Pegasystems Inc.

Thank you for standing by. My name is Carly and I will be your conference operator today. At this time, I would like to welcome everyone to PegaSystems 1Q2026 earnings call and webcast. All lines have been placed on mute to prevent any background noise. After the speaker's remarks, there will be a question and answer session. If you would like to ask a question during this time, simply press star followed by the number one on your telephone keypad. If you would like to withdraw your question, press star 1 again. Thank you. I would now like to turn the call over to Peter Welburn, Vice President of Corporate Development and Investor Relations. Please go ahead.

Thank you, Carly. Good morning, everyone, and welcome to PegaSystems Q1 2026 earnings call. Before we begin, I'd like to read our safe harbor statement. Certain statements contained in this presentation may be construed as forward-looking statements, as defined in the Private Securities Litigation Reform Act of 1995. 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're 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 December 31st, 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 March 31st, 2025 foreign exchange rates to all periods presented. Reconciliations of gap to non-gap measures can be found in our earnings press release. And with that, I'll turn the call over to Alan Treffler, founder and CEO of Pegasystems.

Thank you very much, Peter. I've just gotten back from a few weeks on the road across Samia and the U.S., including an AI conference last week. And it's interesting because I think we're pretty practiced at separating hype from what's real, but there is a lot of confusion out there. Nonetheless, I'm hearing consistent themes from leaders and clients and 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 effectively. 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's what Pegger provides, a harness for enterprise AI. Blueprint to help reimagine how work should run and have people rethink their businesses and then the packet platform to operationalize it with confidence and evolve it as regulatory demands involved now there's a lot of noise about the future of the software industry itself and it's creating some real confusion and some real moments of doubt and bias some investors i've met unsure what the future looks like and are even questioning the long-term viability of enterprise software vendors Well, we think AI will be good for some and bad for others. And for Pega, it will be good. The reality is that enterprises don't succeed based on the alternative of coding fast 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's us. When outcomes matter with customers, regulators, and systems that must evolve from decades, AI-generated code still needs structure. Certainly for the types of things we do, you have very small things. You can just five-code them together. But AI doesn't 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're seeing is now running of costs and giving non-deterministic outcomes. At the moment, you weaken your enterprise platform. You make your whole business weak. Putting AI in the middle in an ungoverned way, well, that's, I think, just 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 agent-to-agent interactions, or whether you want to use AI 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. So let's talk about how mission critical enterprise software really is built. Enterprise applications has always been around a continuous life cycle, regardless of technology. There's not a single build moment. You need to design and align on what the software must do and how it must perform. And that design really can involve collaboration for many parties. And having a collaborative environment like Blueprint that brings the power of the internet, the power of best practices, and the power of a customer and or partner's thinking all together in a way that they can understand, experience, and improve is absolutely central to getting to a great outcome. You've got to build it. And there are lots of ways to build it, but the great news about something you've done in Blueprint is it's basically built. You need to be able to execute or operate it, to run it, scale, secure, make sure that it's performant, that it's being watched and managed. And with Tagger Cloud, which you'll see is really, really continuing to grow beautifully, we give our customers a place to execute that is without parallel. And 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's absolutely critical to get businesses not just what they want to get done in two weeks or four weeks 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 key factors. It's the thing that lets you design it, lets you collaborate. It makes the build trivial. It 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, you can understand, and you can direct change from. And that ultimately to us is how this lifecycle operates. in this new AI frustration age. While LLMs dramatically accelerate the build, they don't replace these other key factors, nor are they going to be able to. That's why clients need Pega. You know, some people are going, well, I only just got software. And certainly AI can generate code quickly, but prompt to code alone falls short. It doesn't tell the enterprise what should change. And the gap we have is encoding speed, is understanding what's there and making sure you don't accidentally change something with unintended consequences. When you're operating at the speed of the prompt, it's actually easier to do that, not harder, particularly if you haven't put out a nice, solid architecture that makes what's going on visible. Now, we do run into some people who say that they believe in AI-only execution. Why do I need a workflow engine at all? Why