Travel Through the Lens of AI with with Booking.com CEO Glenn Fogel

When Glenn Fogel joined Priceline in 2000, the business was worth a few hundred million dollars. One week later, the Nasdaq peaked, eventually sending its stock down to a dollar a share. But over 25 years later, Booking Holdings has scaled over 1000x into an over $100 billion dollar global travel behemoth. Elad Gil is joined by Booking Holdings CEO Glenn Fogel to discuss his career, from law school and Wall Street to working at Priceline through the dot-com crash, and to helping grow the business into a multifaceted, dynamic travel marketplace in the AI era. Glenn explains how leveraging AI and agents such as Priceline’s ‘Penny’ makes travel planning and customer service better, while emphasizing the importance of preserving some human support for some users. He also talks about Booking’s strategy of reinvesting over $700 million into AI and other technologies while still offering stock buybacks and dividends, the durability of their scale and complexities of dealing with a large portfolio physical properties across the world, and why upskilling is so important for employees amid concerns about AI-driven job displacement. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @bookingcom | @priceline Chapters: 00:00 – Cold Open 00:05 – Glenn Fogel Introduction 00:41 – Glenn’s Early Career 06:49 – Lessons from the Early Internet 09:24 – Deciding Factors for Exiting 10:56 – Travel Through the Lens of AI 13:30 – Agentic Travel Planning 18:59 – Agents, Token Economics, and ROI 22:46 – Booking’s Capital Investment Philosophy 25:23 – Scale as Durable Asset 29:40 – Purpose and Choosing Wisely 33:18 – AI’s Impact on Jobs 36:38 – Upskilling in the AI Era 38:36 – Public Perception of AI 40:24 – Conclusion

• 0:00Speaker 00

  There is no such thing as a moat. There is no such thing as somewhere you're going to be protected against innovation. Today, we have a competitive advantage on areas, absolutely, but those can go away tomorrow. The only window in the long term is to continue to develop new services, new ways to do things. How can we do your business better? What do you need? Where you need more demand? Where are you hurting? It's so much more complex. If you think you're just going to come in and do this business and not go away, these very big players. I'd say you should really understand what the business is before you decide to commit your capital.

• 0:43Speaker 01

  Today on No Priors, we're talking with Glenn Fogel, the CEO of Booking Holdings, a twenty-something-year veteran of the company, who joined when it was just Priceline and worth a few hundred million dollars in the year 2000, and has since helped grow it to a hundred-billion-dollar-plus company with multiple massive assets across travel that are now being used in the AI era. We will talk about a variety of topics with Glenn that span everything from the growth and changes that have happened in bookings over time, as well as his own career and perspective on AI. So Glenn, thank you so much for joining us today.

• 1:16Speaker 00

  Well, thank you very much for having me.

• 1:18Speaker 01

  Yeah, so you've had a really interesting career. You know, you went to Wharton, you went to Harvard Law. Along the way, you worked in, I think, the MIS program at Morgan Stanley. I'd love to just hear a little about your early background and how that led you eventually to Booking.com and eventually Booking Holdings.

• 1:37Speaker 00

  Yeah, I can do that. So, real short, I came out of work with Green Finance, and now I end up in the back office at MIS.

• 1:47Speaker 00

  My first job is putting tapes on a drive in a data center.

• 1:53Speaker 00

  IBM 3084s and the bus that went and the tape drives and putting the tapes on the drive. That's where I started, as an operator, actually being an operator of a mainframe. Very different, nothing that you prepared for that in college for that. And I then become, you become a developer and you, I basically learned that this is not a career for me, I should do something else. And all the people I knew undergrad at Wharton were going off to investment bank and making all this money. And I thought, yeah, I should try to do that, but you can't go. I've now gone down one shoot. And you can't just jump out of that one to go come and invest in banker. So I got a degree in finance at Wharton, and Harvard let me into law school, so I'll do that, because that's another route.

• 2:37Speaker 00

  I did that, and I end up getting a job on Wall Street as a banker. I did that for till 1995. And then the bank was bought by another bank, and they fired all the bankers, almost. Not every banker, fired most, including me, but not everybody, because they fired everybody. You could say, wow, they fired everybody. But they didn't fire everybody. See, there was, there was actually some people picked to stay, because I was not one of them. That's pretty bad. So a real good lesson, though, having been fired and knowing what it's like, that is something that I've kept with me throughout my career, about how to do it right, not do it wrong, and understand what goes through the other person when you tell them that, I'm sorry,

• 3:21Speaker 00

  but there's no longer room for you here, and it's not the place for you to be. I really learned that firsthand, being on that side of the table. And so now I'm unemployed, and my father had just died, not that long before this happened. And my father's died, lost the job, my grandmother died, and even the dog died, which is kind of sad. And I'm like, what do I want to do with my life now? My young thirties, I'm alone, I'm saying, oh, whatever. And I said, you know, I always wanted to write a book. So I start writing a book, I write a novel, I get it done. And now I'm going to try and get it published, and it's not really self-publishing, you weren't doing it on your own. You're trying to get some agent to pick it up.

