Pegasystems Inc.

Hello everyone, thank you for joining us and welcome to the Pegasystems second quarter 2026 earnings call and webcast. After today's prepared remarks, we will host a question and answer session. If you would like to ask a question, please press star 1 to raise your hand. To withdraw your question, press star 1 again. I will now hand the conference over to Peter Welburn, Vice President of Corporate Development and Investor Relations. Please go ahead.

Good morning, everyone, and welcome to Pegasystems Q2-26 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 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 Q2 2026 results and on 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 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 June 30, 2025 foreign exchange rates to all periods presented. Reconciliations of gap to non-gap measures can be found in our earnings press release. With that, I'll turn the call over to Alan Trefler, founder and CEO of Pegasystems.

Thank you, Peter, and thank you, everyone, for joining today's call. Ken will walk you through the first half and after results shortly. But before he does, I'd like to spend a few minutes discussing Some major market shifts that we've seen and a lot of the tension and confusion in the market and why we believe it creates significant opportunity for Pega. The market evolution shows a structural shift in software. We're still in the early stages of the fundamental transformation driven by AI. Across the industry, organizations are rethinking how software is designed, built, operated, and evolved. For the time, AI providers acted a little bit like drug dealers, offering their products for free or charging $20 a month for what felt like unlimited usage. To many users, the experience was magical. But at the same time, the frontier model providers have been investing literally billions or trillions of dollars building the data centers required to power AI. And now, They're going to need to seek a return on that investment, making a significant share in the economics of the market. These companies are under pressure to generate meaningful revenue. And what was once available for free or for all-you-can-eat licensing is priced now by token use, with the attendant anxiety and ambiguity. And it's not done. More of this is coming. The challenge for enterprises is token consumption is opaque until the bill arrives. Many of the tokens these models consume are reasoning tokens. They don't show up in input or output, but are used by the model itself as it loops through increasingly complex logic. These reasoning costs can become surprisingly and prohibitively expensive. Now, this cost uncertainty is leading many, many organizations to sort of freeze and try to figure out what's going on and take a more deliberate approach to technology investments as they assess the economic environment. Decision cycles have lengthened as clients seek greater clarity around technology strategies, AI priorities, and the reality of highly variable token costs. At PegaWorld, we unveiled the solution offering our clients access to AI agents with no per-token costs. Our clients' demand for predictable outcomes and predictable costs plays directly and uniquely to Pega Strengths. Our clients see the opportunity to use AI to deploy software faster and more effectively, and to see the power of AI agents to automate work that could not have been automated before. But the value from this technology will not be measured in the lines of code generated or the number of agents deployed. The value comes from better business outcomes with greater speed, control, and efficiency. For decades, we have delivered software that optimizes and executes the workflows and decisions that run our clients' businesses. AI is making that software much, much easier to design and build and continuously evolve. As our tagline puts it, build for change. AI dramatically expands what is possible, but the requirements of enterprise systems remain the same. They need to be predictable, governable, secure and cost effective at scale. So our goal is simple. Help our clients avoid AI chaos and the mess that comes from it by delivering predictable outcomes at predictable costs. Our approach is different from the two misguided approaches that others in the market are offering. The first misguided approach is that enterprises should just use AI agents to code up anything they want, generating millions of lines of code. Now look, Pega has competed against coding yourself for decades. And the reality is, It went through an open source cycle where everything was going to be open source and people would code it themselves with those technologies and tools. It went through an inexpensive fingers in India cycle. But the problems with code and our moat against it remains the same. In fact, with AI, the problems with this alternative get worse. Code is hard to change. It's hard to understand. and AI generates more code with less visibility, making those limitations even more pronounced. Clients report to me that simple things like changing the label on a field become really, really hard when that field is buried in millions of lines of code that no human has ever reviewed and wasn't structured for people to really understand. The code is only readable by coders and it doesn't fit into a model that business and IT can jointly see. PEGA provides that model. Our system is built on a structured and visual foundation of workflows, business logic, personas, and integrations. These remain transparent, understandable, governable, and adaptable over time. We represent the logic in business metaphors like stages, steps, and decision rules that clients can easily understand and change. With the release of Pega Infinity last week, we took a significant step forward with the introduction of Infinity Studio. Together, Pega Blueprint and Infinity Studio now create a more complete AI-powered lifecycle that helps clients design, build, operate, and then continuously evolve enterprise systems, all in a model that both business and IT can work in. That capability reinforces what has always differentiated Pega, our ability to help enterprises build for change. And in an AI-driven world, that advantage becomes even more valuable. While with Blueprint, we apply powerful AI reasoning at design time before an application goes into production, enabling our clients to reimagine how they get work done, create better processes, and see them working in an application they can design in minutes. Blueprint takes in information about a client's business and creates a system built around the scalable structures of workflows, personas, integrations and decisions. And structure is critical. In contrast, if clients generate code directly with tools like Cloud or Codex, where's the architecture? How is the business logic captured and understood? And code-first approaches become opaque, complex, difficult to govern, and extremely expensive to change, especially at scale. When we developed and released Blueprint, it really opened up people's eyes to how they could reimagine their businesses. It brings in our decades of experience and our Blueprint agents are able to really come up with things better than even the input they're given. It's enormously exciting, and I'm constantly having clients tell me this is one of the most novel uses of AI they have seen. There's really nothing else like it out there. Blueprint enables clients to reimagine their business processes to be better, to see how those processes translate into working systems, and engage with a working system early in the sales cycle. Blueprint is transforming how we engage clients and prospects at the front end of the sales cycle, moving Pega from a conceptual sales process to an experiential and product-led one. In retrospect, when we started with Blueprint, we really focused on new clients and new applications. We have not yet brought the full