#541 AI adoption is driving enterprise transformation, with Peter van der Putten, Pega

We are here at PegaWorld iNspire at the MGM Grand in Las Vegas, Nevada we’ve been seeing some amazing things, including how AI can transform the enterprise and I’ve had the opportunity to be hands-on at the Innovation Hub.

A study unveiled today at PegaWorld, conducted by research firm Savanta, surveyed more than 500 business decision makers across enterprises worldwide on their understanding and use of AI, as well as the challenges and opportunities they see in successfully implementing the technology.

Joining us today is Peter van der Putten, Director AI Lab at Pega, to discuss the meaningful AI in the enterprise and this recently-announced research on the rise of creative and analytical AI within global businesses.


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Greg Kihlström:
We are here at PegaWorld Inspire at the MGM Grand in Las Vegas, Nevada, and we’ve been seeing some amazing things, including how AI can transform the enterprise. And I’ve had the chance to be hands-on with some Gen AI tools at the Innovation Hub. We’ll talk about that in a little bit as well. A study unveiled today at PegaWorld conducted by research firm Savanta surveyed more than 500 business decision makers across enterprises worldwide on their understanding and their usage of AI, as well as the challenges and opportunities they see in successfully implementing the technology. Joining us today is Peter van der Putten, Director AI Lab at Pega, to discuss meaningful AI in the enterprise and this recently announced research on the rise of creative and analytical AI within global businesses. Peter, welcome to the show. Yeah, thanks for having me. Yeah, looking forward to having you back on the show, Returning Champion. So for those that missed the previous show that you were on, can you give a little background on yourself and your role at Pega?

Peter van der Putten: Yeah, no, absolutely. I’m the director of the AI lab. So as you said, I’m responsible for AI innovation. So helping our clients kind of imagine, you know, how they can improve their business, provide better service and experience for their end customers or become more efficient. But also, you know, as we say at Pega, we should kind of not eat our own dog food, but drink our own champagne, right? So the idea then is how can we further, you know, improve our own product offerings or go to markets, you know, using AI.

Greg Kihlström: So we’re going to talk about a few things today here and touch on the research in a few different aspects. First, I wanted to talk about just the influence of generative AI. Certainly, it’s been impossible to escape. I don’t think I’ve done a single show that hasn’t talked about it in some way. whether it was the focus or intended focus or not. But, you know, the research indicates the significant influence and how enterprises have really looked at generative AI as a way to, you could say, open the conversation about AI. So can you elaborate? I know last time we talked, we talked a little bit about left brain, right brain. Can you talk a little bit about, you know, how generative AI, this right brain generative AI is kind of setting the stage for the left brain analytical AI solutions and enterprises?

Peter van der Putten: Yeah, no, absolutely. So where, you know, generative AI is right brain, creative AI, we also have our left brain, which is, we think at least, you know, has to do more with making optimal decisions, you know, like predicting, you know, the impact of certain actions we could take and then translating that into what it is, what we need to do. But it could also be other technologies like not just decisioning, but process mining or other technologies that help to make sense of real time data or streaming data, et cetera, et cetera. Obviously, I think left brain AI has been in use within companies for years and years and years. But then it always was something that yeah, in a way was very popular but in very distinct pockets in the organization, right? So, similar to this quote of the future, what is it, the future is already here, it’s just unevenly distributed. And that meant it wasn’t really kind of democratized, right? And generative AI came to us actually through consumer-based applications, right? So where your mom was creating cookie recipes or whatever, your kids were making funny pictures using DALI and whatnot. So it’s a much more kind of democratized form of AI. Hence, many more people within organizations, like CEOs, ask their reports like, hey, my kid is writing her thesis with Gen AI, why aren’t we using it in the company, right? So I think that kind of, I think that’s a little bit the history of it all. left-brain AI in use for ages, but in particular pockets, and the people who are kind of running it was like a very small group. And here came generative AI that basically anyone in a company had some form of exposure to. And, you know, that kind of started in the conversation, oh, should we not, you know, use AI here, there, left, left, right, and center? But of course, in many cases, it wasn’t maybe a generative AI use case.

