're here to change that. We've set a clear vision for this agentic AI era: we call it TERADATA business for this clear opportunity of autonomous intelligence.

Speaker #1: TERADATA is robust, hybrid data foundation, and used at many of the world's leading organizations as essential to help enterprises deploy the business infrastructure needed to get ROI from their AI initiatives.

Speaker #3: 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.

Speaker #1: The mission-critical 3.0—and we have retold our 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.

Speaker #3: 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.

Speaker #1: 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.

Speaker #3: 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.

Speaker #1: 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.

Speaker #3: ActiveCompute and ElasticCompute 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.

Speaker #1: 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.

Speaker #3: 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.

Speaker #1: 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.

Speaker #3: 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.

Speaker #1: 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.

Speaker #3: Combined with our AI services consultants, we bring years of domain expertise and sophisticated analytics AI initiatives can move reliably from concept to production-grade execution at speed.

Speaker #1: It delivers private AI and enterprise-grade performance in a single, integrated system built with Dell Technologies. And with integrated CPUs and GPUs, customers can run the models that fit their needs—including foundation models—entirely on-prem.

Speaker #3: 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.

Speaker #1: 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.

Speaker #3: 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.

Speaker #1: Combined with our AI services consultants, we bring years of domain expertise and sophisticated analytics—AI initiatives can move reliably from concept to production-grade execution at speed.

Speaker #3: 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.

Speaker #3: 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.

Speaker #1: 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.

Speaker #3: 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.

Speaker #1: 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.

Speaker #3: 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.

Speaker #1: 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.

Speaker #3: 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.

Speaker #1: 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.

Speaker #1: I'm pleased to report that the TERADATA Autonomous Knowledge Platform, including its AI Studio component, reached general availability in the early Q3, a couple of months after we announced it.

Speaker #3: We also delivered expanded data access through upgraded native OpenTable format support, enabling customers to query seamlessly across more distributed data without unnecessary movement or duplication.

Speaker #1: 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.

Speaker #3: 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.

Speaker #1: 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.

Speaker #3: 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.

Speaker #1: We also delivered expanded data access through upgraded native OpenTable format support, enabling customers to query seamlessly across more distributed data without unnecessary movement or duplication.

Speaker #3: 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.

Speaker #3: 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.

Speaker #1: 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.

Speaker #1: 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.

Speaker #3: As our teams take our new platform and the AI narrative to the market, they're receiving positive responses from customers and support for the need to activate the intelligence across their enterprise.

Speaker #3: 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.

Speaker #1: 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.

Speaker #1: 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.

Speaker #3: 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.

Speaker #1: As our teams take our new platform and AI narrative to the market, they're receiving positive responses from customers and support for the need to activate intelligence across their enterprise.

Speaker #3: 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.

Speaker #1: 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.

Speaker #3: 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.

Speaker #1: 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.

Speaker #3: 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.

Speaker #1: 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.

Speaker #3: 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.

Speaker #1: 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.

Speaker #3: And a major US healthcare company expanded its on-prem production system and support of government regulations. Our increased engagement in the agentic AI space has not gone unnoticed.

Speaker #1: 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.

Speaker #3: 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.

Speaker #1: 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.

Speaker #3: 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.

Speaker #3: 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.

Speaker #1: And a major U.S. healthcare company expanded its on-prem production system and support of government regulations. Our increased engagement in the agentic AI space has not gone unnoticed.

Speaker #3: Anchored by our new Autonomous Knowledge Platform, built for the agentic age. And we back that vision with delivery, bringing key components of the platform to general availability within a quarter.

Speaker #3: Our hybrid capabilities, and our on-prem strength in particular, continue to resonate with customers running the most demanding and regulated workloads for a solid data foundation is not discretionary.

Speaker #1: 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.

Speaker #1: 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.

Speaker #3: 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.

Speaker #1: 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.

Speaker #3: John will cover in more detail including the areas we are raising our expectations. We remain focused on converting this momentum into durable, profitable growth and lasting value for our shareholders.