• 4:03Speaker 00

  And I was introduced to a woman as a blind date friend, and she was a lawyer, but I don't know. They said, well, she used to work at Random House as an editor. I said, oh, I'm very interested.

• 4:16Speaker 00

  And so we have a date, and the book never gets published. I do end up marrying her and have two great kids. It's a wonderful life. But while I was trying to get the book, you know, an agent to be interested in it, eventually she said, you know, if this relationship's going to go forward, you should get a job. I said, Jim, I didn't want to go back to banking, and I said, I don't know. And a friend of mine from law school was a senior-type person at Morgan Stanley. And I told him, look, Amy says I have to get a job. She had any thoughts? She said, well, we have this trading position here that you could do. I've never traded anything in my life. She said, don't worry, you'll be fine. I was like, okay. So I end up being head trader for a guy named Barton Bay, he's kind of a Wall Street legend, so I do that for a number of years.

• 5:01Speaker 00

  But I just don't like it. It's not that exciting, just not to me. And that's when the internet was really taking off, that first real explosion, you know, the internet boom, that's late 90s. So 1999, I started trying to interview, and I think, well, I got some skills. But when I was an IT person, I got that, and I know a little bit about corporate development because being a banker. And I started interviewing. The only real company on the East Coast at the time of internet, you know, abilities was Priceline. And they had a job for corporate development. I was like, perfect. So I get an offer from that, but I said, I want to wait, I want to wait till I get my bonus for 1999, which gets paid at the end of February 2000.

• 5:45Speaker 00

  So I go and I get my bonus check, and I'm ready to start. And that's when, of course, that's when the NASDAQ peaked, thereby having gotten long internet a week before the NASDAQ peaked and stuff. And it proved, though, I shouldn't be a trader, having just been in the absolute wrong way. And, you know, Priceline has its difficulties after that. Our stock went from, when we went public, we, a week or so, we were thirty billion, which back then was real money, and that meant something back then. And by the time I joined, I joined after the IPO, I joined, we're probably down to about fifteen billion.

• 6:27Speaker 00

  That's now, you know, February, March of 2000. In nine months, our market cap is now down to just a couple of hundred million. And our stock is now trading at a dollar a share. We're going to get to Ulysses, because it's dropping below a dollar a share. But stick with it. We do a reverse split, make sure we don't get to Ulysses, it goes to six dollars a share. I stay, and I've been there twenty-seven, on my twenty-seventh year. And we went from that, that now reverse split six dollars, and in last summer, we came very close to six thousand dollars. Over that, you know, a little more than a quarter of a century, up a thousand times.

• 7:08Speaker 00

  And, you know, market cap was peak, you know, a hundred and eighty billion. Remember, it's a few hundred million.

• 7:13Speaker 01

  Yeah, that's amazing.

• 7:15Speaker 00

  It's been a good ride so far, but of course, you never stop. Every day's a new adventure. Every day's, you got a a big headline in the FT when I had an interview with them, I said, got to fight for a customer every day.

• 7:27Speaker 01

  How do you think about this, the lessons from that internet era in terms of the current AI wave? Because we're seeing this massive shift in market cap.

• 7:37Speaker 00

  You think like this is a huge explosion of new things, of all these, everything, just like in the late 90s? The optimism of technologies, everything is going to be wonderful. But then you get a little bit of the backlash, coming with backlash then too, and now. It's just, it's just bigger than it was then. The numbers are much bigger. The issues at hand are much bigger, the pluses and the minuses. So I just see a lot of parallels.

• 8:07Speaker 01

  Yeah, because, you know, when I look at it right now, some companies clearly have enormous revenue bases. You know, OpenAI and Anthropic are rumored to have thirty to fifty billion dollars in revenue run rate each. And, you know, in parallel, you see companies that are extremely highly valued, ten billion, et cetera, that don't necessarily have even revenue yet. And if you look at the internet era, I think it was something like four hundred and fifty companies went public in 99, four hundred and fifty went public in the first few months of 2000, maybe five hundred went public before that. So you had fifteen hundred companies, of which, what, two dozen are left at most? You know, the other thousand, four hundred and eighty are gone. And so do you think the same thing will happen to the AI set of companies? Do you think something

• 8:49Speaker 01

  different will happen? And like, and those are IPOs, by the way, those are the very strongest or perceived to be strongest companies, right?