Greg Kihlström: Yeah, it kind of made it mainstream, even though it was already in some cases being used within the organization, but it kind of opened up that conversation.

Peter van der Putten: Sometimes it is a straight-gen AI use case, but in other cases it turns out to be more of a, yeah, I’m always trying to find a better word for, I don’t want to say traditional AI, like I said. AI geek that hurts, if I would say that. But let’s say left brain AI.

Greg Kihlström: Well, you know, another thing in the research that I found really interesting was you could characterize it as high confidence in understanding and yet In reality, some of the leaders or many of the leaders surveyed said they knew a lot about generative AI, but when they were actually able or asked to explain it, didn’t have as great a grasp. To me, probably says a couple of things. One is we’re probably at peak hype cycle probably for all of this stuff. Not necessarily a bad thing if enterprises are using it correctly, but you know, why do you think there is such a discrepancy?

Peter van der Putten: Yeah, I think it might have something to do with what’s the name of the effect again? There’s a phenomenon where, you know, like If people don’t know a lot about the topic, they kind of overestimate their abilities.

Greg Kihlström: Yeah, I know what you mean.

Peter van der Putten: Yeah, exactly. So that might be a little bit at play here. And I think in many cases, people kind of have a sense of what generative AI is, but then they can’t really Imagine what these other forms of AI are if they, you know, if they don’t come from that AI community or, or, or backgrounds. Right. So I think that’s, that leads them to confusion or labeling everything as if it’s generative AI, where certainly that’s not the case.

Greg Kihlström: Yeah. Well, so speaking of generative AI, you know, one of the, one of the big announcements was around gen AI blueprint. I got to try it hands on in the, in the innovation lab. Pretty cool. Um, made my own, I posed as a retail banking, um, company and created a whole workflow and stuff. But could you first, maybe for those not familiar with it, could you talk a little bit about, you know, what is it and, and you know, what’s it intended to do?

Peter van der Putten: Yeah. Great, great question. So, In many cases, Gen AI is used for, I would say, for productivity hacks, right? So nothing bad with it. Like, let’s say you have a call center and you’re doing a lot of conversations, then it’s useful to summarize that conversation and play it back to a customer. But that use of AI was very useful. It’s not necessarily transformational. Yes. Backup Blueprint is more an example of something that could be transformational in the sense that it let us imagine here kind of new ways of, well, if you want to build a new app for a loan application or deciding whether someone can get certain government benefits or maybe something way more exotic. I think mud logging was one of the examples that you mentioned in the keynote today. Now then, based on very simple prompts of, yeah, what is it what you’re trying to achieve, it will generate an entire working application, right? So, what are particular workflow or process or what kind of data will be useful, but also what could be the experience for people interacting with this app in different channels. So, it’s really in that sense an ideation tool, right? So, it’s trying to put ideation on steroids by providing all kinds of examples and starting points for, you know, for such an application.

Greg Kihlström: Well, yeah, and I mean, I think this, this uncovers a few things that, you know, anyone who’s been through a digital transformation of any kind, I mean, there’s a lot, there’s a lot of hurdles, you know, there’s a lot to do even in successful ones, but there’s a lot of hurdles to success. And one of those, from my experience, is visualizing the end result, right? So, you know, you can do that in many different ways. You can get different views of different things, but What I was impressed by was the ability to actually get multiple views of the exact same thing as opposed to like sending out something for prototypes to this one team and like, so is that, I mean, how in your mind, you know, does that help that end transformation?

Peter van der Putten: Yeah, I think it’s, Exactly, that’s what it’s meant for, right? So we’re listening to a podcast but we’re in a typical meeting room environment. My definition of hell is when people say let’s develop a new application, let’s get into a meeting room like this with a bunch of post-its. I want you all to think from scratch and we’ll develop everything from nothing. for me at least personally a horrible experience. Whereas if you can get together with some people and you generate some examples and actually it’s kind of nice if they are all kind of the same but somewhat different and use it as fuel to fuel the ideation process. It’s such a more pleasant experience to and better experience and faster experience to get to a result. And like you say, people have, it’s this, you know, what is it, the blank page writer syndrome. If you have a blank page, it’s very hard to imagine here what it’s going to be. Whereas if you have a story in front of you, you can say, oh, I like this part, but I don’t like that part. Let me change that, right? So, and this is exactly that. And I think that that will help also involve a wider audience of people to become part of that whole ideation process, not just, let’s say, hardcore developers.