Speaker #1: 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.

Speaker #3: Now, over to you, John.

Speaker #1: 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.

Speaker #1: Our hybrid capabilities—and our on-prem strength, in particular—continue to resonate with customers running the most demanding and regulated workloads, for a solid data foundation is not discretionary.

Speaker #1: 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.

Speaker #1: 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.

Speaker #1: John will cover this 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.

Speaker #1: 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.

Speaker #1: Now, over to you, John.

Speaker #2: 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.

Speaker #1: 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.

Speaker #2: grew 3% year over year, marking our third consecutive quarter of positive Recurring revenue 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.

Speaker #1: 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.

Speaker #1: Second quarter total revenue was $410 million, flat as reported and in constant currency, which was two points above the high end of our outlook due to higher recurring revenue.

Speaker #2: 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.

Speaker #1: Second quarter recurring revenue was $363 million, up 3% year over year as reported and 2% in constant currency, which was three points above the high end of our outlook.

Speaker #2: 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.

Speaker #1: 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.

Speaker #2: 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.

Speaker #1: 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.

Speaker #2: Second quarter total revenue was $410 million, flat as reported and in constant currency, which was two points above the high end of our outlook due to higher recurring revenue.

Speaker #1: 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.

Speaker #2: Second quarter recurring revenue was $363 million, up 3% year over year as reported and 2% in constant currency, which was three points above the high end of our outlook.

Speaker #1: 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.

Speaker #2: The outperformance was primarily due to the timing of revenue recognition related business. Second quarter consulting services revenue was $39 million, down 24% year over year as reported and 23% in constant currency.

Speaker #1: 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.

Speaker #2: 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.

Speaker #1: 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.

Speaker #1: 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.

Speaker #2: 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.

Speaker #2: 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.

Speaker #1: 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.

Speaker #2: 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.

Speaker #2: 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.

Speaker #1: Non-GAAP diluted earnings per share were $69 cents, exceeding the top end of our outlook range by 12 cents. The outperformance was primarily driven by higher recurring revenue.

Speaker #2: 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.

Speaker #1: 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.

Speaker #1: 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.

Speaker #2: 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.

Speaker #1: 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.

Speaker #2: Non-GAAP diluted earnings per share were $69, exceeding the top end of our outlook range by 12 cents. The outperformance was primarily driven by higher recurring revenue.

Speaker #1: 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.

Speaker #2: 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.

Speaker #1: 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.

Speaker #2: 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.

Speaker #1: 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.

Speaker #2: We continue to target using 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.

Speaker #1: 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.

Speaker #2: Given the strengthened balance sheet, this will enable us to make future strategic investments in AI, as well as continue our stock buyback program and be opportunistic on strategic M&A.

Speaker #1: 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.

Speaker #2: 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.

Speaker #1: 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.

Speaker #2: 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 last year.

Speaker #1: 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.

Speaker #2: 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.

Speaker #1: For the third quarter of 2026, recurring revenue is expected to be in the range of minus 4% to minus 2% year over year, total revenue is expected to be in the range of minus 6% to minus 4% year over year, and non-GAAP diluted earnings per share is expected to be in the range of $55 cents to $59 cents.

Speaker #2: While our guidance for the year remains unchanged, we did experience higher growth over the first half of the year and expect the second half of the year.

Speaker #2: 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.

Speaker #1: 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.

Speaker #2: 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.

Speaker #1: 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.

Speaker #2: For the third quarter of 2026, recurring revenue is expected to be in the range of minus 4% to minus 2% year over year. Total revenue is expected to be in the range of minus 6% to minus 4% year over year, and non-GAAP diluted earnings per share is expected to be in the range of 55 cents to 59 cents.

Speaker #1: We significantly strengthened our balance sheet, generated very strong free cash flow, and continue to execute our profitable gross 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.

Speaker #2: 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.

Speaker #1: Thank you all very much for your time today. Now, let's open up the call for questions.