do I need a harness at all? Why don't you just simply turn everything over to general-purpose AI agents and manage it and just have, say, a control power that watches what's going on and reports out and keeps things in line? But I'll tell you, these create systems that are difficult to test, expensive to run, and nearly impossible to evolve safely. NLMs are incredibly sensitive to even the tiniest bits of additional data. And a new version of the NLM, and let's look at how quickly they're coming out, can often behave differently from the one you used just the day before. I think it's safe to say that for many types of work in provision, Improvisation is not a reasonable business strategy. People want predictability and reliability. But the other thing which really broke last week is that this approach to AI reasoning is becoming cost prohibitive. I hear growing discussion about the cost of Gen AI and how teams are bouncing between token maxing in which they try to tell the team to use as many tokens as possible, to rationing tokens, to usage caps, to surprise bills. The concerns are real, but they reflect the misapplication of AI, using the wrong AI at the wrong time. When you ask Gen-I to reason at runtime over and over again for processes you've 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 Gen AI can brilliantly explore options, map work for flows, 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. Gen AI isn't expensive, but misapplication is. And the smart organizations will stop paying the LLF to relearn their business every five minutes. Success in the enterprise doesn't come from AI reasoning everything on the fly. It comes from executing redesigned work, reimagined work within clear, governed structures. Our architecture uniquely allows enterprises to design intelligence into how work gets done, not bolted on afterwards. Now, since we last spoke, we introduced new five coding tooling into Beggar Blueprint. And this combines the speed of AI augmented design with security and predictability that Blueprint gives. You can try it out on Pega.com slash Blueprint. Remember that Blueprint facilitates the reimagination of critical work, not just the development of applications. And 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 Pegas 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 agentic capabilities. So we're also winning awards for our software. We've already this year received four awards for innovation related to how we're leveraging AI, including a product of the year award. Now, we love receiving awards for our work, But personally, it's 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 Vega software. These sorts of recognitions reinforce our strength and the need to be able to orchestrate complex service journeys and apply AI predictably. Now, this is not theoretical at all. If you take a look at how this is playing out, we recently had one of our customers, Proximus, Belgium's largest telecommunications operator, use 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 credit-typing blueprint in 15 minutes and went live in weeks. And numerous other great names, NGIN, Vodafone, National Australia Bank, have really been able to drive change and include a redesign and include extensive automation all AI powered. I love that customers are excited about this and that they're going to be coming to Pegaworld in quantity to talk in detail about what they're doing. And these same stories that you just heard and others will be shared at Pegaworld in June in Las Vegas. Because the way that I think we all learn is by seeing what other clients are doing. And it is such an honor and it's wonderful that customers are willing to come and do that. It's from June 7th to 9th, and I would say it's 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 these 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. You know, we'll discuss large-scale legacy modernization, leveraging Pega Blueprint and AWS Transform to re-architect decades of legacy core system. And I would say that what is also exciting is the breadth of industries. Wells Fargo will talk about how they highlight AI decisioning across billions of customer interactions. So, we're going to have great customer stories, but I'm also going to tell you that this year, we're going to have a tremendous product agenda that we're going to be releasing. Because this is going to be a very substantial year for the product. You've already seen what Blueprint has done. And Blueprint AI has fundamentally changed the upfront design and the reimagining of how people should work with systems. What we're doing this year and what you'll see us be able to show at Pega is how Blueprint AI is moving into the entire development and support suite so that that interface, that AI driven guidance and that power will operate from the moment of visualization and inception that you get from Blueprint all the way through to how you complete a system and how you support a production system. I think this is the most consequential change to the underlying technology that I have seen. And it's there to support the agentic process fabric technology we have that then allows all of your Pegasystems and even non-Pegasystems to be able to operate as a connected orchestrated network for the next generation of technology. I think only Pega has the efficient runtime intelligence, the deep design time skills, the experience with these key workflow harnesses, and is going to be able to put in your hands the way for you to make our harness your harness. We look forward to continuing the conversation and we can continue the investor conversation on Monday, June 8th. At noon in Las Vegas, we're also hosting an investor session. So thank you all. We're working hard. And for the numbers, let me turn it over to Ken.