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DATE

Wednesday, April 22, 2026 at 8 a.m. ET

CALL PARTICIPANTS

  • Founder and Chief Executive Officer — Alan Trefler
  • Chief Operating Officer and Chief Financial Officer — Ken Stillwell
  • Moderator — Peter Welburn

TAKEAWAYS

  • Pegasystems (PEGA 4.16%) Cloud revenue -- Revenue grew from $151 million to $205 million year over year and increased 30% on a trailing twelve-month basis.
  • Pega Cloud Annual Contract Value (ACV) -- ACV increased 29% as reported and 27% in constant currency year over year to just over $900 million, approaching 56% of total ACV.
  • Free cash flow -- Free cash flow reached $207 million; more than 80% was returned to shareholders through $167 million in buybacks (3.5 million shares) and $5 million in dividends.
  • Net ACV add comparison -- The prior-year quarter included a $60 million net ACV add, which management described as an outlier approximately 20% higher than any other quarter that year.
  • Q1 constant currency ACV growth -- Growth was approximately $20 million, slightly below management's internal expectations but considered to be a minor variance.
  • Cloud mix target -- Management aims for Pega Cloud ACV to reach 75% or more of total ACV over time, displacing term and maintenance ACV as a stated strategic intent.
  • Maintenance and term license revenue -- Both are expected by management to decline over time as clients shift to Pega Cloud; term license revenue is recognized upfront upon renewal and is expected to be more back-end loaded this year.
  • Pipeline and new logo momentum -- Blueprint AI is credited with accelerating new logo pipeline growth and deal velocity, with management highlighting an "unusually high level of new logo pipeline growth."
  • Blueprint AI impact -- Successful examples include one existing client going live with two new applications in 92 and 70 days, and a new financial services client migrating 30 applications to Pega Cloud due to Blueprint’s legacy transformation capabilities.

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RISKS

  • Ken Stillwell stated that the federal government shutdown, and two wars—both in Europe and in the Middle East—clearly put pressure on the entire environment, noting that delays and renewals slipped out of Q1 due to government procurement disruptions.
  • Stillwell further noted, "The duration of the wars could hurt the spending environment across IT because of supply chain disruption," with approximately 30% of the company’s business in Europe potentially subject to derisking as a result.
  • Management acknowledged increased tension between U.S. providers and other regions, requiring heightened management of cloud deployment and sales efforts as “sovereign clouds,” and localization demands rise amid geopolitical issues.

SUMMARY

Management directly reported significant year-over-year growth in Pega Cloud revenue and ACV, with Pega Cloud ACV now exceeding $900 million and representing 56% of total ACV. Pegasystems returned over 80% of free cash flow to shareholders via aggressive buybacks and dividends. Management identified the second half of the year as a period of heightened renewal and business activity, anticipating further shift of ACV mix toward the cloud. Blueprint AI was repeatedly highlighted as a new driver behind pipeline build, sales efficiency, and deal acceleration. Company leaders explicitly warned of macroeconomic and geopolitical headwinds impacting procurement cycles, especially in government and European markets, and confirmed delayed deals resulting from these disruptions.

  • Ken Stillwell said, "Our renewal portfolio is back-end loaded this year, which means we expect a higher level of business activity in the second half of the year."
  • The company’s pricing model is based on "Importantly, our pricing model is aligned with the shift toward outcomes. Pega prices based on cases, which is a measure of the amount of work that the Pega platform executes, tying our economics directly to the business value delivered rather than to users or seats. This stands in contrast to many model providers, where price is driven by usage metrics like tokens or API calls. As AI costs come under greater scrutiny, we believe our outcome-based pricing model provides a clearer and more efficient path for clients to generate and measure return on their AI investments."
  • Alan Trefler emphasized, "LLMs do magical things, but you want to use them for the right things," positioning Pega’s Blueprint architecture as a differentiated, structured approach versus pure AI-code generation.
  • Most new pipeline growth is now connected to the use of Blueprint in some way, highlighting Blueprint’s central role in new logo acquisition and workflow transformation.
  • Management plans to provide additional detail on Blueprint-driven metrics and new logo momentum during its investor session in June.

INDUSTRY GLOSSARY

  • Annual Contract Value (ACV): The value of contracted recurring revenue (subscription and maintenance) expected to be earned in a 12-month period, often used to measure growth in SaaS and cloud businesses.
  • Blueprint AI: Pegasystems’ proprietary platform for AI-powered design and transformation of business workflows, referenced as a driver of pipeline and sales velocity.
  • Term license revenue: Upfront revenue recognized when a client renews a multi-year software license, distinct from recurring cloud or maintenance revenue.
  • Five-coding: An AI-assisted rapid application development technique within Blueprint, enabling users to generate new workflow elements using natural language commands.
  • Sovereign cloud: Cloud computing infrastructure tailored to a specific country’s regulatory and data localization requirements, increasingly relevant in government and regulated industries.

