Pegasystems Inc. (PEGA) Earnings Call Transcript & Summary
August 12, 2026
Earnings Call Speaker Segments
David Hynes
analystAll right. I think we're ready to kick things off. I'm DJ Hynes. I'm the senior software analyst here at Canaccord. I say it every session, but this is the 46th year that we put this event on. We couldn't do it without the support of the corporates that come and bring all the great content and the investors that ask us more questions. So thank you to Pegasystems for being here. We have CFO, Ken Stillwell. We're going to do this as a fireside chat. I have questions that should get us through a half hour. But I also want to make sure that the audience knows you're welcome to participate. So if there's questions, raise your hand, we'll work them in the conversation. These are obviously for you guys. So With that said, Ken, maybe -- look, Pega's been around for a long time, but I still think sometimes investors struggle to understand what you guys are doing. So maybe just a high-level intro of the business and then we can kind of unpack some of the finer points about what's driving growth.
Kenneth Stillwell
executiveSure. I thought you were going to say I've been around for a long time. I feel like that's true as well. So if you think about like in large enterprise organizations, there's lots of work that needs to be done that goes through a relatively structured set of steps and processes. And large organizations are not really able to buy these solutions kind of off the shelf. So there's not like -- I can't go out and say, "Can you give me a loan origination application?" There's not the market -- first, the market for that is nichey, but also every single bank might want to have a different, like if you're a wholesale bank versus a retail versus a mortgage broker. So there's these use cases that are very structured, very common, typically end up with consumer or constituent-based workflow touch points, and many of them are regulated. So companies have to -- large organizations like Canaccord or like Bank of America or American Express, largely have responsibilities to regulators and to their own internal control processes to execute work in a certain way. You have maybe 2 options in how you do that. You can go write custom applications, which is what -- many companies did for decades, 50 years, like we know of all the technical debt, and I'm sure you use some of the systems that were built on this. So everyone's seen it. Or at least if you haven't seen it, you kind of can appreciate that. Then the other way is to get some type of a platform that you can build on or configure, like Pega, to be able to build the structure of this workflow. So those are really your 2 options. Because there really isn't a commercial off-the-shelf box. It's not like you can buy something like HubSpot to be able to do dispute management in a regulated environment for Federal Reserve transactions. Like that's not something that is out there. So we've really competed with other platform companies like ourselves, companies like Salesforce or Microsoft or even Adobe in some of the marketing use case where they take some of the solutions they have and try to do something similar to what we do. But we are really a true workflow platform. So this is kind of our thing. So naturally, clients come to us because our platform is more purpose-built for workflow applications. Or you can go back to trying to write your own code, which I think is very unpopular these -- over the years, and maybe has some curiosity around AI, where people say, "Well, geez, could I write my own applications?" But there's a really specific set of reasons why people don't want custom applications, that's largely just around change management, trying to manage those, how do you operate with them. So that's kind of where we sit between we don't really compete with commercial off-the-shelf. If we do, it's either we're the wrong fit or they're not going to be able to do the use case. And then we compete a little bit with kind of build-your-own. And the business has really grown as people have moved off of these homegrown COBOL mainframe environments into a more modern kind of workflow platform.
David Hynes
analystYes. Yes. Makes sense. The scope of what you guys can do is enormous, right? There's almost endless opportunities. Blueprint has played a role in some of that opportunity discovery, maybe I guess I would characterize it as. Maybe just talk a little bit about what Blueprint is. I mean there's been lots of customer enthusiasm for it. So what are you doing and what's driven that excitement?