• 8:56Speaker 00

  Right. Well, I, I, I wouldn't want to even guess at what the ratio of success to failures will be this time around versus that time versus any other time when there was incredible boom. And, you know, if you go over the last hundred and fifty years, there have always been these kind of springing further back.

• 9:16Speaker 01

  Yeah.

• 9:17Speaker 00

  Or speculative booms that create tremendous innovation, people coming in, just both money and people. I mean, California, you know, the forty niners, I mean, everybody running off to the hills to gold and it was going to rain. I'm sure there were a lot of companies selling, you know, axes and.

• 9:36Speaker 01

  Yeah, Detroit auto boom, same thing, you know, we've seen this before.

• 9:40Speaker 00

  And how many, so I don't know, but I, this is not new. And there'll be a great deal of disappointment. There'll be a lot of people that'll lose a lot of money, of course. That's just the nature of how we're coming to work. And when there's speculative bubbles, that will bring a lot, but that doesn't mean that there aren't a lot of companies, actually a real value, you know, to make.

• 10:02Speaker 01

  How do you think as a, as a founder running a company or as a CEO, you should make the decision in terms of whether to keep going or whether to sell? It's kind of like, okay, Priceline is worth a couple hundred million dollars and the decision was made, we'll keep going no matter what. And there may or may not have been options in terms of exits. I have no idea. Um, but in today's era, there's quite a few options in terms of exits. Should people mainly be thinking about exiting right now? Do you think? Do you think they should keep going?

• 10:26Speaker 00

  Yeah, I think that's right. I don't think we can give a, a general rule without knowing what the facts that specific situation are. By the way, there were times early in the day where Priceline would have been happy if somebody had made an offer.

• 10:40Speaker 01

  Yeah.

• 10:42Speaker 00

  It really depends a lot on what the situation is, how confident is management and people who have put the money in that which there is going to be a future and how concerned are you? What, what are you really trying to do? Are you trying to accomplish something? The goal is to actually make something that matters? Or are you just here to make money? And nothing wrong with that. I'm not against that. Since you gotta understand what is your motivation? What are you trying to achieve? We have on average, why don't if you're American, fail for hell because I think that's what I put that I was seventy eight year expected lifespan when you're born, of course, the longer you live, the higher it's, whatever it is. And how are you going to spend those years? What is important to you? What do you

• 11:25Speaker 00

  want to, what's the meaning to it? And I'll let the people who are actually in those situations aside, I would not, I would not give them any general advice.

• 11:33Speaker 01

  Makes sense. So, I mean, back to booking, um, you know, one of the categories that you all obviously are really crucial to is, um, travel. And there's a number of the next gen sort of AI companies who've started experimenting with things like OpenAI, uh, had, um, uh, checkout and chat GPT. And, you know, one of the main use cases was travel and then they canceled that feature. And I think at the time booking went up eight percent on the news. What, what do you think didn't work there? Or what, what do you think? How do you think people should think about travel through the lens of AI?

• 12:08Speaker 00

  So I think we should back up a little bit so we understand what's going on here. So in any type of situation, you'll have people who are not that knowledgeable about the industry or about how, um, things actually happen in the business. And so from the outside, it looks rather easy to, oh, this easy, uh, AI will take care of travel and all the travel companies won't be worthwhile, won't be worth anything. And so, and that was why companies like ourselves took a big hit as some of the new models were dropped that had a much better way of doing agentic commerce, as it was perceived at the time. And then when

• 12:51Speaker 00

  the, when people make analysis, oh, we're not going to do that. Like when, uh, OpenAI said, we're not playing to the emotional record, trying to, or we're not even going to keep in this app type of way of doing commerce. We're not doing it. Then people say, oh, well, that, I, I, I was wrong. I'm not going to worry about it as much. It puts the other side. The truth is, the way we look at AI is an incredible beneficial tool and a way for us to be able to do our mission easier, cheaper and better for our customers. All business, what is the purpose of a business? A business is to do something of value to its customers. We have two kinds of customers. We've got travelers and we've got partners.

• 13:35Speaker 00

  We are in the middle of that for a marketplace. How can we do it better? AI, particularly AI using, uh, large language models and other things like that can help make it a much more valuable, uh, method for people, travelers to get information they need to do what they want to do and beneficial to our partners. That's the thing. Now, the idea of chat GPT, you know, you're no longer having one, uh, method. I mean, I wouldn't be too much into that one way or the other.