Full Conference Call Transcript

Peter Welburn: Thank you, Carly. Good morning, everyone, and welcome. Words such as “expects,” “anticipates,” “intends,” “plans,” “believes,” “will,” “could,” “should,” “estimates,” “may,” “forecast,” and similar expressions are intended to identify these forward-looking statements. These statements speak only as of the date the statement was made, and are based on current expectations and assumptions. Because these statements relate to future events, they are subject to certain risks and uncertainties that could cause actual results to differ materially from our current expectations for fiscal year 2026 and beyond.

Factors that could cause such differences are described in the company's press release announcing our Q1 2026 results and our filings with the Securities and Exchange Commission, including our Annual Report on Form 10-K for the year ended 12/31/2025, as well as other recent SEC filings. Investors are cautioned not to place undue reliance on these forward-looking statements, as there can be no assurances that the results contemplated will be realized. Except as required by law, we undertake no obligation to update or revise any forward-looking statements to reflect subsequent events or circumstances.

In addition, non-GAAP financial measures discussed on this call should be considered in conjunction with, and not a substitute for, our consolidated financial statements prepared in accordance with GAAP. Constant currency measures are calculated by applying the 03/31/2026 foreign exchange rates to all periods presented. Reconciliations of GAAP to non-GAAP measures can be found in our earnings press release. With that, I will turn the call over to Alan Trefler, founder and CEO of Pegasystems Inc. Thank you very much.

Alan Trefler: I have just gotten back from a few weeks on the road across EMEA and the U.S., including an AI conference last week. It is interesting because I think we are pretty practiced at separating hype from what is real, but there is a lot of confusion out there. Nonetheless, I am hearing consistent themes from leaders, clients, prospects, and partners. In a world of constant disruption, clients want and need innovation without sacrificing reliability. They want solutions to reimagine how their businesses work while still running them predictably and delivering measurable results. This means platforms architected for scale, interoperability, and continuous change, where AI is governed, explainable, and harnessed in workflows rather than bolted on.

That is what Pega provides: a harness for enterprise AI, Blueprint to help reimagine how work should run and help people rethink their businesses, and then the Pega platform to operationalize it with confidence and evolve it. It is regulatory and dependable. There is a lot of noise about the future of the software industry, and it is creating some real confusion and some real moments of doubt. Some investors I have met are not sure what the future looks like and are even questioning the long-term viability of enterprise software vendors. We think AI will be good for some and bad for others, and for Pega, it will be good.

The reality is that enterprises do not succeed based on the alternative of coding asked, using AI. They succeed based on whether they can design the right outcomes, execute them predictably, and evolve safely over time. The assumption that AI-generated code can replace architecture is backwards. In mission-critical enterprises, AI increases the value of platforms that are architected for predictability, governance, interoperability, and continuous change—and that is us. When outcomes matter, with customers, regulators, and systems that must evolve for decades, AI-generated code still needs structure—certainly for the types of things we do. Very small things, you can just five-code them together, but AI does not replace the need to have a business system.

Alternatively, if people are using AI to just dynamically reason each process over and over, what we are seeing is it is now running at cost and giving nondeterministic outcomes. The moment you weaken your enterprise platform, you make your whole business weak. Putting AI in the middle in an ungoverned way is, I think, a recipe for disaster.

So whether you use AI to generate code that you want to be able to orchestrate and pull together, whether you use AI to be able to run or handle certain parts of your business where you want the creativity of agentic interactions, or whether you want these AIs to be able to pull together and orchestrate multiple business functions with a harness like Pega driving that—in all of those cases, Pega adds tremendous value. Let us talk about how mission-critical enterprise software really gets built. Enterprise applications have always been around a continuous life cycle, regardless of technology. It is not a single build moment.

You need to design and align on what the software must do and how it must perform. That design involves collaboration from many parties, and having a collaborative environment like Blueprint that brings the power of the internet, the power of Pega best practices, and the power of a customer’s and/or partner’s thinking together in a way that they can understand, experience, and improve is absolutely central to getting to a great outcome. You have to build it, and there are lots of ways to build it, but the great news about something you have got in Blueprint is it is basically built.