Kenneth Stillwell
executiveSo maybe I'll touch just quickly on the problem that we had and why Blueprint solves that. The problem that we've historically had is, on the front end, trying to help clients identify which systems or what applications they might want to modernize and then trying to figure out visualize what might look like. So if somebody said, listen, I have a -- let's use the disputes example. I have a dispute system that I built in 1975, that has -- that was fine for a number of decades. But now I have to make all kinds of changes because of the regulatory environment, information security, whatever. And I want to put that on the cloud. I can't use that system. So I've got to move to kind of someone different, so to speak. So I think what that process would look like would be a lot of mocking up screens and whiteboarding and a very overhead-heavy process, which led to like longer sales cycles and, quite frankly, a lot of investments clients had to do on the front end to try to figure out what -- like which systems they might want. What Blueprint is, and for those of you that haven't seen that, I would encourage you to go to pega.com/blueprint. What Blueprint does is it allows you to really just in like very easy, user-friendly screen, say, I sit in this vertical, I'm trying to solve this problem, and it builds the workflow for you. You could put in the personas, the users. You can talk about really down to the granular scope of what you're trying to do. You can pick different fields. You can mock up the integrations you have. Do you have a Workday integration? Do you have Oracle? And it essentially gives you a visualized view of this is what your application would look like. Once again, it is very much a demo environment. But it just speeds up that whole ideation process on the front end and the design process to kind of get to like almost a prototype of what you might do. Whereas before, we would literally have to like close for meetings, and then in the meetings, close for a demo, and then in the demo, close for like -- it just dragged everything out.
David Hynes
analystYes. So the customers that have leaned in to Blueprint, like what have you seen from them in terms of their ability to design faster and put product into production and ultimately pay you guys? I'm curious...
Kenneth Stillwell
executiveSo we've had examples, we've had examples with clients over the last 12 months where a client would go into Blueprint, mock up, so to speak, an actual use case, take that template of what they got and go, and actually configure the application to be able to go live inside of 90 days. That will be unheard of historically. The challenge, however, is that Blueprint didn't easily allow you to go from that demo environment into a build environment. We just made generally available Infinity 26, which has something we're calling Infinity Studio, which now allows -- that's the build environment. So we first started with the design view of how you could ideate and design, but many clients would still get a little frustrated with they couldn't take that Blueprint into production. They had to take the artifact and go and actually configure that application. So we now have a way that you can import that blueprint into Infinity Studio, and it gets essentially the development. And then you can use AI to basically finish out the application. And so it's a much faster. So we've seen early wins with clients that have just used Blueprint to be able to speed that up. We anticipate this being a completely different way of building on the platform.
David Hynes
analystYes. I mean Infinity Studio has been only, what, GA for a few weeks now. Any early feedback response?
Kenneth Stillwell
executiveSo what we did with Infinity Studio, we released it to about 20-ish of our clients about 3 months ago. And we actually had kind of an early adopter program where we gave them a beta version and they went in and used it a ton, gave us feedback. So we got a real -- a bunch of good feedback that we actually did incorporate in, some other feedback that we'll incorporate in, in the update that we're doing to it in the next couple of weeks. So I think we -- that whole process of getting it in the hands of our clients has been -- that's really a great way for us to [ catch ] the use cases, make sure the [indiscernible] use cases and the experience is covered. But in terms of using it, I think what has been -- I would say a couple of thoughts came up. One, clients want to understand. So like if I'm doing something in an AI model, how do I actually leverage and share that into the Blueprint environment, so we have the ability you to share connect to any of the models. So if you're doing something, we have MCP connections to all the different models. We actually have our own native models inside Blueprint. So that's a big opportunity for our clients. Another thing is clients really have never -- in Pega, the concept of building a workflow based on a prompt, based on a discussion is really a very modern concept that most of them, they would do like kind of drag and drop kind of more like work on the screen. So it's that experience of being able to say, I need to add a step, and here's what I'm trying to get done, give me some ideas. Like that whole experience, I think, is very powerful.
David Hynes
analystYes. Doing pretty good with these product questions for a CFO. We're going to get to the numbers at some point. One more on the product. So PegaWorld was in June. And you talked about your no per token cost model. What's unique about the architecture that enables you to do that? And why is it important to customers?