Greg Kihlström: Another hurdle that organizations often run into in transformation is, you know, there’s people, process, platform, right? So, you know, I think we’ve talked some about the process and the platform. You know, I think one of the… Most people don’t love change, let’s just face it, but change becomes easier when you’re able… Yeah, yeah. But also when you’re able to be educated more quickly and when the change process isn’t so cumbersome and when you can see the end result. And so, you know, we talked a little bit about, you know, from that blueprint side. But another, you know, another exciting thing that I saw today was Socrates and, you know, just that whole learning and training part. Can you talk a little bit about that?

Peter van der Putten: Yeah, absolutely. So Socrates, the idea is that if you, like even separate from Pega, you know, like the Socratian way, is that how to put it?

Peter van der Putten: There you go, the Socratic way to learn something. It’s not to tell you everything, but to ask you questions, right? So that’s a much better way of learning, because then you’re constantly being, as a learner, you’re kind of being challenged to think along. And of course, based on your level of skills, you’ll get more background, less background. And this way, you’ll be guided through the learning process. And because it works both ways. Like if you normally put out learning content, If it’s too difficult, that’s frustrating, but the other side of the coin is if it’s too easy, you know, many things you already know and you have to read through it and do it, like, yeah, it’s a waste of your time, right? So by following this kind of Socratic approach, you can make it much more personalized and targeted, yeah? So based on generative AI, right? So we write some prompts where we say, well, this is the content actually that someone needs to learn, but then guide the student through it, through questions, et cetera. And that will help, and also based on how you answer those questions, we can become even more contextual about, okay, you know, you got point one, two, and four, we just need to help you a little bit with point three. Yeah, at first we’re going to use that more in our kind of impact academy, which is basically our product training environment. But this is something that you ultimately just want to bring straight into the, into let’s say the developer experience as well. Right. So as and when you’re developing applications, yeah, sometimes you just want to have a straight answer to your question, but sometimes it helps. Also, if you’re being kind of guided through how to build something at the right level, you know, and that’s where Socrates can, you know, Socratic approach can work really well. And in Gen AI, you know, it’s, it’s incredibly easy to create that type of learning with, with, you know, Gen AI based methods.

Greg Kihlström: Yeah. Yeah. So, you know, speaking of learning and upskilling and all of those things. So, you know, there’s, There’s a lot of tools and processes that are getting democratized as we’ve talked about, even other things in other realms, creative and other area of marketing and those things as well, which I talk a lot about on the show. How should enterprises be thinking about, you’ve got this increasing democratization, which is helping kind of push these tools to more people. I don’t think software engineering is ever going to go away and data science is ever going to go away, but where should enterprises be thinking about when they’re reskilling, upskilling? What’s the right approach to think there with AI becoming more and more prevalent?

Peter van der Putten: Yeah, so I think one of the potential promises of AI is to make every employee behave more like the best employee, make every agent like the best agent, make every developer like the best developer, make every marketer like the best marketer. And what I kind of like is to not frame it as replacement or anything like that. I like that question that was asked today, don’t you want to be better at your job? Everyone wants to be better at their job, right? And AI should not be something that kind of replaces you, but something that assists you, right? So it’s really interesting when you, I’m a part-time academic as well, if you read some of the older AI stuff from the 60s, there’s a lot of focus not on AI kind of replacing the human, but It’s about AI as augmented intelligence. So how can you work shoulder to shoulder with a human and together you’re better, right? So I think that point of view, it’s interesting. It’s coming back now more and more actually because of Gen AI. So that’s a partial answer to your question. I think the other angle to it, I think it is important that people become AI literate. I think there’s this cliche of you won’t be replaced by an AI, but you will be replaced by an employee who’s using AI. And trust me, all the people that will flow into organizations next year, year after, these are people that went through college, that stumbled through college writing their thesis with AI. They have completely different AI literacy skills as the people are maybe working in companies right now. Also different expectations in the sense of that they actually expect the companies that they start to work for that they are somewhat ahead of the curve, not a company that has total ban on using generative AI or something like that.