• 14:08Speaker 01

  Mm hmm. Yeah, that makes sense. You know, it's interesting because I'm in the middle of Silicon Valley where people are very, uh, AGI pilled, right? We, people strongly believe, uh, that AI will drive all sorts of things and in some cases it will, and in some cases it'll take longer and some cases it won't. You know, it reminds me a little bit of crypto where crypto was going to solve everything and it didn't, but it was very important for certain aspects of the financial system. And I think stable points and other things are increasingly valuable there. On the AI side, what a lot of people are really moving towards is more agentic work. And that could be specific companies like Decagon, having agents to do customer support. But it's also the larger platforms like OpenAI, Anthropic, Google, et cetera, providing increasingly, um, self-driven systems, Codex or, uh, Claude

• 14:52Speaker 01

  Co-Work or, you know, some of the things Gemini is doing. And one of the arguments people are making is that the nature of UI is going to change and you're going to have agents doing transactions on your behalf and sourcing things like trips or figuring out your travel itinerary for you or, uh, buying or purchasing, um, the, the actual different aspects of travel. A, do you think that's a, a correct vision of the world? And B, do you think, um, or how do you view that interacting with booking and what you all provide as a service?

• 15:22Speaker 00

  Uh, so again, we want to reduce this to understanding what does the customer want? Many people with travel find it very frustrating. I know that, you know, that we all travel and find very frustrating. Trying to put together a complicated trip with a family, let's say, multiple destinations, different things you want to do. It's complex and it's pain. And you start planning it and then you stop because there's too much pain. And everybody would like something else. Now, many people would like something else to do for them. In fact, that's why you'll find very wealthy people have travel concierge people who are actually human beings who really understand the needs that customer, what they really like, not to have to do a lot of the hard work for them. People aren't

• 16:06Speaker 00

  quite in that wealth zone. They'll have their partner or their spouse trying to do it for them. I'll be perfectly honest. I'm exposing myself here, but I'll say it, okay? My wife and I sometimes argue about, okay, who's going to have to do all the travel for this trip? Because it can be frustrating and sad. Now, with AI, the beauty is it's going to make it so much easier and it's doing it right now. We are doing it right now. And let's use that generic term. Let's call it an agent. So I can't wait until we, Booking Holdings in our companies are offering up these personalized agents that are, that know everything about you, everything you want and able to do so much more for you

• 16:47Speaker 00

  than any human travel agent could ever do. Because the machine never forgets anything. The machine has an infinite amount of permutation and rapidly look through and choose what is the best thing. And it can go down and then back up. That doesn't work. Why? This doesn't fit that well. And can come back with, now, people will always want some agency. So they make the decision themselves or at least confirm they want it. Most people aren't for the most part going to complicated thing. They don't want to double check them, check the thing out or whatever, which is different than say a business person says, I gotta go from New York to Chicago. And, you know, your assistant, your human assistant around doing it for you. That's like an agent doing it for you. It knows what like you need and all that. That's great.

• 17:29Speaker 01

  Yeah.

• 17:29Speaker 00

  But when it's complicated, you want that agency. So we at Booking Holding or our companies, we are doing that right now. In fact, if you go to Penny, uh, uh, which is Priceline, a, uh, agentic AI, uh, system. And I just did it the other night. I put in a very complex, uh, need for a travel with the family where it was, uh, my wife and I, we want to go up in front of the bus. I want the young adults who are adults, but I'm paying. So I want them in the back of the bus. Uh, they're starting. So I got two cabins now. There are, one person has to go back to a different city. We're going to Europe, going to a city. We're not, we're not actually doing the trip from that city where we're going to land. How are we going to get from one to the other? Should we have

• 18:11Speaker 00

  the hotel where we land and then travel the next day to the other city? Or should we go that night? How are we going to do it? What restaurant? All the things. And I did on Priceline Penny and it was incredible. I also added another thing. I told it that, by the way, I got a lot of frequent flyer miles. So should I be using my miles or should I use a cash and for which ones? And it was just beautiful how it went back and forth and asked me questions like, how many miles do you have with each airline? And I'm giving it. And then we're going through the flight part and how much of the cost. And by the way, it ended up, as I expected, I'm using my miles for the upfront part for my wife and I were paying cash for the kids on the flight. We're going to go to the hotel, um,

• 18:52Speaker 00

  in the city that we landed. The next day we're going to get a show. It was wonderful.

• 18:57Speaker 01

  Yeah.

• 18:58Speaker 00

  Wonderful. And that's what we want even more. So here's a real important thing is when things go wrong and things go wrong in travel, and nobody's fault many times, weather, mechanics, it happens, okay? You want to have that one point of contact that can fix everything because travel is like domedos. One thing falls over and it all starts falling over. And that's the beauty with AI, being able to figure out, being able to look ahead. What can we do? My goal is to have a system that actually we are able to predict well enough what the problem be before it happens and suggest changing, fixing. I have so many examples of this, but I see the future coming.