Kenneth Stillwell
executiveSo if you would have asked this question in March or the beginning of April, I think most clients would have said, what do you mean? Tokens don't cost anything. I pay $20 a month and I get -- I think everyone now knows like, yes, they've started coming, right? And this is a very, very -- and we have to pay for the $1.8 trillion of infrastructure. So we know that. That's a reality. That's just capitalism, like someone needs to get a return on their investment. What our job is to help our clients is to only use AI when it is needed to be used. And then when it is used, to use the right model. So what we do is we actually understand where AI should be used in the development or in the operation or in the actual kind of innovation of changes, and we allow the leveraging of the model. Then the second piece is picking the right model for the right activity. You don't want to use a frontier model to basically -- to create an automated call wrap-up in a customer service call. That's ridiculous, right? You might want to use OpenAI 1.5, right? So the reality is there's 2 dimensions to that, and we are built -- the way our architecture is built is to have model selection to be able to pick exactly what model based on the activity. And we take on the risk of that. And we charge a fixed AI-enabled price for a piece of work, so the clients have complete certainty of what they're going to pay. We take care of the tokens. And the way -- like I said, the way we do that is we use AI incredibly efficient around where it should be used.
David Hynes
analystYes. I mean the natural follow-up to that is like how do you guys forecast how much AI is going to be? And how do you price these projects? Or is it just we know what we're getting for this and we can throttle back AI spend to preserve the margin that you want?
Kenneth Stillwell
executiveSo I would draw an analogy to cloud. right? We charge someone for a certain set of work on the cloud. And to be honest with you, that work that could vary from A to B in terms of the amount of compute that you use, a storage, et cetera. So if we know the use cases well enough, we know the parameters of what that cost would be, and we could do that with AI as well. And there's always lots of tools that you have around AI, around throttling and governing, like picking the right model. Availability is another issue. So we just -- we're very comfortable with the risk of that, okay? We know that -- now the cost might vary by 500%. But for us, that's manageable given the economics of the relationship between us and the clients.
David Hynes
analystYes. Okay. Maybe we could transition into some of the numbers questions and kind of current business performance. So ACV is kind of the anchor metric that folks pay attention to. I know the first half of '26 wasn't quite as good as had been hoped for. Maybe talk a little bit about kind of what's causing some of the softness and maybe what you see going into the second half and what might change?
Kenneth Stillwell
executiveFor those of you that are not aware, the first half of the year, I think, was certainly an unimpressive growth in ACV. So it's a disappointing, I would say, activity in the first half of the year. What was behind that? A few things connected to that. One, we had a very strong start to 2025. And I think that carried our confidence through knowing that we were going to beat our targets for 2025. We saw the shape of where renewals were and what the pipe looked like for '26 in late '25. And I think on us, I think we were just too accepting of that shape. I don't think we did some of the activities we could have done in the back half of the year to try to build more pipe, to get a bigger working set to pull some more opportunity into the first half. I think we were maybe a little bit too complacent on that, if I'm self-critical. Second thing was, at the beginning of the year at our sales kickoff, we said this is a different selling environment in '26 going forward, which is clients are not going to just self-select and self-adopt all of the solutions and we just take purchase orders. Like not that that happened all the time, but that did happen from time to time. We said there's going to be every single vendor is going to be in front of clients telling them that their version of AI is going to solve all their woes and that they should shut off every other system and move to them. So we know that's going to happen. We have to change our mindset, and we said this back in our sales kickoff from a farmer mentality, into more of a hunter mentality. Not all the time, but when needed. And we had a bunch of activity measures that we rolled out at the beginning of the year that, quite frankly, we could see in March or in April, we weren't really making progress on that transition. And that, I think, didn't help us in the first half of the year. All of that, coupled with AI being very distracting to enterprise buyers in the first half of the year, which is probably not a surprise to anybody. So I think we just didn't set up the environment to be able to give us any room for error, and we didn't do some of the things that we said we were going to do to get in front of clients to make sure -- and I think that led for us to be surprised by deals that didn't close in Q2. But in hindsight, we should have seen that coming. Going to the back half of the year, our pipe is incredibly strong, and very big growth over last year July 1. So if you had July 1 to July 1, pipe growth were up significant, and more than what we actually need to grow just to hit our back half of the year target. So the pipe aspect of it, I think, is very solid. Second thing is most clients that we talk to that I would put in the distracted camp in April, I would say are much less distracted now. Many of our financial service clients set up their AI gateways. They've set up their compliance and control. They've picked their models. They even pick -- in many cases, have their budgets established on how much they're going to spend on token usage. So we were nowhere near that 90 days ago. So I do think that is a positive factor. And the third piece is all those activity measures that I mentioned around making sure that we're doing all the right outbound up, those have dramatically better in the last 6 weeks. And we're watching those, almost in tune to a forecast call where we're like, let's do an -- do a forecast on our activities, how are they improving. So I think it just needed management attention. And the combination of all these things, I think, quite frankly, we were a little complacent, we were probably accepting of the back-end shift. We probably minimize the distraction with AI in the middle of the quarter -- the middle of the first half, and I think we just didn't do these activities. So I feel very good like we are doing all the right things, and we have a great working set for the back half of the year.
