The AI Revolution in 2025 Explained | Nurtekin Savas (PayPal)

**Laszlo** (0:08)
Data Storytellers, a long-awaited episode here on our AI executive series. Nurtekin and I connected a couple of weeks back, and we're excited to explore a very interesting conversation about AI and also other topics. So Nurtekin, first of all, welcome on the show.

**Nurtekin Savas** (0:29)
Thank you, Laszlo, thank you for having me.

**Laszlo** (0:33)
Absolutely, so look, before we dive into your career playbook, I have a bunch of questions that I want to ask you about what you've done over at Fidelity and Amazon and Visa, and obviously now you are at PayPal. Now, before we dive in or even before kind of like an in-depth introduction, it's a very dynamic space today in AI and analytics, right? So Gen.AI kind of lit everything on fire. It was the spark that really catalyzed this huge revolution that we're living through. I always like to say that we are in an AI bubble, but it's the kind of bubble that the dot-com bubble was, right? So it bursted not because the internet ended up being not such a big deal, but because the revolution was so huge that market forces naturally behave in a certain way in that environment. So what do you make of this whole AI landscape? It's an intentionally large question that I'm asking you, but how do you see things being different from even two, three years ago, right? Which is a long time in the 21st century.

**Nurtekin Savas** (1:39)
Yeah, hey, thanks. That's a very relevant and important question. Obviously, AI is going extremely fast and there are a lot of people working on it. I think in a lot of ways, it's similar to other tech revolutions, like you mentioned, the Internet Revolution. And if you look at other historical technological innovations, this seems similar in a lot of ways.
It's a pivotal point in how humanity is going to evolve, but also in a lot of ways, it's different. One way it's different is, in my opinion, the number of people, whether those are scientists or practitioners that are interested in it, that are working on it, that are trying to build on top of one another. And that's one of the reasons why it's going so fast and so quickly and changing on a day-to-day basis. So it's in our everyday lives, and we're using it, and as we're using it, we're all providing feedback to the people that are working on this. So I see this trend continuing. I think, I don't know. I mean, it would be speculation to say there's going to be a bust coming soon, although I did read a Gartner research today that 40 percent of agentic AI use cases will be canceled in 2017 So that gives you even more sense of how fast things can go up and down. But that's even speculation. And I think as long as you are applying AI in a way that makes sense for whatever your use case is, I think the chances are you'll be successful. And if you go back to the principles of, hey, we're here, like if you're a for-profit organization and you go back to the principles of, I want to improve customer experience, I want to generate profits, or I want to improve some sort of operations, reduce cost, and you use AI in that direction, and you experiment your way into it, I think you'll be successful. I don't think it's going to be a across all industries type of a bust. It's probably going to be folks who are using AI just for the sake of AI, some POCs just to show people that they're applying AI.
They may fail and they will likely fail, but the ones that have good foundational and building on top of that, I think they're going to continue to succeed and continue to advance.

**Laszlo** (4:15)
Absolutely. And I like how you put it that it would be a bold prediction to say that that will be a bust. And I think that even if there's a little bit of a burst, it's more like a market correction rather than a bust. I mean, I think most people already forgot about the dot-com bubble, right? It's just basically from our perspective, everything just changed overnight, even though on the ground at the time, it was less clear and it was a little bit more messy. And I actually saw that Gartner research today, right? It just came out, I think, this morning. Now, what's interesting is that, correct me if I'm wrong, but Gartner and we love Gartner, by the way, all of our members are also Gartner members. I think they do fantastic work, but you can't get everything right. You know, even McKinsey gets things wrong all the time, right? But I think they did get Jenny I wrong, right?