Greg Kihlström: Right, right. Yeah, I mean, what do you what would you say to those companies that just have the like total the total ban? I mean, you know, what what are they missing?

Peter van der Putten: Well, you know like So I I appreciate the initial apprehension, right? So but then you need to work like quite quickly on, yeah, but what are, you know, what kind of boundaries do we want to set, etc., so that we can make good use of the technology. And specifically, you know, like, there’s a difference here between left brain and right brain, because you could get quite far in the left brain world of saying, well, we’re not doing this, blah-de-blah. Right brain AI, you cannot stop it. It’s 75, 80% of the people who are working in companies today are using generative AI as a, let’s say, what IT calls shadow IT tool. What I call actually a useful tool. So people are using it anyway. So you may as well control it and making sure that you put some proper governance around it and that you really build it into very specific use cases that drive most of the benefits and marketing and sales.

Greg Kihlström: Do you think a few years down the road, do you think that AI will be anthropomorphized, like thought of as a team member? Because it kind of feels right now like it’s headed that way. But is this just a fad and it’s hype? Or is that going to be normalized? Where do you think we’re headed with that?

Peter van der Putten: Yeah, that’s a great question because I immediately have two conflicting answers in my head, right? So I think in a way both will happen, you know, bad answer. But we are wired to anthropomorphize, right? As humans, we always, if something smells like something intelligent, whether it’s a Tesla or a teddy bear, we project creativity, emotions, meaning whatever on top of that intelligent thing. That’s just how we are hardwired through evolution, because 50,000 years ago, if something yellow, black striped, jumped out of a tree and said, raw, you weren’t like, oh, are you an object or a subject? You would run. So, hungry animal, I need to run. So, in a way, we are hardwired to do that anthropomorphization, but on the flip side, I do think that AI will be demystified a lot more. And you already see tendency right now, people get a little bit sick of just AI hype and humbug and people go like, yeah, but how can I use it for real? Oh, it’s summarizing myself. My customer service interaction. Brilliant. You know, or yeah, it’s a simulating an angry customer so that I can train my customer service agents. Brilliant. Uh, it’s, uh, helping me to ask questions with knowledge body on how to resolve a particular issue. And so it becomes way more practical and then, then we might anthropomorphize it actually less because we see it more as a useful tool, maybe a companion, but not a robotic overlord.

Greg Kihlström: Right, right. Yeah, that was one of the survey responses was there is some fear of… Yeah, around 40% of the people think, you know, like there’s risk that they will be enslaved.

Greg Kihlström: It’s, you know, hopefully we’ve got at least a few more years. Yeah. Awesome.

Peter van der Putten: They can steal my job and I’ll just be on the beach, you know, drinking a cocktail. Why not?

Greg Kihlström: Right, right. Well, Peter, thanks so much for joining. As we wrap up here, what’s been a highlight for you so far this year at PegaWorld?

Peter van der Putten: Well, you know, like at Risk of Sound, it’d be a shame for me. It’s always great to meet all the clients, you know, people, new clients that I haven’t met before, but also people I’ve been working for years and years. Obviously, as the AI guy, I cannot complain about the amount of attention for AI, you know, like Blueprint, KnowledgeBuddy, Socrates, but also other things like Gen AI Coach. Yeah, it’s AI left, right, front and center. But what I also appreciate, it’s not It’s very much not in promises, but more like, Hey, look at this real thing, you know, like, and we are going to sort out to what extent it’s really useful, but at least it’s, it’s real capability. It’s real product. It’s not, not some, you know, we’re an East coast company, right? So it’s not just some West coast talk, you know, like it’s, it’s real stuff.