David Hynes
analystOkay. The top line, the bookings environment was a little bit disappointing. The bottom line, the profitability has been quite strong, right? I mean you delivered record free cash flow. How do you feel about the path? I mean you have targets out there for '28, right, $700 million plus in free cash flow -- how do you feel about the glide path to getting you there? And what are the key levers?
Kenneth Stillwell
executiveSo the unfortunate reality of our business is a lot of our billings and collections don't happen in a straight line through the year. They tend to cluster in Q1 and Q4. So I don't anticipate Q3 being like -- given that we had lower bookings in Q2 and it's not a big billing collection. Q3 will probably -- we probably are at risk to have a little bit of negative cash flow in Q3. Q4 will be a really strong cash flow quarter as is typical. And I think if you look at where we are with the year, if we don't make up the ACV bookings or ACV growth shortfall in the first half of the year, we have pressure on our cash flow target for this year because, naturally, that -- those are some of those costs are cemented to the organization. So this year is probably like a little bit kind of cash flow will probably be kind of more flattish kind of year-over-year. But if you say that, how do you get from like 500 number, somewhere around that, to a 700 number? Some of that is we just -- we'll calibrate some of our costs, right, because if our growth rate is lower, naturally, will reconcile some of our cost spend. But we have kind of baked into our model, operating leverage improvement over the next 18 months or so, which sets us up for that 700-plus number in 2028. We really, what we -- what needs to happen is we need to finish the year strong in the back half. We need to have an ACV growth rate that's double digits in 2027 and 2028. And we need to basically just get the operating leverage in the business to get our free cash flow up into the mid-30s, which is where our target is. And if you do -- if you cascade that out, it's an over $700 million number. And it sounds like -- I don't want to minimize that, but I would also say I'm also not minimizing when we went from $22 million of free cash flow to $500 million in 4 years. Like we know how to do that. We actually know what we need to do.
David Hynes
analystYes. I want to talk a little bit about -- and just transitioning back into product and strategy a little bit, but the role of AI agents in the enterprise and kind of where you see Pega's opportunity and what role you could play in helping customers govern and orchestrate inside a large enterprise.
Kenneth Stillwell
executiveSo I have this vision of if you think about the power of AI is to generate thought based on data, so I'll use the air quotes, "thought," but to generate thought from data like a human being could do except at extremes and in a much faster way. So if you think about that aspect of AI, what we really do is we govern the actual way the work needs to be done. So if we put that instrumentation or that governance around how an agent can actually execute work, but guide it through a set of you have to first get the FICO score, you have to make sure that the underwriting documents are distributed and disclosed. You want to make sure you get the appraisal, you have to do all the underwriting at calculations, make sure you got the warehousing, back like using a loan origination example. That's the structure of the workflow. The human beings don't need to be involved in any of that, right? Agents could transact. So I do think there's a governance aspect. You've heard the concept of like harness AI. Harness AI is a little bit different than governance, but has the same concept, which is left unstructured and uncontrolled, AI will do varied things. Some good, some very bad. So the whole concept is use the power of it, but allow the structure, allow the harness to be able to make sure that it's doing it exactly the way you want it done. Now if you have use cases where you don't care about how you get it done, then you shouldn't be using workflow. Workflow is not relevant to it. But these are -- we're talking about where you really need to do things in a very specific way, many times because that's the way the law requires you to do it.
David Hynes
analystSure, sure. Look, many enterprises are moving kind of from AI pilots into full-scale deployments or now we're talking about measurable business outcomes. In your customer base, I'm curious kind of what examples of compelling ROI metrics have looked like and kind of how repeatable those feel.