power of Blueprint to help existing clients reimagine and rethink their existing Pega applications. for two reasons. First, we were learning how to use it. And secondly, helping clients reimagine existing systems is in many ways a more tricky and complex problem. But now, with Pega 26, Infinity 26, which we released last week, we've made the power of Blueprint AI available for clients to reimagine and improve their new and existing Pega applications. This release brings Blueprint AI from the design time use into build and deployment and to evolve using this Infinity Studio capability. Our completely reimagined builder environment enables our Pegacloud and ClientCloud clients to leverage Blueprint AI to deploy new applications and to improve existing ones. Blueprint AI helps businesses and helps IT leaders reimagine how organizations get work done. Infinity Studio extends the power of Blueprint AI into the application development and deployment, creating a continuous path from idea to execution. This is especially compelling for our existing clients who can use Blueprint to modernize and evolve existing big applications, helping them reimagine what's possible. But it also is terrific for new clients who can answer the question How are they going to continue to evolve after their initial build? Furthermore, we've made the whole Pega development environment available via MCP. So people who are very technically oriented could use Cloud Code or OpenAI Codex or any coding agent to be able to initiate their Pega applications. These improvements dramatically lower the barriers to entry, reducing training time and accelerating productivity and we'll enable more workflow creation across the enterprise. Infinity Studio will make it easier for our clients to build and extend their workflows. We launched it last week and we'll be rolling it out aggressively through the rest of the year. But Infinity Studio is a really big deal for our clients and prospects. I said there were two misguided approaches to AI and let's talk about the second for a moment. The second approach says, hey, just use AI agents to reason through every process at runtime. Now, people know this approach brought risks. I mean, agents built on LLMs don't execute with the consistency that enterprises need for most of their workflows. It also turns out, however, that it can be hugely expensive. We've got a calculator at Pega.com that shows you the difference between this and our approach, and it's pretty staggering. Our approach is fundamentally different. Use AI extensively at design time, to blueprint AI, and design the workflows and get them right and really make them excellent. But once you get them right, run them repeatedly at scale, thousands or millions of times, only using the AI selectively in the runtime steps where it makes sense. I like the metaphor of a chef. A great restaurant doesn't reinvent each dish each and every night, each and every paper. They take the time to design a recipe or set of recipes that work really well at scale. And that's what we do at Blueprint. And then when it comes time to execute the dinner service, the whole kitchen follows the recipe predictably and consistently. tuning it only when needed. That's our workflow running in production. Clients know how to execute effectively at scale, providing the perfect balance between AI inspiration at design time and AI used consistently at runtime. And this also means we're not using up massive amounts of costly reasoning tokens at runtime. And it's how we are able to offer Our regentic AI has an uplift to our case-based price with no variable or token cost. We use AI selectively for specific and well-defined tasks where it adds value at runtime, like summarization or reading documents. But core workflows remain deterministic, predictable in the outcomes they deliver, and efficient in the cost it takes to run them. This is a key and structural differentiator for us. It's hugely important to how our clients both ensure they deliver the outcomes they want predictably and to ensure their AI costs are tied to value. We've taken this power even further with Infinity26. Every single workflow in Pega, both new and existing, is automatically available through MCP. That means any agent built on any agent platform can find and invoke a Pega workflow. The workflow instructs the agent to operate predictably and consistently. And because the workflow does the reasoning for the agent, Pega helps our clients make even agents built outside of Pega more cost effective. In conclusion, our clients tell us they want to see increased efficiency and better results from AI. They also, however, want better outcomes of installation from runaway token costs and measurable results in increased efficiency and better processes. For much of the work they do, they don't want to re-reason a business process every time it runs. And instead, our approach really resonates. We imagine with AI, execute predictably, continuously evolve, and improve it. And this is what Pega delivers, giving clients the ability to design an effective recipe for executing worker design code. And then, when users request a business outcome, the menu at the restaurant contains the proven recipes that organizations know how to do extremely well at scale and that are consistent with regulators' needs and the efficiency the organization wants. Clients, I believe, are increasingly recognizing the value of our approach, and we have a strong and differentiated story today. The clients who saw it at PegaWorld, who I met with extensively, were extremely excited. And you can see Infinity26 just sell in Kerim's keynote, which is available on Pega.com. It's also becoming increasingly clear that while the market is still early in its AI journey, many of the key trends I think are moving in our direction. Increasingly, clients are coming to us to ask how they can manage business costs while achieving business value. As organizations move beyond AI experimentation and try to bring ROI to production deployments, they will avoid approaches that generate massive amounts of brittle code or highly, highly unpredictable economics. We think that these companies will succeed with AI by becoming those that combine innovation with structure, control, and economic discipline. Some of the things we hear just seem like madness. People talking about trying to control thousands and thousands of independently operating agents. We just don't see how that works. And candidly, I've talked to a lot of customers who don't see how that works either. Our approach instead really builds on our tradition of workflows inspired by AI for way more aggressive design and the use of AI to do the pieces that it needs to do at runtime. And we remain committed to how we help our clients get through The confusion that has been, you know, candidly promulgated by so much noise in the market about saspocalypse and software being dead, etc. I think some software is definitely under threat, unquestionably. But the types of systems we are, to build them in code would be extremely complicated, hard to update, hard to accept. And that build for change is important for our clients. These principles relate to how we are going to work with our customers to work with them, but we don't just want to help our customers bring efficiency to their businesses and help our customers run well-managed businesses. We need to also operate our business that way. We remain committed to getting through the current period of wild confusion and generating strong free cash flow along the way regardless of market conditions or how long it takes for the sort of understanding here to stabilize. We will be using and leveraging our AI technologies and capabilities to improve our efficiency and create additional operating leverage. And we will temper our spend accordingly vis-a-vis our free cash flow needs. With that, let me turn it over to Ken to provide more color on our first half.