Speaker #2: We will now begin the question and answer period. If you would like to ask a question during this time, simply press star, followed by the number one on your telephone keypad.

Speaker #2: 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.

Speaker #2: If you would like to withdraw your question, press star, followed by the number one again. In the interest of giving everyone an opportunity, we appreciate that you limit yourself to one question one follow-up.

Speaker #2: 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.

Speaker #2: Your first question comes from the line of Erik Woodring. Erik, your line is now open.

Speaker #3: Great. Thank you so much for taking my question, Skys. And I just have one other quick follow-up. So I guess John and Steve, it's a combined question for you guys.

Speaker #3: 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.

Speaker #2: Thank you all very much for your time today. Now, let's open up the call for questions.

Speaker #1: We will now begin the question and answer period. If you would like to ask a question during this time, simply press star, followed by the number one on your telephone keypad.

Speaker #3: 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.

Speaker #1: If you would like to withdraw your question, press star followed by the number one again. In the interest of giving everyone an opportunity, we appreciate it if you limit yourself to one question and one follow-up.

Speaker #3: Would 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.

Speaker #1: Your first question comes from the line of Erick Woodring. Erick, your line is now open.

Speaker #3: Just help us understand some of the moving pieces that maybe would make us feel more at ease understanding the shape of the year. I'm going to quick follow-up.

Speaker #3: Great, thank you so much for taking my question, Skys. I just have one quick follow-up. This is a combined question for you, John and Steve.

Speaker #3: Thanks.

Speaker #4: Yeah. 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.

Speaker #3: 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.

Speaker #4: 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.

Speaker #3: As I think about your guide, can you help us understand why the 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?

Speaker #3: 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.

Speaker #4: 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.

Speaker #3: 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.

Speaker #4: 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.

Speaker #3: Thanks.

Speaker #4: Yeah. Hi, Erick. 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.

Speaker #4: 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.

Speaker #4: 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.

Speaker #4: John, do you want to talk a little bit about?

Speaker #3: Yeah. 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.

Speaker #4: 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.

Speaker #4: And as they are evaluating our new technologies, they are making those choices so that our overall total ARR is in a good position. That’s why we reaffirmed our guidance for the full year.

Speaker #3: And feel like we're right on right in line and on target with achieving those. What has changed this year has been the linearity on the revenue side in particular.

Speaker #4: 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.

Speaker #3: 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 then 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.

Speaker #3: 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.

Speaker #4: John, do you want to talk a little bit about?

Speaker #3: Yeah. Erick, 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.

Speaker #3: 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.

Speaker #3: And we 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.

Speaker #3: And then, John, maybe just a quick follow-up. You just beat two Q by 14 cents. I think the full year earnings guide went 9 cents higher.

Speaker #3: And so, due to the nature of ASC 606 accounting, which we talked a little bit about on the Q1 call and then 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.

Speaker #3: Just what are some of the earnings headwinds that I guess you're encountering in the second half? Because inherently, if you're if two Qs beating by more than you're raising the full year, second half EPS needs to come down a little bit.

Speaker #3: So just what are the incremental headwinds we need to be taking into account? Thanks so much.

Speaker #3: 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.

Speaker #5: Yeah. Yeah. 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 to the earnings side as well.

Speaker #3: 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.

Speaker #5: 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.

Speaker #5: We raised that again but the timing of when those impacts hit has shifted on us. Operator, we'll take the next question.

Speaker #3: And then, John, maybe just a quick follow-up. You just beat two Q by 14 cents. I think the full year earnings guide went 9 cents higher.

Speaker #3: Just what are some of the earnings headwinds that I guess you're encountering in the second half? Because inherently, if you're if two Qs beating by more than you're raising the full year, second half EPS needs to come down a little bit.

Speaker #3: So, just what are the incremental headwinds we need to be taking into account? Thanks so much.

Speaker #2: Your next question comes from the line of Radi Sultan. Your line is now open.

Speaker #2: Yeah. Yeah, Erick, 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 to the earnings side as well.