• 19:37Speaker 01

  I guess at a sort of generic level, because, you know, your team on, on a call that we had prior, prior said that, uh, Penny adoption, which again is this, um, agentic tool that you have well for Priceline, has doubled every month for the past, past few months. And it's, uh, generated a lift in conversion plus faster search, shorter path to booking, lower cancellation, you know, higher customer success. So it seems like it's working in really interesting ways. Are there a common set of use cases that, you know, you think are most common for Penny? Are there, um,

• 20:09Speaker 01

  You know, specific things that it doesn't do well, that you just need the underlying models to get better for. I'm a little bit curious.

• 20:14Speaker 00

  Yeah, well, the actual weeds have some areas where we're coming out with some new things on it, but here's something really important. So when you ask me the questions, when you say it's so great, but you tell me it's not really doing much, you know, the numbers don't really show up much in the numbers yet, because it's still really, really small in terms of the absolute number. We've got to talk scale here. You know, last year, we did a hundred and eighty-six billion dollars with the travel. That's a lot of travel. Okay, even if you did over a billion room nights. So, you know, the actual numbers, so there's a lot. Well, part of it is, we're not pushing it really fully now. There's one of the issues that I always want to think about is what's the cost of this? And that's such a reason to understand. What is the cost? And that's what's developing of running it. How many

• 20:57Speaker 00

  tokens are we consuming here? Where? Well, how many times are they coming back and forth? We're doing, tell me how much was the cost of us getting that trip for that person? And what is our ROI going to be? And the next thing is, well, what's the return long-term? Does it mean lifetime value? Do they come back? Are the loyalties up or what? How much? And will it change? These are things that we don't know yet that we're going to have to continue to work on, develop, so we know. And by the way, the whole thing of token economics now, which model should we be using, for which purpose, and when, and stuff. And obviously, you can get tokens like cheaper in certain parts to different models, they're a lot cheaper. And that's something that we have to look at very closely, too. So it

• 21:41Speaker 00

  is fascinating that we can do things that I I'm so thrilled that we do. And for example, things like using customer service right now, customer service where we're using AI, it's, it's great. It happens much faster. You know, instead of having to staff your humans, and at peak time, somebody's got to wait for somebody to pick up. We've all been in that line, that queue, waiting for somebody to pick up. We hate it. But now with AI, the computer can pick it up. It's not a problem. And solve the problem even better and faster. You never will have in the future. We finally talk to a human, the human says, I'm sorry, you'll have to be at hold again. Well, I get somebody else who

• 22:22Speaker 00

  can solve that problem. Which is, and then you want to swaddle somebody. AI will solve that problem. But here's the question again about that is sometimes, though, you want to figure out because people want to talk to humans sometimes. You've got to balance that. Because what you don't want to do is end up, yeah, you can do it all AI, but actually, that's not what the customer wants. And it's always what's best for the customer.

• 22:49Speaker 01

  Yeah, that makes sense. And I think you said on your Q1 call, the customer service costs are already down about 10% for reservation and booking. It's a bit 10%.

• 22:58Speaker 00

  Let's just go, let's go this, just this space. Our costs for customer service per contact are down. That's great. Customer satisfaction is up. That's even better. But we have to make sure that we are able to always recognize some customers wanting, they're being, and some customers are, you know, they're happy as could be to AI.

• 23:23Speaker 01

  Yeah, that makes sense. I mean, I think you also mentioned that you're investing something like $550 million of cost savings into AI and platform on that, on that same early call. Where are you investing it? Or where, where are you putting the brunt of that, both capital and effort?

• 23:39Speaker 00

  Yeah, so we, and the amount we're investing is actually higher. We talked about 700 million approximately this year is being invested, but it's in many, many different areas, not just, you know, developing AI, though AI, it's definitely money going to call it tech enablement, but there are different projects, different areas. I would not put that all into, and say, oh, you're investing in techno or in AI. That's not correct. There are lots of areas of investment we talked about on the call. That's not, what's important is the idea that, but you've got savings, you've got money, you've got cash flow. How much should you be putting in reinvesting in the company? How much should you be looking perhaps

• 24:21Speaker 00

  acquisitions? And how much should be handing back to shareholders? And that's always a balance, trying to figure out what's the white ratio, what is it? Really is the first thing is, do we believe investing in the top grade is going to give a positive ROI that's sufficient to justify doing that? Or after that, are there acquisitions? And if you can't do either of those, then get the money back to the shareholders, because they can then invest it better than you can. And that's what I've always believed in.