You need to be able to execute or operate it—to run it at scale, secure it, make sure that it is performant, watched, and managed. With Pega Cloud, which you will see is really continuing to grow beautifully, we give our customers a place to execute that is without parallel. Then you need to be able to evolve it and respond to change as the cycle starts again. This cycle is high-stakes, and it is absolutely critical to get businesses not just what they want to get done in two, four, or six weeks, but to get them to operate over the years of the business.

The Pega model, which is at the heart of a Pega system, is the key to most of these factors. It lets you design it, collaborate, makes the build trivial, actually executes it and orchestrates the AI, and best of all, it lets you go back to it and have a structure that you can look at, understand, and direct change from. That ultimately, to us, is how this life cycle operates in this new AI orchestration age. While LLMs dramatically accelerate the build, they do not replace these other key factors, nor are they going to. That is why clients cannot take a “just add software” approach. Certainly, AI can generate code quickly, but code alone falls short.

It does not tell the enterprise what should change. The gap is not in coding speed; it is in understanding what is there and making sure you do not accidentally change something with unintended consequences. When you are operating at the speed of the prompt, it is actually easier to do that, not harder—particularly if you have not put out a nice solid architecture that makes what is going on visible. We also hear some people say they believe in AI-only execution—why do I need a workflow engine or a harness at all?

Why not simply turn everything over to general-purpose AI agents and manage it with a control tower that watches what is going on, reports out, and keeps things in line? These create systems that are difficult to test, expensive to run, and nearly impossible to evolve safely. LLMs are incredibly sensitive to even the tiniest bits of additional data, and a new version of the LLM—look at how quickly they are coming out—can behave differently from the one you used just the day before. For many types of work, improvisation is not a reasonable business strategy. People want predictability and reliability. What also broke last week is that this approach to AI reasoning is becoming cost-prohibitive.

I hear growing discussion about the cost of GenAI and how teams are bouncing between token-maxing—using as many tokens as possible—and rationing tokens to suppress the bills. The concerns are real, but they reflect a misapplication of AI—using the wrong AI at the wrong time. When you ask GenAI to reason at runtime over and over again for processes you have already validated, every interaction becomes a new experiment and consumes tokens. You end up paying repeatedly for the same thinking, which is expensive, unpredictable, and hard to scale.

Instead, do what Blueprint AI does: do the super-heavy reasoning at design time—where GenAI can brilliantly explore options, map workflows, let you collaborate, and pressure-test decisions—then use the right AI for the execution, focusing on consistency and speed. Costs become predictable and value scales with confidence. GenAI is not inexpensive when misapplied. Smart organizations will stop paying the LLM to relearn their business every five minutes. Success in the enterprise does not come from AI reasoning everything on the fly. It comes from executing redesigned, reimagined work within clear governance structures. Our architecture uniquely allows enterprises to design intelligence into how work gets done, not bolt it on afterward.

Since we last spoke, we introduced new five-coding tooling into Pega Blueprint. This combines the speed of AI-augmented design with the security and predictability that Blueprint gives. You can try it at pega.com/blueprint. Remember that Blueprint facilitates the reimagination of critical work, not just the development of applications. That reimagination goes beyond process alone—it includes redefining roles, decision rights, skills, and experiences. AI can be applied intentionally to these, rather than accelerating whatever already exists. Users interact with Blueprint designs in natural language now, describing changes by typing or speaking, and the results are enterprise-ready governed workflows. We receive continued validation of Pega’s leadership across the industry from clients, partners, and analysts who see and work with Blueprint AI.

Recently, Forrester named Pega as a leader in customer service solutions, recognizing Pega Customer Service, Pega Blueprint, and Pega Process Mining for automation and agent capabilities. We are also winning awards for our software. We have already this year received four awards for innovation related to how we are leveraging AI, including a Product of the Year award. We love receiving awards for our work, but personally, it is even better seeing our clients win awards for the work that they do with our software. Just last month, the National Health Service, which provides 24-hour digital and telephone-based health service to Scotland’s 5.5 million citizens, received the public sector award for work leveraging Pega software.

These recognitions reinforce our strength and the need to orchestrate complex service journeys and apply AI predictably. This is not theoretical. One of our customers, Proximus—Belgium’s largest telecommunications operator—used Pega to modernize a mission-critical B2B installations application, moving from a fragile legacy tool to an orchestrated, cloud-ready solution. They built their first prototype in Blueprint in 15 minutes and went live in weeks. Numerous other great names—ING, Vodafone, National Australia Bank—have really been able to drive change and include extensive automation, all AI-powered. Our customers are excited about this, and they are coming to PegaWorld in quantity to talk in detail about what they are doing. These stories and others will be shared at PegaWorld in June in Las Vegas.