Speaker #1: Awesome. Yeah. Thanks for taking the questions, guys. First for Steve, I wanted to drill into TERADATA factory a little bit more. Could you just walk through customer conversations there?

Speaker #1: And then I'm curious in how you expect that to drive pull through to other parts of the business and how do you see that impacting the 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?

Speaker #2: 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.

Speaker #2: We raised that again, but the timing of when those impacts hit has shifted on us. Operator, we'll take the next question.

Speaker #1: Thank you.

Speaker #4: 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.

Speaker #4: 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?

Speaker #1: Your next question comes from the line of Roddy Salton, your line is now open.

Speaker #5: Awesome. Yeah. Thanks for taking the questions, guys. Let's receive I wanted to drill into TERADATA factory a little bit more. Could you just walk through customer conversations there?

Speaker #4: It means that AI workloads can run natively on both the GPUs in that infrastructure but also on the CPUs in our massively parallel processing architecture.

Speaker #5: And then I'm curious how you expect that to drive pull-through to other parts of the business, and how you see that impacting the 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?

Speaker #4: So that expands use cases and the footprint that we have that allows organizations to run AI workloads right next to their data and they can do that on-prem.

Speaker #4: Which has got great use cases, for example, where data sovereignty is important. And some of the customer examples I gave in their prepared remarks point straight to that.

Speaker #5: Thank you.

Speaker #4: 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.

Speaker #4: 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.

Speaker #4: 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?

Speaker #4: It means that AI workloads can run natively on both the GPUs in that infrastructure, but also on the CPUs in our massively parallel processing architecture.

Speaker #4: 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.

Speaker #4: So that expands the use cases and the footprint that we have, allowing organizations to run AI workloads right next to their data, and they can do that on-prem.

Speaker #4: And that's why as we look at the overall business, what's important too is this total ARR. So when customers make the choice to deploy on-prem or in the cloud, we can capture that growth with them.

Speaker #4: This 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.

Speaker #4: 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.

Speaker #1: Got it. And then just to follow up for John, the balance sheet's obviously in a great place plus the SAP settlement, the debt paydown.

Speaker #1: 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?

Speaker #4: 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.

Speaker #1: I'd love to just dig into your thinking there as you think about uses of capital from here.

Speaker #3: Yeah. Sure. Radi, happy to. Appreciate the question. And yeah, so our balance sheet is in great shape. It's very strong following the retirement of our debt in the second quarter.

Speaker #3: 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.

Speaker #4: And that's why, as we look at the overall business, what's important too is this total ARR. So, when customers make the choice to deploy on-prem or in the cloud, we can capture that growth with them.

Speaker #3: 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.

Speaker #5: Got it. And then just to follow up for John, the balance sheet's obviously in a great place, plus the SAP settlement and the net paydown.

Speaker #3: 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.

Speaker #5: 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?

Speaker #5: Let's just dig into your thinking there as you think about uses of capital from here.

Speaker #2: Yeah. Sure. Roddy, happy to. Appreciate the question. And yeah, so our balance sheet is in great shape. It's very strong following the retirement of our debt in the second quarter.

Speaker #1: Awesome. Thanks, guys.

Speaker #3: Yep.

Speaker #2: Your next question comes from the line of Yitchuin Wong. You are now free to speak.

Speaker #2: 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.

Speaker #6: Hi. Good evening. Thanks for taking the question. Steve, definitely good to see some of the call-outs among your AI use cases getting some traction for your customers.

Speaker #2: 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.

Speaker #6: We certainly heard a lot of rising concern from according to out there from your peers, 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?

Speaker #2: 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.

Speaker #6: And then why the AI monetization seems to lag behind what your peers are seeing with accelerating growth recently?

Speaker #5: Awesome. Thanks, guys.

Speaker #2: Yep.

Speaker #1: Your next question comes from the line of Yichun Wang. You are now free to speak.

Speaker #4: Yeah. 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.

Speaker #6: Hi. Good evening. Thanks for taking the question. Steve, definitely good to see some of the call-outs among your AI use cases getting some traction for your customers.

