Pegasystems Inc Rosenblatt's 6th Annual Technology Summit: The Age of AI (Part II)

Welcome, Don. Nice to be here.

Certainly. Pega is in the workflow and decision space. We drive what I would call mission-critical workflows and decisions for pretty global firms across industries like financial services, federal and regional governments, insurance, healthcare, et cetera. An example of some of this would be Verizon uses Pega's AI technology, which is sort of a decisioning statistical AI technology, to figure out what the right conversation to have with every client is when they interact with a client. We do similar things for folks like Wells Fargo and Commonwealth Bank of Australia and others. We are also used across industries as a workflow platform for things like customer servicing, investigations management, claims management, onboarding, KYC, those kinds of things.

Yeah. I have been around Pega for a little over 25 years. My background is in our support and engineering and then deployment organization. I spent many years doing what I think the cool kids today are calling being a forward deployed engineer. Back then I was just a consultant who knew enough to actually write software when it needed to be written and knew enough people back in product management that if he found things he did not like, he could get it changed.

But I did that for many years. Probably about 10 or 12 years ago, took on the CTO role really in a field-facing capacity. I spend about 50% of my time with CIOs, CTOs, chief architects at our clients and potential clients, really making sure that we understand their roadmaps, their architectural patterns, where they are going with technology, and then making sure that they understand what we are going and we understand the map between those. Then I spend the other half of my time with my team, which is really focused on go-to-market activities. Everything from brand to sales strategy to activation and corporate comps.

Well, I think there's one pain point that everybody's kind of been dealing with, and frankly, we've all been dealing with for, I would argue, since GPT popped up, which is pressure from CEOs and boards to just demonstrate that we're using AI. I think that pain point hasn't gone away. I think there's that continual sort of pressure of are we being AI first? Are we becoming AI-led organizations? Where I think the shift that I'm starting to see in client conversations is shifting that conversation towards value. So it's not just are we using AI?

I thought it was a really interesting bit of whiplash in the market in Q1, Q2, where it seemed like literally in a couple of weeks, we went from everybody talking about token maxing and putting up leaderboards of who was using the most AI and celebrating the people who are burning through millions of tokens every week or month, to a sudden realization that, wait a sec, those people are spending lots and lots of money using those tokens. That stuff is not free, and it's not going to be free. So what we really need to do is actually how do we ensure that in the concept of tokenomics, which has now kind of taken over the conversation, how do we make sure that we're governing our use of AI so that it's attached to where the actual value is?

I am seeing in the client conversations I have a shift back to not just let's do a lot of AI, but where can I use this to drive meaningful value in my business? Ultimately that comes down to where can I use it to drive better customer experiences that help me drive increased revenue. Where can I use it to drive measurable efficiency gains? Not just sort of that generic sense of, yeah, we all have Microsoft Copilot and we feel more productive, but actual measurable efficiency gains, often measured at the process or the workflow level. Things like regulatory adherence, right? The kinds of consistency that, especially in a regulated industry, is absolutely essential when you deploy any technology at scale.