It is a must-see event—a chance to interact with thousands of transformation leaders from around the world and see incredible new developments at over 200 different AI-powered demos. We have exciting keynotes lined up, with nearly 100 more customers from 60 organizations presenting detailed breakout sessions. MetLife will show how a highly regulated insurer moved from AI experimentation to AI at scale. We will discuss large-scale legacy modernization leveraging Pega Blueprint and AWS to rearchitect decades of legacy core systems. Wells Fargo will talk about how they highlight AI-driven decisioning across billions of customer interactions. We will also have a tremendous product agenda. Blueprint AI has fundamentally changed the upfront design and reimagining of how people should work with systems.

This year, you will see how Blueprint AI is moving into the entire development and support suite, so that AI-driven guidance and power will operate from visualization and inception in Blueprint all the way through to completing a system and supporting a production system. I think this is the most consequential change to the underlying technology that I have seen, and it supports the agentic process fabric technology we have that allows all of your Pega systems—and even non-Pega systems—to operate as a connected, orchestrated network for the next generation of technology.

Only Pega has the efficient runtime intelligence, the deep design-time skills, and the experience with these key workflow harnesses, and we will put in your hands the way for you to make our harness your harness. We look forward to continuing the conversation, and we will continue the investor conversation on Monday, June 8, when at noon in Las Vegas we are also hosting an investor session. Thank you all. We are working hard. For the numbers, let me turn it over to Ken. Thanks.

Ken Stillwell: As discussed last quarter, the rhythm of our business was expected to return to a more typical seasonal pattern in 2026. We entered the year knowing the first quarter would also be a challenging comparison, given the $60 million of net ACV add in Q1 2025, which was very much an outlier and roughly 20% higher than any other quarter last year. It is an interesting start to 2026, with all of the AI experimentation that Alan mentioned, the federal government shutdown, and two wars—both in Europe and in the Middle East—clearly putting pressure on the entire environment. It is not surprising that Q1 had a lower growth rate.

We continue to believe in the durability of demand for our platform, especially for our cloud offering. Pega Cloud revenue in Q1 2026 increased year over year from $151 million to $205 million and also grew 30% on a trailing twelve-month basis. Pega Cloud ACV grew 29% year over year as reported, and 27% in constant currency, to just over $900 million—over a $200 million jump. It is very exciting to see Pega Cloud ACV now rapidly approach the $1 billion mark. As we have said, ACV growth and mix is reflective of the evolution of our business. Pega Cloud ACV now represents about 56% of total ACV.

Our focus on growing Pega Cloud puts pressure on both term and maintenance ACV, as well as revenue. Naturally, as Pega Cloud ACV continues to grow as a percentage of overall ACV, it will impact near-term and in-quarter revenue for term and maintenance. Moving to free cash flow, free cash flow reached $207 million in Q1 2026, marking a strong start to the year. As a reminder, our free cash flow is primarily driven by our operating performance and our ACV growth, which serves as a proxy for subscription billing growth. We remain confident in our strategy to drive free cash flow and ACV growth for several reasons.

First, expansion within our existing client base remains a core go-to-market motion, with our sales team continuing to successfully cross-sell and upsell into our installed base. Second, we are accelerating new logo pipeline build, with Pega Blueprint as a key enabler. Blueprint makes it easier for sellers to showcase the power of the Pega platform and for buyers to reimagine their legacy mission-critical workflows. As a result, Blueprint is already driving meaningful pipeline creation across both new logo and existing clients. We expect this new pipeline will begin converting into ACV in the second half of the year, as deals progress through the sales cycle with a faster motion thanks to Blueprint.

This is also an unusually high level of new logo pipeline growth, which is awesome to see. Third, we are already seeing early proof of Blueprint’s ability to accelerate time to value. Last month, I met with a large healthcare organization—an existing client—that used Blueprint to design and build two new applications, one going live in 92 days and a second in 70 days. A strong example of what our platform can do, powered by Blueprint. Fourth, we are seeing renewed interest in legacy transformation, as more enterprises look to leverage AI and the cloud to modernize their operations.

Blueprint is unlocking these legacy transformation opportunities by simplifying how clients reimagine and redesign their workflows to drive growth, reduce costs, and improve customer experience. Together, Blueprint and Pega Infinity create a powerful combination—Blueprint to design and reimagine the work, Infinity to run it—reinforcing Pega’s position as the platform of choice for large-scale, mission-critical workflow transformation. Unlocking legacy transformation is just one way Blueprint is transforming our business. Early signals show Blueprint is accelerating pipeline growth and helping us capture new clients. For example, in Q4, we signed a new financial services logo, leveraging Blueprint’s legacy transformation capabilities, with plans to migrate more than 30 applications from a legacy application platform to Pega Cloud.