Speaker #6: We certainly heard a lot of rising concern from according to out there from your peers 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?

Speaker #4: 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.

Speaker #4: 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.

Speaker #6: And then why the AI monetization seems to lag behind what your peers are seeing with accelerating growth recently?

Speaker #4: Yeah. 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.

Speaker #4: 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.

Speaker #4: 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.

Speaker #4: One of the advantages of running these workloads on the TERADATA platform is the costs and expense don't spiral out of control as these agentic workloads deploy on top of the platform.

Speaker #4: 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.

Speaker #4: 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.

Speaker #4: 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 second half.

Speaker #4: And we'll certainly be monetizing that as we go along.

Speaker #4: 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.

Speaker #6: That's helpful, Steve. John, I have a follow-up for you. Cloud ARR seems to come in somewhere below expectation given the double-digit guidance that's out there.

Speaker #6: And then with this shift in 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 the elongation of the middle-east situation and then maybe getting an update on kind of the stage migration from a year ago?

Speaker #4: 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.

Speaker #4: That's a unique competitive differentiation, but it does create some lag in the growth that we see from an ARR perspective. Certainly, the opportunity is there.

Speaker #6: Any changes from that front? Thank you.

Speaker #4: 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 second half.

Speaker #3: Yeah. 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.

Speaker #4: And we'll certainly be monetizing that as we go along.

Speaker #3: 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.

Speaker #6: That's helpful, Steve. John, I have a follow-up for you. Cloud ARR seems to come in every below expectation given the double-digit guidance that's out there.

Speaker #3: We are still seeing faster growth for cloud versus on-premise. Subscriptions but any given quarter, the mix of those deals may vary a little bit.

Speaker #6: And then with this shift in 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 the elongation of the Middle East situation?

Speaker #3: And so we still think that low double-digit growth target is the right range and the right trendline growth for our cloud business. But again, there may be some quarterly variability.

Speaker #6: And then maybe get an update on kind of the stage migration from a year ago, any changes from that front. Thank you.

Speaker #3: 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.

Speaker #2: Yeah. 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.

Speaker #3: 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.

Speaker #2: 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.

Speaker #3: We factored less migration activity in 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.

Speaker #2: 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.

Speaker #3: We're still continuing to see some of that activity. But much less going forward.

Speaker #2: And so we still think that low double-digit growth target is the right range. And the right trendline growth for our cloud business. But again, there may be some quarterly variability.

Speaker #6: Thank you.

Speaker #2: Your next question comes from the line of Patrick Walravens. Patrick, your line is now open.

Speaker #2: 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.

Speaker #6: Oh, great. Thank you. 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.

Speaker #2: 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.

Speaker #6: 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.

Speaker #2: We factored less migration activity in 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.

Speaker #6: Did that play into how you actually ended up doing?

Speaker #4: Look, I think as I look through the quarter, we are operationally execution and discipline was really good. And you can see that in the results part.

Speaker #2: We're still continuing to see some of that activity. But much less going forward.

Speaker #6: Thank you.

Speaker #4: From a go-to-market perspective, the teams have really embraced these new offers and new capabilities. They're proactively taking them out to our customers. Again, really good feedback about TERADATA Factory.

Speaker #1: Your next question comes from the line of Patrick Walravens. Patrick, your line is now open.

Speaker #6: Oh, great. Thank you. 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.

Speaker #4: As we said, it's from the early announcements and it's going GA. And the sales teams are excited. They're energized to take these messages to our customers.

Speaker #6: 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.

Speaker #4: 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.

Speaker #6: Did that play into how you actually ended up doing?

Speaker #4: Look, I think as I looked through through the quarter, we are operationally execution and discipline was really good. And you can see that in the results part.

Speaker #4: 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.

Speaker #4: From a go-to-market perspective, the teams have really embraced these new offers and new capabilities. They're proactively taking them out to our customers. Again, really good feedback about Teradata Factory.