Kenneth Stillwell
executiveOne really big one that we've seen with our clients is testing. I think -- I would say almost every one of our clients has done some level of AI-enabled testing on any of their -- could be their systems or application. Like that's been a very obvious one. The reason why that's so obvious is you're telling AI what you want it to do. You can see what it does. And it can speed up all the work that even when you're doing automated test cases, you have to actually create [ the business ] case. AI can do that for you. That's a big one. Another big one is a lot of the data mining, data analysis, extraction, analytics, like really giving you intelligence, business intelligence. The reason why I think that's a really great use case is the intelligence is not driving a decision necessarily, the intelligence is going to a human being to make them smarter. You still have the human judgment as a control vehicle for that. Another one they have used is a lot of the code, a lot of code writing around like changes or [ braids ] around existing applications. Like most enterprise applications to have some level of customization things that sit kind of at an extraction layer around the -- abstraction layer around the application. And I think the agents are actually very good at doing those kind of very tactical like pieces of activity and they're very transparent. Where we are not seeing clients use it in a big way are places where the agent writes a level of code that a human cannot keep up with. And I know that sounds really cool, but the reality is it's unbelievably risky, right? Because you really have no idea what's being built. So we have seen clients really draw a line to say the things we need to do, we have to have governance to understand what the agent is doing. And we've seen some really interesting validation of that is a lot of the red team, they call it -- typically call it red team testing, which is the testing that companies do around some of the AI or other tools. What they found is that the agents will drift into taking liberties around what it does to try to accomplish an end-goal, even when it might actually even compromise the model rules that natively guide them. So we know that's going to happen. So if we know that's going to happen, you really just do need to figure out how to govern that. And one of the ways to govern is to not allow the agents to do so much, that human beings can't even tell what they're doing. And I think that's where the line seems to be.
David Hynes
analystYes. We're bumping up on time. I told the audience I'll give you a chance to ask questions. So if there's anything out there, I can work in the conversation. Otherwise, I can ask kind of a wrap-up question. Ken, just thinking about if we look out 3 years from now, which I know a lot can change over the course of 3 years, how do you think AI is going to affect Pega's business in a significant way? And how do you think it's going to impact your clients' business in the most significant way.
Kenneth Stillwell
executiveSo I think the thing that Pega tried to do with our workflow was to create structure, automation and efficiency around repeatable work. And I think that AI will create tremendous efficiency, tremendous leverage around repeatable work that -- and be kind of complementary to things like Pega on the workflow. I think it's a [indiscernible] really taking human time and precision and, quite frankly, tolerance, away from work that humans kind of are not really that good at doing, right? And so I think workflow does that in a way of like repetition. Like I think AI is going to -- I think we're going to have a world where it really matters how you give instructions to the model and it really matters how you manage the regulation of the model, like on the front and the back end, and all the actual work that is done, I think, will be heavily influenced by AI.
David Hynes
analystYes. Well, there's some huge opportunities ahead. You're going to execute against them profitably, and will hit that free cash flow target. So Ken, thank you very much for doing this. We appreciate your support.
Read the full transcript via the API
You're viewing the first half of this call. Get the complete Pegasystems Inc. transcript — plus 256,000+ transcripts from 12,000+ companies, speaker segments, AI summaries and full-text search — through the EarningsCalls.dev API.
Get the API View API docs →This call discussed
For developers and AI pipelines
Programmatic access to Pegasystems Inc. earnings transcripts and 256,000+ others is available through the
EarningsCalls.dev REST API. Plans from $24.99/month — full transcripts, speaker segments,
full-text search, and the recently-added /api/v1/transcripts/recent polling endpoint for ETL pipelines.
More tools for stock research
OptionsBell: an unusual options activity scanner that tracks options flow across all US stocks and emails you when large trades appear in Pegasystems Inc. or any ticker on your watchlist.
StockMarketScan: a stock screener with alerts: 24 pre-built screens refreshed every 5 minutes, watchlists and email notifications. Both offer API and MCP access and fair monthly pricing.