Blueprint is also driving meaningful go-to-market efficiency. Where deals once required a full bench of supporting roles, today our client executives can cover far more ground with our clients when leveraging Blueprint. Finally, we are seeing R&D benefits as well. Our new agentic engineering approach will enable us to execute our product roadmap more efficiently, allowing us to increase our pace of innovation. Since Blueprint runs on Pega Cloud, we can deliver new features and capabilities rapidly to clients and prospects. We are excited to share more about this new approach with you at our upcoming investor session in June.

Moving to capital allocation, we continue to maintain a balanced approach, prioritizing investments in long-term ACV growth while returning capital to shareholders as appropriate. In Q1, we returned more than 80% of our free cash flow to shareholders, repurchasing 3.5 million shares for $167 million under our repurchase program and paying $5 million in quarterly dividends. As of 03/31/2026, our shares outstanding decreased from the end of 2025 by 1.6 million shares. Looking ahead, we will continue to return capital while maintaining strategic flexibility. Our buyback reflects our unwavering confidence in the durability of our cash flow. These buybacks are accretive to earnings and also combat stock-based compensation dilution. They are made possible by strong and durable cash flow.

A few thoughts on modeling. We provide full-year guidance at the start of the year, and we typically do not issue quarterly guidance or update our outlook during the year. Our renewal portfolio is back-end loaded this year, which means we expect a higher level of business activity in the second half of the year. The shape of our pipeline also influences the timing of term license revenue, which is largely recognized upfront in the quarter a client contract is renewed. As a result, we expect term license revenue to be more heavily weighted towards the back half of 2026. At the same time, our focus on driving Pega Cloud ACV growth also puts pressure on term and maintenance ACV.

The success of our Pega Cloud sales efforts is already reflecting the shift, and we expect it to continue as Pega Cloud ACV scales to 75% or more of our total ACV over time. Put simply, a portion of our Pega Cloud ACV growth is displacing term and maintenance ACV, as intended, and we expect this dynamic will persist as we march toward our cloud mix goal. In addition, we are beginning to see a meaningful change in how enterprise clients are thinking about AI. The economics of AI are changing. Frontier model providers are tightening monetization, and the era of low-cost, subsidized, all-you-can-use experimentation seems to be coming to an end.

As a result, AI usage is increasingly treated as what it is—a true operating expense. Every API call must be justified with clear business value. Given this change, buyers are moving out of the experimental phase of AI into the ROI stage. This transition to profitable AI plays directly to our strengths. Pega has always been focused on delivering measurable business value. AI is not just about efficiency; it is about generating tangible returns, and that is exactly what Pega is built to do. Importantly, our pricing model is aligned with the shift toward outcomes.

Pega prices based on cases, which is a measure of the amount of work that the Pega platform executes, tying our economics directly to the business value delivered rather than to users or seats. This stands in contrast to many model providers, where price is driven by usage metrics like tokens or API calls. As AI costs come under greater scrutiny, we believe our outcome-based pricing model provides a clearer and more efficient path for clients to generate and measure return on their AI investments. As Alan mentioned earlier, we are holding our annual investor session at PegaWorld on Monday, June 8, at the MGM Grand in Las Vegas.

During the investor session, we look forward to providing you with additional color on several of the topics that I discussed today. We also plan to provide more insight into how we envision clients driving legacy transformation with Pega and how we are progressing against the long-term targets we laid out last year. We also plan to give you insights into several key Blueprint metrics, including the impact on pipeline build and deal progression and, most interestingly, some of the metrics around new logo momentum. In closing, we look forward to seeing you on the road at conferences and non-deal roadshows over the next few months, and at our investor session at PegaWorld in June.

We encourage all of you to join us. Please also note that we plan to participate in the NASDAQ opening bell ceremony on Monday, July 13, at NASDAQ MarketSite in New York, to celebrate the thirtieth anniversary of Pega’s initial public offering. With that, operator, please open the line for questions.

Operator: At this time, I would like to remind everyone, in order to ask a question, press star, then the number one on your telephone keypad. Your first question comes from Alexei Gogolev with JPMorgan.

Alexei Gogolev: Hello, everyone. Ken, would you mind providing a bit more color on acceleration of ACV growth through the year? I remember you talking about the client compelling events and renewal cycles driving potential uplift in 2026.