Speaker #6: 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.

Speaker #4: 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.

Speaker #4: 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.

Speaker #6: But 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 like, "Oh, sorry.

Speaker #4: 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.

Speaker #6: 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?

Speaker #4: Yeah. 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 a vendor lock-in to a 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.

Speaker #6: Okay. And then, if I could ask a follow-up: 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.

Speaker #4: 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.

Speaker #6: But 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.

Speaker #4: And we believe that we can provide real context and business context to data that's inside our customers' ecosystem better than any of the else.

Speaker #6: 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?

Speaker #4: 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.

Speaker #4: Yeah. 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 a vendor lock-in to a 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.

Speaker #4: 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.

Speaker #4: 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.

Speaker #4: And that's our differentiation when we go in front of customers. That's what's going to enable us to win.

Speaker #6: Thank you.

Speaker #4: And we believe that we can provide real context and business context to data that's inside our customers' ecosystem better than any of the else.

Speaker #2: Your next question comes from the line of Matt Hedberg. Matt, your line is now open.

Speaker #4: 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.

Speaker #1: All right. Thanks, guys. 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 just sort of curious if your perspective on any supply chain thoughts as we head into the second half or even calendar year 27.

Speaker #4: 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.

Speaker #3: Yeah. 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.

Speaker #4: And that's our differentiation when we go in front of customers. That's what's going to enable us to win.

Speaker #6: Thank you.

Speaker #3: 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.

Speaker #1: Your next question comes from the line of Matt Hedberg. Matt, your line is now open.

Speaker #3: 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 increase pricing.

Speaker #5: All right. Thanks, guys. 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 just sort of curious if your perspective on any supply chain thoughts as we head into the second half or even calendar year 27.

Speaker #3: 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.

Speaker #2: Yeah. 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.

Speaker #3: 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.

Speaker #2: We're 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.

Speaker #1: Got it. Thanks. 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 obviously, you talked about kind of on-premise strength in the first half.

Speaker #2: 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 increase pricing.

Speaker #1: Can you talk about sort of thoughts on verticals, either financial services, government, and then how should we think about those in the second half?

Speaker #1: And I guess if that has any implication on potential on-prem cloud mix.

Speaker #4: Yeah, Matt. I think there's no doubt that in highly regulated industries or 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.

Speaker #2: 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.

Speaker #2: 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.

Speaker #5: Got it. Thanks. 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 obviously, you talked about kind of on-premise strength in the first half.

Speaker #4: 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.

Speaker #5: Can you talk about sort of thoughts on verticals, either financial services, government, and then how should we think about those in the second half?

Speaker #5: And I guess if that has any implication on potential on-prem cloud mix.

Speaker #4: Yeah, Matt. I think there's no doubt that in highly regulated industries or 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.

Speaker #4: And that's certainly the offer that we can take to these customers and 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.

Speaker #4: 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.

Speaker #1: Thanks, guys.

Speaker #2: Your next question comes from the line of Derrick Wood. Your line is now open.

Speaker #5: Great. Thanks for taking my question. 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?

Speaker #4: 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.

Speaker #5: 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?

Speaker #4: And that's certainly the offer that we can take to these customers and 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.

Speaker #4: Yeah. 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.

Speaker #5: Thanks, guys.

Speaker #4: 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.

Speaker #1: Your next question comes from the line of Derek Wood. Your line is now open.

Speaker #5: Great. Thanks for taking my question. 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?

Speaker #4: And we don't really see any change with respect to the TERADATA platform. We don't require large capex investments from our customers or recurring revenue model in our commercial model with customers gives us some advantage in terms of how we're contracting and the offer that we're taking to those clients.

Speaker #5: 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?

Speaker #4: What I would do is as well is just expand upon the supply chain point and just say that the partnership with Dell is actually meant that we can leverage Dell's buying power when it comes to some of this componentry.

Speaker #4: Yeah. 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.

Speaker #4: 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.

Speaker #4: 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.

Speaker #4: 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.

