← No Priors: Artificial Intelligence | Technology | Startups
No Priors: Artificial Intelligence | Technology | Startups
Travel Through the Lens of AI with with Booking.com CEO Glenn Fogel
00:41:04
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- [00:00]
A
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 one to win 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. It if you think you're just going to come in and do this business and knock away these very big players, I think you should really understand what business is before you decide to commit new capital.
- [00:43]
B
Today on no Priors, we're talking with Glenn Fogle, the CEO of Booking Holdings, a 20 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 $100 billion 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.
- [01:17]
A
Well, thank you very much for having me.
- [01:19]
B
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 Morganstown. 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.
- [01:37]
A
Yeah, I can do that. So real short. I came out of war with Green Finance and now I end up at the back office in mis. My first job is putting tapes on a drive in a data center. IBM 3084s and the disks that went and the tape drives and put the tape on the drive. That's where I started. There's an operator actually being an operator of a mainframe. Very different. Nothing that you prepare for that in college for that. And I then become you become a developer. And 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 made all this money and I thought 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 become investment banker. Says, oh, I got a degree in finance, Warren and Harvard let me into law school. So I'LL do that because that's another route. I did that and I end up getting a job on Wall street as a banker. I did that for. Till 95, till 1995. And then the bank was bought by another bank and they fired all the bankers. Almost not everybody fired most of, including me, but not everybody, because they fired everybody to say, well, they fired everybody, but they didn't fire everybody. So you. There was a. There was actually some people were picked to stay, and I was not one of them. That. That's pretty bad. So a real good lesson, though, having been fired and knowing what it's like, that is something 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, but there's no longer a room for you here. 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 happens. 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 30s, I'm alone. I'm saying, oh, whatever. And I said, you know, I always wanted to write a book. So I. 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, Randy, or doing on your own. You're trying to get some agent to pick it up. And I was introduced to a woman as a blind date for a friend. And I think 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. And so we have a date and the book never gets published. I do end up marrying her and have two great kids, this 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, I didn't want to go back to banking. And I said, I 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. He thought, well, we have this trading position here that you could do. I've never traded anything in my life. Is that don't worry, you'll be fine. It's like, okay. So I end up being head trader for a guy named Barton Bay, who's kind of a Wall street legend stuff. I do that for a number of years, but I just don't like it. It's not that exciting. Just not for 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'm thinking, 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. Perfect. So I get an offer from that place. I want to wait, want to wait till I get my bonus for 1999, when it gets paid at the end of February 2000. So I go and I get my bonus check ready to start. And that's when, of course, that's when the NASDAQ peaked, thereby having gone long Internet a week before, peaked and stopped. And they proved though I shouldn't be a trader having just absolute wrong way. And you know, Priceline has its difficulties after that. Our stock went from where we were in public weaker. So we were 30 billion, which back then was real money. That meant something back then. And by the time I joined, I joined after the, you know, a few months after the IPO I joined, we're probably down to about 15 billion. 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.
- [06:37]
B
Wow.
- [06:37]
A
And our stock is now trading at a dollar a share. We're going to get the Ulysses dropping below a dollar a share, but stick with it. We do a reverse split to make sure we don't get delisted. So it goes to $6 a year. I stay and I'll be there 27 on my 27th year.
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B
Wow.
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A
And we went from that, that now reverse split $6. And in last summer we came very close to $6,000. Wow. You know, a little more a quarter of a century up a thousand times and you know, market cap was peaking around 180 billion. Remember, it's a few hundred million.
- [07:14]
B
Yeah, that's amazing.
- [07:15]
A
It's been a good ride so far. But of course you never stop. Every day is a new adventure. Every day is you gotta a big headline in the ft when I had an interview with and I said gotta fight for a customer every day.
- [07:27]
B
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.
- [07:37]
A
You think like this is a explosion of new things. Of all these would come everything. Just like in the late 90s, the optimism of technology is everything is going to be wonderful. But then you get a little bit of the backlash coming, this backlash then too. And now it's, 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 do see a lot of parallels.
- [08:07]
B
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 30 to 50 billion dollars in revenue run rate each.
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A
And
- [08:20]
B
in parallel you see companies that are extremely highly valued, 10 billion and et cetera, that don't necessarily have even revenue yet. And if you look at the Internet era, I think it was something like 450 companies went public in 99. 450 went public in the first few months of 2000. Maybe 500 went public before that. So you had 1500 companies of which what, two dozen are left at most. 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 different will happen? And those are IPOs, by the way. Those are the very strongest or perceived to be strongest companies. Right, Right.
- [08:57]
A
Well, I wouldn't want to even guess at what the ratio of success to failures will be this time around versus that, that time versus any other time when there was incredible boom. And you know, go over the last 150 years, there always been these kind of springing further back. Yeah, speculative booms that create tremendous innovation. People coming in, just both money and people. I mean California, you know, the 49ers, I mean everybody's running off to the hills, to gold and it was done to brain. I'm sure there are a lot of companies selling, you know, axes and hammers.
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B
Detroit, auto boom, same thing.
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A
You know, we've seen this 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 are going to lose a lot of money. Of course that's just the nature of how our economy to work. And when they're speculative bubbles that will bring A lot. But that doesn't mean there aren't a lot of companies. That's a real value in our economy.
- [10:02]
B
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. 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?
- [10:26]
A
Yeah, I think that's right. I don't think we can give a general rule without knowing what the facts of that specific situation are. By the way, there were times early in the day where price I would have been happy somebody had made an offer. It really depends a lot on what the situation is. How confident is management, people who put the money in that which there's going to be a vulture and how concerned are you? 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. You got to understand what is your motivation? What are you trying to achieve? We have on average, I don't know if you're American male for hell, because I think that's when I looked at I was 70 year expected lifespan when you're born, of course the longer you live, the higher the expense, whatever it is. And how are you going to spend those years? What is important to you? What do you want it? What's the meaning to it? And I'll let the people actually involve most situation aside, I would not, I would not give them general advice.