Ken Stillwell: Yes. Good morning, Alexei. There are two factors. One is our renewal cycle is tipped toward the back half of 2026, which is more the usual distribution than unusual. In 2025, that was reversed—there were not as many compelling events in the back half of the year. When there are renewal cycles, that is typically an event where clients that are going to expand their relationship tend to do it around that renewal cycle. Second, we have put a renewed focus on new logos with Blueprint. As we build pipeline, the conversion of that pipeline will naturally grow, and the opportunity tends to sit towards the back end of the year as well.

So there are two factors that really tip our business momentum towards the back end of the year, which is very different than last year, where we were unusually tipped towards the front end of 2025.

Alexei Gogolev: Thank you, Ken. And Alan, in the past you spoke about AI adoption disconnect. Can you talk a bit more about what you are seeing in terms of the narrative in the industry and update us on the trends from Q1 in terms of agentic adoption?

Alan Trefler: There are some things that, looked at properly, you have to either laugh or cry. I spend a lot of time out in the field talking to people about what they are doing. There is so much going on. People talk about LLMs, the word “agentic,” LLM technology, vector databases—we make very heavy use of vector databases as a way to use LLM technology but do it in a very cost-effective fashion. What I encounter is some people think they will be most successful when they use LLMs for as much as possible. That is just crazy.

LLMs do magical things, but you want to use them for the right things, not for the parts of the problem that are statistical and not for the parts that should be planned out in advance—and planned out well ahead of time. That is what Blueprint does. You should not just plan and replan and pay an incredible tax for rethinking what you already know.

Some are so enamored with LLMs that they are in love with them, and some enterprises have told their teams, “We just want you to use this stuff.” I can appreciate that if they are trying to get people to understand it, but that is not what ends up sticking—because of cost and lack of reliability. It is also about sustainability—this can be very power hungry. Understanding proper use of LLMs is absolutely key, and to be honest, I think we have nailed it. What I see with others is a structurally different path in most cases. Thank you.

Raimo Lenschow: I just wanted to stay on that new-logo focus. Over the years, you have been the high-end provider—very good for complex scenarios—but on new logos that was always a bit of a question. You had a very deep installed base. Talk a little bit more about that new focus on new logos. I can see how Blueprint is going to help here, but I want to understand that better. And then, Ken, on the maintenance side: I hear you that the push towards Pega Cloud will impact maintenance. The numbers we saw this quarter—are they indicative of what we see for the year, or were there other factors in Q1 we should be aware of? Thank you.

Ken Stillwell: On maintenance, as we continue to move towards Pega Cloud, you will see maintenance go down over time, and you will see term license be flat to down as well. Even though some clients will still continue to run on client cloud, I think you will start to see that shift—not 100% at any point in the foreseeable future, but it will move in that direction. On new logos, the way we think about it—this is just a framework—if you look at a company like Gartner, they have something like 15 thousand clients. I think Forrester has slightly less than that, but still many thousands, probably approaching 10 thousand clients.

The types of companies that would go and seek advice from a Gartner or Forrester clearly have enterprise spend of some size. We believe all of those organizations are an opportunity for Pega. There are others that do not subscribe to Gartner as well. We are not talking about going down to tiny organizations to get that opportunity. There are a lot of companies that we have not historically sold to. It is a newer motion for us, but not brand new. We have always added a few new logos. Blueprint completely changes the dynamic of how fast we can engage with a new logo and the speed at which we can validate if there is interest.

In the past, it might have been a two-year sales cycle to see if there was momentum. Blueprint really changes the game.

Alan Trefler: Blueprint is a great starter for that, but we have done a couple of other things that also change the game. First, we will predesign things that you would have had to be a lead system architect with years of experience to really do—and now it just happens. We have built in a lot of that expertise, and every month we build in more. We have radically changed the training-required curve and the expertise-required curve, and candidly, all of these also adjust the cost curves at the same time that they improve speed of delivery. We have added Socratic education, which makes it easier to teach people about their gaps as opposed to having them go to big formal courses.

There has been a huge simplification. We want to go from the 800 companies that we would traditionally sell to and have as customers, to 10,000 as a much more easily addressable population of multi-billion firms we can go after. We now have a tool well equipped for that. And because it runs on Pega Cloud, which is tied into our predictive diagnostic cloud—doing a lot of self-maintenance, performance management, and handling scaling beautifully on Kubernetes—we are in a position where we can really go after this. It is not just the choice to go after it; it is years of product evolution and business evolution that have made this possible.

Raimo Lenschow: Yep. Makes sense. It is exciting. Thank you.

Steve Enders: Great, thanks for taking the question, and good to see everybody last week at the conference. I wanted to start on the AI discussion and the focus on becoming the harness for enterprises. What does this mean for your customers in terms of use cases as you try to become that harness layer, and how are you thinking about the adoption curve within some of the bigger customers that you have?