• 24:48Speaker 01

  Makes a lot of sense. And I think you, you folks did something like a record for a billion in Q1, in terms of buybacks and other sort of returns to investors.

• 24:57Speaker 00

  You know, I really am very proud of the fact that over the last, let's say, dozen years or so, we've bought back approximately 40% of the outstanding share. That's good. And we offer a dividend. We have a nice dividend. So in the fourth quarter, was we bought back 3.6 billion dollars worth of stock. We gave out approximately, you know, over 300 million in a dividend. And in addition, we also were paying for the taxes for the equity grants that vested, and we had to, you know, pay the taxes, do it by withholding the shares that part of the assets, another 300 million or so. So a lot of money, making sure it's

• 25:39Speaker 00

  going back to the shareholders if we don't think that we can use it properly ourselves. That's, I, I, it's going to be from investment banking background, maybe back then, maybe trading. We're companies that just build up huge amounts of cash, and they're not doing anything with it, and they're not giving it back to the shareholders. I'm like, that doesn't seem like the right thing.

• 26:01Speaker 01

  I think one last thing that you, that you mentioned earlier, one thing that you mentioned earlier that I thought was really important, is just the scale of your business. And I think it's at enormous scale, and that's kind of underappreciated as an asset. And so as an example, and you closed 2025 with what I believe is 8.6 million alternative accommodation listings. So that's people listing homes or rooms or other things for rentals. It could be a variety of different types of, of spots. But that creates a really interesting, I think, durable asset. So, you know, I feel like people overstate sometimes how AI is going to transform certain businesses. It's obviously going to be transforming everything. But there are also things that are very hard to build, and that are very durable in the long run, that if you have an agent, it's going to go and book an alternative accommodation

• 26:46Speaker 01

  with you because you have all them listed, right? You have the marketplace built. Are there other aspects of your business that you view as especially durable going into this era?

• 26:53Speaker 00

  So on that one, it, it, it is a good point. I think you're right. I think it's underappreciated by some people. Probably, I'd say Americans, because in the alternative accommodation area, obviously, a player is someone who invested in very early Airbnb. Congratulations on your part. But a lot of people don't recognize that globally, when you look at our amount of listings, and you look at Airbnb, it's not that different. And even more so is, when you look at our total amount of transactions, our room night for alternative accommodation, you look at, you see that we are approximately three quarters the size of Airbnb, and that's just our alternative accommodation area. There's a whole much bigger hotel business on top of that. And, and, you know, over the last

• 27:38Speaker 00

  five years, we've been growing, for the last five years, we've grown faster than Airbnb in the alternative accommodation area. We do like to like, we've been growing faster the last five years. So it's a great product, great thing. It's going very well. Your question, though, does that give us an advantage, so to speak, against somebody who comes in, all they're doing is creating a nice AI intent type system, and how are you going to get the connectivity to these players or not? And I'll say, there is no such thing as a moat. There is no such thing as somewhere you're going to be protected against innovation. And that's, I try and get across to the team, we've got 25,000 employees, and I try and

• 28:19Speaker 00

  get this across to everybody. Every day, we've got to be fighting. And, yeah, today, we have a competitive advantage on areas, absolutely. But those can go away tomorrow. The only way to win, the only way to win long-term is to continue to develop new services, new ways to do things, come up with this agentic travel assistant that I want, this universal that will make it so much better. That's the only way. And working on the other side, by the way, also very important, with the partners, we're helping them a lot again, a lot of people to understand the complexity involved. It's not just getting the inventory loaded into some database. Anybody can do that. That's nothing. We've got thousands

• 29:01Speaker 00

  of people who are dealing with hotels and other property managers. How can we do your business better? What do you need? Where are you? Need more demand? Where are you hurting? What can we do to make your systems better? It's so much more complex than I believe many other people who look at this industry far, far. And what second things, and this is something, really, people don't understand, this is the regulatory framework around the world. Dealing with travel is a very highly regulated. Now, it's not a bank.

• 29:34Speaker 01

  Okay, got it.

• 29:35Speaker 00

  And it's not near Playa Air Lines, such that, or it's, you know, not drug discovery. But it is very regulated. And it's complex and you've got to meet it. And if you want to be Merkel record in travel, you got to hear it's a whole bunch of rules, et cetera. And by the way, around the world, much more than the U.S., around the world, those regulations are increasing. I won't necessarily say exponentially, but let's say they're increasing. That too is something that if you're big at scale, you can afford to deal with that. And if you think you're just going to come in and do this business and knock away these very big players. I'd say you should really understand what the business is before you decide to commit your capital.

• 30:19Speaker 01

  So I guess, um, if you reflect on life or you reflect on things looking forward, because I mean, you've had an incredible run. Right. And the run is by no means over, you know, you still have so much stuff you're working on and doing.