Speaker #4: We don't require large capex investments from our customers or recurrent revenue model in our commercial model with customers gives us some advantage in terms of how we're contracting and the offer that we're taking to those clients.

Speaker #4: And the partnership with Dell, we look to as generating some significant value for us.

Speaker #5: 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?

Speaker #4: What I would do as well is just expand upon the supply chain point and say that the partnership with Dell actually means that we can leverage Dell's buying power when it comes to some of this componentry.

Speaker #3: Yeah. I think we do have that posted up on the site. Derrick and I rather than quote the numbers here, I'll just direct you to that document.

Speaker #4: 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.

Speaker #5: Got it. Okay. Thank you.

Speaker #3: Yep.

Speaker #4: So, from a number of different factors, Derek, we've got a good handle on what's happening inside our customers. We're protecting our operating margin, and we're delivering price performance at the same time.

Speaker #4: Thank you.

Speaker #2: Your next question comes from the line of Raymo Lenschow. Your line is now open.

Speaker #6: Thank you. 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 etc.

Speaker #4: And the partnership with Dell, we look to as generating some significant value for us.

Speaker #5: 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?

Speaker #6: Is that something John that and Steve that drove the Q2 outperformance? Or can you just maybe explain one more time to us why Q2 and then hitting you in Q3?

Speaker #2: Yeah, I think we do have that posted up on the site, Derek. And rather than quote the numbers here, I'll just direct you to that document.

Speaker #4: Yeah. 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.

Speaker #5: Got it. Okay. Thank you.

Speaker #2: Yep.

Speaker #4: Thank you.

Speaker #1: Your next question comes from the line of Raymo Lenshao. Your line is now open.

Speaker #6: Thank you. 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 etc.

Speaker #4: It didn't drive incremental revenue from that perspective into Q2. So that wasn't the reason for outperformance. But Raymo, anytime you recognize that we've had good revenue performance and good recurring revenue performance in the quarter, I'll definitely take that.

Speaker #4: 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.

Speaker #6: Is that something John that and Steve that drove the Q2 outperformance, or can you just maybe explain one more time to us why Q2 and then hitting you in Q3?

Speaker #4: Yeah. 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.

Speaker #4: John, did you want to talk a little bit about Q2?

Speaker #5: Yeah. Not a whole lot more to add other than the comments that we've already talked about with regards to recurring revenue. I guess, Raymo, to answer your question specifically, hardware was not a meaningful factor in the revenue upside in either Q1 or Q2.

Speaker #4: It didn't drive incremental revenue from that perspective into Q2. So that wasn't the reason for outperformance. But Raymo, anytime you recognize that we've had good revenue performance and good recurrent revenue performance in the quarter, I'll definitely take that.

Speaker #5: 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.

Speaker #4: 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.

Speaker #6: 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.

Speaker #6: How should we think about the roll-out in terms of 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 more broad adoption next year?

Speaker #4: John, did you want to talk a little bit about Q2?

Speaker #5: Yeah. Not a whole lot more to add other than the comments that we've already talked about with regards to recurring revenue. I guess, Raymo, to answer your question specifically, hardware was not a meaningful factor in the revenue upside in either Q1 or Q2.

Speaker #6: Or how do you think about the lifecycle there? Thank you.

Speaker #4: Yeah. I think if I look in characterized 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.

Speaker #4: 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.

Speaker #5: 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.

Speaker #4: And capabilities that are making customers think about TERADATA in a very different way. I used the term on the prepared remarks, TERADATA 3.0. So not just being an opening connected multi-cloud data platform, which gave us some real differentiation, but really thinking about TERADATA as a knowledge platform.

Speaker #6: Okay. Perfect. Thank you. And then if you think about the new product lot of activity in Q2 and I'm excited to see more there.

Speaker #6: How should we think about the role out in terms of 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 a more broad adoption next year?

Speaker #4: 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.

Speaker #6: Or how do you think about the lifecycle there? Thank you.

Speaker #4: Yeah. I think if I look at characterized 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.