Alan Trefler: Customers—think Proximus, and others—look to the use of our AI powered by Blueprint, but still able at critical points in the workflow to call even a non-Pega agent. The idea is that we can use our agents and customers’ agents, all in the context of a business objective that they were able to think out and design. That gives customers a level of reliability and auditability that they cannot come close to with the alternatives. Customers who take the moment to understand that they do not want to revisit everything all the time get this. You all probably use Claude, Gemini, and OpenAI.

I was using Claude this morning—asking questions—and it starts explaining that it is “reasoning,” using terms like frolicking and canoodling. When it is doing that, it is feeding itself tokens. We are paying for these journeys of intellectual research. I am thrilled to do that when it is not the exact same stuff that was done that morning. People who think they will handle credit card disputes by turning them to an LLM to figure out the detail and nuance for each individual customer are missing the chance to bring stability and efficiency into those operations. When we explain the harness concept, customers really get it.

Ken Stillwell: I will add one thought. If you think about the value of Pega functioning as a harness—you have the efficiency, you have risk management, and you also have resiliency because we can use multiple models and use the right model at the right time. Models vary in performance, speed, and context. We create the best of all models in terms of leveraging them at design time and selectively at runtime.

Steve Enders: That is helpful context. Maybe on the ACV dynamics, it would be helpful to know what the net new ACV was if we look at Q4 2025 constant currency—what that was for the quarter. And then on the levels that came in this quarter, did this come in as you were expecting when you guided for the year, or does this change how you think about ACV growth for the year?

Ken Stillwell: First-half last year we had a significant amount of constant currency growth—that was unusual and will not repeat this year. We were going to be more back-end loaded. The constant currency growth in Q1 was somewhere around $20 million. It was within a few million dollars of where I thought it would be—probably a couple million dollars lower than what I thought—but pretty close. It was more of a rounding error than something significant. Q2 is not a big renewal quarter either; it is really Q3 and Q4. The year is not that different than how I envisioned it playing out. We knew cash flow would be stronger in Q1 because Q1 is typically a strong cash flow quarter.

Across the board, it was not dramatically different than our plan.

Rishi Jaluria: Wonderful. Thanks for taking my questions. Two for me. Ken, in your prepared remarks, you talked a little about the macro backdrop. With everything with government and geopolitical tension—and leaving AI aside for a second—how has that impacted your business so far, and how should we think about the potential impact for the rest of the year?

Ken Stillwell: On government and the shutdown and some of the changes, there were a few deals and a renewal or two that slipped out of Q1. We do not believe those are lost deals; it is more about the procurement process changes creating some confusion in Q1, more in March. I do not suspect that will extend for a prolonged period, but Q2 might still have a little confusion as GSA starts to take deals more directly, etc. There is definitely some backlog of work that needs to process through the government. On the wars—plural—both are impactful for Europe, and about 30% of our business comes from Europe.

It would be accurate to say there is potential for derisking because of higher oil prices and temporary goods flow disruptions into APAC and parts of Europe. Government—yes, some delays that I think will clean up through the rest of the year. The duration of the wars could hurt the spending environment across IT because of supply chain disruption. We have started to hear some conversations. I would not point to specific deals in Q1 necessarily, but it is definitely something we are watching.

Alan Trefler: There has been more of a push to go for some of these “sovereign clouds,” which AWS, for example, is working on. But just having that as an extra complication can drag things out.

Ken Stillwell: Thankfully, we have Cloud Choice, so we can work with different hyperscalers and regions. But there is definitely some tension between U.S. providers and other parts of the world, and we have to manage through that as these wars continue.

Rishi Jaluria: Thanks. That is very helpful. And then for both of you: Ken, you talked about the era of subsidized, unlimited tokens possibly ending, with throttling of usage. As that trend plays out, what does that do to your own cost structure with Blueprint—where you are using LLM for design and ideation, not necessarily runtime—and does it change the nature of conversations with customers who wanted to try AI for everything?

Alan Trefler: We were really seeing those effects last week after providers announced price changes. It will be fabulous for us. Blueprint is as consumptive as anything else, but when you design something once and run it 200 thousand times, the design cost is not really relevant. That is really nailing it. It is great that tokens have started to approach closer to reality—they are still very heavily subsidized—and I think that subsidy will persist as people try to push numbers up before going public.

Devin Au: Hey, Ken. Hey, Alan. Thanks for taking my questions. Ken, I know you mentioned some geopolitical disruption in India that is ongoing, but when I look at your revenue performance in the U.S. and APAC in the quarter, it seems like both regions were down quite notably. I know revenue is not the best metric to assess the business quarter over quarter, but would love more color on what drove the downtick for those regions in the quarter.