• 30:31Speaker 00

  In fact, I think we're just at the start. No, see, this is, I tell you, this is the most exciting time ever, ever, because of the ability to build these things.

• 30:41Speaker 01

  Yeah, I, I, I agree. I mean, I think this is a transformative moment.

• 30:44Speaker 00

  Total.

• 30:45Speaker 01

  Uh, in terms of this technology in the world and society and everything else. And, you know, it's so exciting to be in the middle of all this. And obviously you all are playing a really prominent role in one aspect of that or a key aspect. Um, you know, you, you joined, uh, price line to your point when it was in the hundreds of millions. The stock is now, you know, a hundred and thirty billion dollar plus company. It was a hundred and eighty earlier in the year. I'm sure it'll go back there over time, given, you know, all the things we're working on, fingers crossed.

• 31:06Speaker 00

  We do what we're supposed to do.

• 31:08Speaker 01

  How do you think about just like what you hope to accomplish more broadly in life? Or what is the right measure of a person or, you know, of an outcome or of the next few years? Or I'm just sort of curious because I, you know, we, we chatted very briefly earlier and I, I felt like you're somebody who's thought deeply about more than just, you know, how will I drive bookings for us, although obviously you think about that quite a bit. I, I'm just sort of curious, like, you know, uh, what is the right, uh, measure in general that you're measuring yourself against? Or how are you thinking about the next couple of years?

• 31:41Speaker 00

  Yeah, well, look, uh, I am, I'm very blessed. I've been very lucky in my life that I'm in a position that I could pretty much do what I'd like to do. And sometimes they go ask me, why do you continue to do what you're doing? And I said, because I think, I think the part of this is doing something good. And yeah, we're not curing cancer. I know that. But I think that travel is a very important thing for a lot of people. It really adds to their, their lives. You know, we can do it better. Look, our mission is to make it easier for everybody to experience the world. And I believe that does improve everybody and improves the world by getting people to travel more, experience other cultures, other people, et cetera. And we can do it right and make it easier.

• 32:25Speaker 00

  That's great. I want to be part. I want to do that. I do believe that's adding something. And, you know, that's part of the, everybody needs to understand, I believe, why are you doing what you're doing? You only get one life. You get one life now. Sometimes you don't have choices or all that. That's the only job they have. You need to afford to be able to support their family. I got that. I believe that. I know that. Um, but for people, you know, who have a little bit of ability to choose, I'd say choose wisely. Choose wisely because you will not get that time back. And some people have different ideas of what will, they believe their life should be. And that whatever it is, it's long enough for going that path. That's great.

• 33:08Speaker 00

  My biggest fear too much is people who've taken past that in the end, you know, middle aged or later. And they're a little bit wistful about, gee, I wonder if I done that. And I'll be pretty honest, and, uh, well, not too many in my, my law school classmates, you know, this, I hope, but I fear that too many of them, they chose going to law school because that was just kind of like a path. And then they became lawyers just because, you know, that's normally what you do when you come out of law school. A couple of, I didn't, but many people did. And then it paid really well and it was easy and their comfort zone. And then they're, you know, later in life, it's kind of like, gee, what did I do?

• 33:51Speaker 00

  And that's what I think everybody should really think hard about. Being sure you choose wisely.

• 33:57Speaker 01

  You know, one thing they've talked about quite a bit is the AI impact on jobs. And, you know, there's this claim jobs apocalypse and all those other things coming. Um, would love to hear your views on that and how you think about that.

• 34:08Speaker 00

  So it is really interesting. I mean, we take it in terms of the general sense of technology, meaning job replacement. That's something that's happened forever. We, we look at the way the agrarian societies went more towards urbanization, this technology, that's industrial revolution. We can go through anything like that. And so we know that happens. The issue that's really interesting though is the speed of the change. So if you look right now where we are, I've seen it happen over my time just this company. So at the beginning of the company, we were dealing at bookie.com or we acquired booking.com.

• 34:49Speaker 00

  They were doing hotel reservations in over forty languages, which meant all the content, all the scripts, everything was in forty languages. And this customer service, forty languages, all that is wonderful. There were a lot of people involved back because all the translation is now, you know, it's like two thousand and five. All the translations are be talking about human beings. There's no machine translation at all at the time. And all those customer service human beings, we had our people in all these forty different languages. That was a big deal. Now, now we have machine translations. All those jobs are gone. There's nobody doing that. That's all, all those jobs disappeared. So what happened to those people? Where'd they go? What are the jobs are they now taking? What are they doing?