Speaker #4: We certainly see some of our customers picking up those capabilities early on in terms of their 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.

Speaker #4: 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.

Speaker #4: And capabilities that are making customers think about Teradata in a very different way. I used the term in 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.

Speaker #4: 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 having some impact as we move into the future.

Speaker #4: Thanks for the question, Raymo.

Speaker #6: Perfect. Thank you.

Speaker #4: 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.

Speaker #2: Your next question comes from the line of Wamsi Mohan. Your line is now open.

Speaker #7: Yes. Thank you. Steve, for the early AI wins, this cost our customers generating incrementally new spending? Are they expanding existing commitments or are they reallocating current TERADATA spend to AI studio and related products?

Speaker #4: We certainly see some of our customers picking up those capabilities early on in terms of their 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.

Speaker #7: I would love some color over there and I have a follow-up.

Speaker #4: Yeah. In Q2, we actually I would say we had all of those bars Wamsi. We actually we got some new logo wins. We had expansion in terms of workloads that we were delivering.

Speaker #4: 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 having some impact as we move into the future.

Speaker #4: 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.

Speaker #4: Thanks for the question, Raymo.

Speaker #6: Perfect. Thank you.

Speaker #4: 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.

Speaker #1: Your next question comes from the line of Wamsi Mohan. Your line is now open.

Speaker #7: Yes. Thank you. Steve, for the early AI wins, this cost our customers generating incrementally new spending? Are they expanding existing commitments? Are they reallocating current TERADATA spend to AI studio and related products?

Speaker #4: 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.

Speaker #4: And it points to, again, the point that John made in terms of why 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.

Speaker #7: Would love some color over there, and I have a follow-up.

Speaker #4: Yeah. In Q2, we actually obviously we had all of those bars Wamsi. We actually we got some new logo wins. We had expansion in terms of workloads that we were delivering.

Speaker #4: 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.

Speaker #4: 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.

Speaker #4: 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.

Speaker #4: 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.

Speaker #4: 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.

Speaker #7: Okay. Thanks, Steve. And I think in your opening comment, you cited anticipated incremental gains in retention as you go through the course of the year.

Speaker #4: And it points to, again, the point that John made in terms of why 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.

Speaker #7: 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 percent ARR growth outlook?

Speaker #4: Yeah. 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 FY25.

Speaker #4: 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.

Speaker #4: We saw improvements in the first half of 2026. And we see that continuing into the second half of 2026. A renewal team is doing a great job.

Speaker #4: 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 difficult to compete with.

Speaker #4: 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.

Speaker #7: Okay, thanks, Steve. And I think in your opening comments, you cited anticipated incremental gains in retention as you go through the course of the year.

Speaker #7: 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?

Speaker #4: So that's our opportunity to sit in 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.

Speaker #4: Yeah. 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 FY25.

Speaker #4: And I'm very proud of the TERADATA team in terms of how they're executing.

Speaker #7: Thanks, Steve.

Speaker #4: We saw improvements in the first half of 2026. And we see that continue into the second half of 2026. A renewal team is doing a great job.

Speaker #2: That now concludes today's Q&A session. I will now turn the call back over to Steve McMillan for his final remarks.

Speaker #4: 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.

Speaker #4: 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.

Speaker #4: And we absolutely remain confident in our ability to achieve our full-year objectives. And so with that, I thank you all for joining.

Speaker #4: So that's our opportunity that's sitting ahead of us. We're confident in our outlook for the year, and I think it's all about disciplined execution, to the point I made earlier.

Speaker #4: And I'm very proud of the TERADATA team in terms of how they're executing.

Speaker #7: Thanks, Steve.

Speaker #1: That now concludes today's Q&A session. I will now turn the call back over to Steve McMillan for his final remarks.

Speaker #4: Thank you, operator, and thanks, everyone, for joining us today. 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.

Speaker #4: And we absolutely remain confident in our ability to achieve our full-year objectives. And so, with that, I thank you all for joining.