Ken Stillwell: That is solely the timing of term license revenue and how that compares year over year and quarter over quarter from Q4 to Q1. In terms of business activity, I do not believe we have seen any impact on bookings or new business in either region. My comment was more that it would be reasonable to think they would be under pressure, but we have not seen it. The revenue is just related to term license timing, not structural.

Alan Trefler: And we hate that revenue behaves the way it does. Nothing would make us happier than to be able to report everything on a recurring rate.

Devin Au: Understood. Appreciate the context. And a quick follow-up: you talked a little in the remarks about the new five-coding capability released in Blueprint. Would love for you to speak to how usage and engagement have trended since that release. Have you seen any early signals on greater expansion activity from users leveraging that five-coding tool?

Alan Trefler: We are getting great feedback. It is right in Blueprint—there is an AI assistant panel on the left. On any page, if you say, “Add an insurance policy to this travel request,” it will design the data structures and fields right into the blueprint. You do not have to get it right upfront. Peter would be thrilled to demo it to you, but anyone can just go on and do it. It is absolutely central to what we are doing, and feedback has been great.

Patrick Walravens: Great, thank you. Alan, two for you. You talked about the long-term viability of enterprise software vendors, and you said AI will be good for some and bad for others. Who is it going to be bad for?

Alan Trefler: It will be really bad for products where GenAI has just made a feature. For example, there was a company we used to license document processing software from, and if a customer wanted to pull fields off a physical document, they were really good. Now you can just do that by calling the LLM. So point features have massively changed or gone away. I think a lot of the low-end workflow companies—like tools for 10-person workgroups—are going to be the types of things somebody might be able to just code.

Ramping that up to work across even a 500-person company, let alone 5 thousand-person companies, which is our bread and butter—AI adds tremendous value to that and does not really open us up to risk.

Patrick Walravens: The second question is out of left field, but I am sure you have a point of view. SpaceX buying Cursor—or maybe buying Cursor—for $60 billion with a $10 billion breakup fee. What does that tell us about what is going on in the AI world?

Alan Trefler: I would have to rely on guys like you to tell me. There are so many AI companies. Last week, I was driving up 101 and there was billboard after billboard of AI companies I had not heard of. There is an enormous collection of co’s, some of whom have become instant unicorns. That tells me parts of AI are in the bubble phase, and that will shake out. Whether SpaceX makes Cursor one of the few survivors, or whether the glut kills them all—I do not know. I am not fighting in that fray and have no interest in getting thrown into it.

Ken Stillwell: One point we heard last week at the AI conference: Cursor is sort of a harness—but for programmers. It suggests that AI models need to be governed in different ways for different use cases. When we use the word harness, it is thinking about being a harness at runtime. Blueprint is a harness at design time—it gets you to think about the design the right way first, in the right structure and order. I think you need a design-time harness and a runtime harness. Cursor is a good design-time harness—guardrails for AI models.

Patrick Walravens: That is super helpful. Thank you both.

Mark Schappel: Thanks for sneaking me in here. Ken, what portion of your pipeline is now AI-driven versus more traditional platform ACV?

Ken Stillwell: I will reframe your question. How much of our pipeline is led by Blueprint? Almost all of our new pipeline growth is connected to the use of Blueprint in some way, which I would put in the AI camp. In terms of our AI accelerators—like KnowledgeBuddy, Coach, etc.—some of the specific runtime AI accelerators, we typically think about those as a premium markup on the value of activity that happens through the platform. But for all new pipeline added—certainly new logos and new workflows—those are led by Blueprint and Pega AI.

Mark Schappel: Thank you. And Alan, could you comment on how demand for legacy-scale modernization programs is evolving, especially in government and regulated industries?

Alan Trefler: We are engaging. It is slow, but we have a number of these legacy transformation projects going on now, and I am excited about it. It is a big market. We are building up our expertise and getting good examples. When you come to PegaWorld, you will be able to see some pretty amazing things in support of that.

Operator: This concludes the Q&A portion of our call. I will now turn the call back over to Alan for any closing remarks.

Alan Trefler: Thank you very much, everybody. We are working hard. I really hope to see all of you at PegaWorld. You should fire up your AI agents and have them book your reservations from June 7 to 9 in Las Vegas. As Ken mentioned, on the 8th we are going to have a very good and very important investor session, and we have a lot of new things to show. It should be awesome. See you there. Thanks.

Operator: Ladies and gentlemen, that concludes today’s call. Thank you all for joining. You may now disconnect.