• 35:32Speaker 00

  So that's the example where we see that happen in real time. And now we have the issue now of Apple now the fear of, well, will I get a job coming out of university? Because all the jobs seem to be gone because what was necessary was an analyst at a financial department, a bank or a big corporation. It's not, it's not being taught through basically AI. So the jobs aren't, that's what's going, how's it going to affect? Now we know also the other side that new jobs aren't going to be created. We all know that also by history, looking at the cloud, the speed of job disappearance and new job creation. Those rates are not happening, probably the same rate.

• 36:13Speaker 00

  And the second thing is, what about the people who are not able to make that change? So I think, well, what I think about the tip of the iceberg, I think about is a fifty something year old truck driver. And when the person who was making a very nice living, it felt very good about itself because he or she is driving an eighteen wheeler across the U.S. And they were responsible, helping contribute, it's a good job. And then all of a sudden that's completely automated. You're out of a job.

• 36:45Speaker 00

  What are we going to, how are we going to retrain that person? Was that person, that person could feel really bad? And we've seen in society how these types of large dislocations have caused problems in the past. When you look at that. And I, I, I'm concerned that there's not enough thought being done about how are we going to deal with these changes? If they happen too quickly or not. To the side is hold absolutely, it's always benefited from technology and created and be able to do more things. But we have to, or how are we going to deal with the flip side, the cost that come with it?

• 37:18Speaker 01

  Do you have a, do you have a specific viewpoint or proposal in terms of what we should be doing there?

• 37:22Speaker 00

  Well, I'll tell you one thing that we do here at our company. One thing that we're always doing is trying to upskill people. I am, I'd say every day I'm talking with my head of C, my C H R overhead of, you know, how can we do the best training? How can we get people so they are ready for the future? How do we get them so they are becoming AI literate? It's probably a word that means I don't want to do that, AI, be able to do AI. And that's really important because even if we end up that we can't replace or retrain or put someone else, at least they are better skilled for a job somewhere else. And I feel a real obligation for that. Now, that's, that's our point. I think everybody should be thinking that way too. It's good for our company. It's a positive for our life for somebody to be able to use new tools in a better way, they're more productive.

• 38:07Speaker 00

  That's great. It's good, but it also helps them for their career. Now, sometimes I could see somebody in short term saying, I don't want to spend the money for that. And it's not the right way to think about it. Now, we could have governments coming in with certain types of programs, trying to come up with ways, but retraining by governments over the last fifty years really hasn't worked out so well. So I'm not sure that's the right way to go either. But I do believe this is something that I really would like to have more conversation about how to do it. Because I do, I am concerned if we end up in a situation where people will start rejecting technology because of fear, that will end up being bad for us as a society. And by the way, other parts of the world are not going to have that problem.

• 38:52Speaker 00

  And they will be disadvantaged, I assure you, when I, in China, they're, they are not having that same thing about, oh, AI is bad. And we shouldn't do it. That is not what's happening there. So I really think we got to talk honestly and openly so we have a right conversation and to not end up on the bad side of people coming out and rejecting what actually are going to be good for society.

• 39:15Speaker 01

  That makes sense. Yeah, it's interesting too, because I know that, um, I know at least one group that has rerun consumer surveys on AI. Because there's this claim right now that people are very negative on AI. And it turns out it depends on what the question you ask is. If you ask people, do you love, you know, using chat GPT and Gemini and Claude and all that? They're like, we love it and we'll pay more for it and it's wonderful and it's helping our lives in all these different ways. Or it's helping our kids with school or whatever it is. Then if you ask them, are you worried that AI will come and destroy your life and take your job and ruin your career? And then of course people are like, I don't like it. And so I think that the questions are being asked a certain way on purpose. And I think to your point, we need to be level headed and say, okay, what's the real implication for different areas of the economy? How do we make sure that people benefit overall?

• 39:59Speaker 01

  And how do we make sure that people can participate? And that's very different from, you know, taking a pure doomer view or taking a pure sort of negative view on what's coming. So, you know, appreciate your perspective on that.

• 40:09Speaker 00

  You're so right. And part of the problem is in a democracy, which we have, which I'm in favor of. You'll have people who are saying certain things because they're not seeing what they believe, but they believe we'll give them a book. And that's also problematic in any, or kind of favorite democracy, but I'd be in favor of people, you know, of a more honest of what they're saying.

• 40:29Speaker 01

  Yeah, yeah. What's their all purpose? Yeah, a hundred percent. Thank you so much for joining today. I really appreciate, um, you know, you, uh, you sharing your various views across all these topics. It's been really great chatting with you.

• 40:39Speaker 00

  Well, thank you. Congratulations on all the things that you have accomplished. It's, it's pretty impressive.

• 40:47Speaker 02

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