- [11:33]
B
Makes sense. So I mean back to booking, you know, one of the categories that you all obviously are really crucial to is travel. And there's a number of the next gen sort of AI companies who've started experimenting with things like OpenAI had Checkout and ChatGPT and one of the main use cases was travel and then they canceled that feature. And I think at the time booking went up 8% on the news. What do you think didn't work there? How do you think people should think about travel through the lens of AI?
- [12:09]
A
So I think we should back up a little, understand what's going on here. So in any type of situation you'll have people who are not that knowledgeable about industry or about how things actually happen in the business. And so from the outside it looks rather easy to oh, this easy. 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 agent commerce, or so was perceived at the time. And then when the decision, when people make announcements, oh, we're not going to do that, like when OpenAI said we're not planning to be a merchant of record trying to or we're not even going to keep in this app type of way into it commerce, we're not doing that. Then people say oh well, that I was wrong, I'm not going to worry about it as much. 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, hopefully 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 got travelers and we got partners. We are in the middle of that for a marketplace. How can we do it better? AI, particularly AI using large language models and other things like that can help make it a much more valuable 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 ChatGPT no longer having one method, I wouldn't read too much into that one way or the other.
- [14:09]
B
Yeah, that makes sense. It's interesting because I'm in the middle of Silicon Valley where people are very AGI pilled. People strongly believe that AI will drive all sorts of things and in some cases it will and in some cases it'll take longer, in some cases it won't. 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 stablecoins and other things are increasingly viable 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 that do customer support. But it's also the larger platforms like OpenAI, Anthropic, Google, et cetera, providing increasingly self driven systems Codex or Cloud, Cowork or 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 buying or purchasing the actual different aspects of travel. A, do you think that's a correct vision of the world? And B, do you think or how do you view that interacting with booking and what you all provide as a service?
- [15:23]
A
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 will travel very frustrating. Trying to put together a complicated trip with 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 it's just too much of a pain. And everybody would like somebody else. Many people would like somebody else to live for them. In fact, that's why you'll find very wealthy people have travel concierge people who are human beings who really understand the needs that customer, what they really like not and how we do a lot of the hard work for them. People aren't quite in that wealth zone. They'll have their partner or their spouse try and 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 planning for this trip because it can be frustrating in 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 they know everything about you, everything you want and able to do so much more for you than any sweet 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 and can come back with now. People always want some agency so they make the decision themselves or at least confirm they want it. Most people are for the most part a complicated thing. They're going to want to double check, double check the fan or whatever, which is different than say a business person says I got to go from New York to Chicago. And, you know, your assistant, your human assistant's doing it for you. That's like an agent doing it for you. It knows what you need and all that. That's great.
- [17:29]
B
Yeah.
- [17:30]
A
But when it's competent, you want that agency. So we have Booking holding all our companies. We are doing that right now. In fact, if you go to Penny, which is Pricelines agentic AI system, and I just did it the other night, I put in a very complex need for a travel with the family where it was, my wife and I, we want to go up in the front of the bus. I want the young adults who are adults, but I'm paying. So they want them in the back of the bus. They're starting. So I got two cabins now there, one person has to go back to a different city. We're going to Europe, we're 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 or the other? Should we have 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 it on Priceline Penny, and it was incredible. I also added in other things. I told it that, by the way, I got a lot of frequent flyer miles. So should I be 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 cars are, by the way, in and up. As I suspected, I'm using my miles for the upfront part. For my wife and I, we're paying cash for the kids on the flight. We're going to go to the hotel in the city that we land in. The next day, we're going to get a shelf. It was wonderful. Wonderful. And that's what we want even more. So here's a real corn thing is when things go wrong and things go wrong in travel and nobody's fault, many times whether mechanics could happen, okay, you want to have that one point of contact that can fix everything. Because travel is like dominoes. 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. I have so many examples of this,
- [19:36]
B
but I see the future, I guess at a sort of generic level because you know, your team on, on a call that we had private prior said that Penny adoption, which again is this agentic tool that you've built for Priceline, has doubled every month for the past past few months. And it's generated a lift in conversion plus faster search or a path to booking, lower cancellation, 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, 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.
- [20:15]
A
Well, the actual. We have some areas where we're going to be coming out with some new things on it, but here's something really important. So when you ask me the crisis claim, you say it's so great, but you tell me it's not really doing much. You know, the numbers doesn't really show up much in the numbers yet because they're really, really small in terms of the absolute number. I mean, gotta talk scale here. You know, last year we did $186 billion worth of travel. That's a lot of travel. Okay. You know, we did over a billion roombites. So, you know, the actual numbers are why? Well, part of it is we're not pushing it really fully. Now this. One of the issues that I always want to think about is what's the cost of this? And that's not so easy to understand. What is the cost? That's what's developing of running it. How many tokens are we consuming here? Where or how many times are they coming back and forth or doing. Tell me how much was the cost of us getting that trip for that person and what is our ROI going to be then the next thing is, well, what's the return long term that mean lifetime value? Do they come back, the loyalty is 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 you know, obviously you can get tokens a lot cheaper and certain parts, different models can be a lot cheaper. And that's something that we have to look at. Very closely too. So it is fascinating that we can do things that I. I'm so thrilled that we do. Like, 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, in that queue, waiting for someone to pick up, and 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 where finally you talk to human. The human says, I'm sorry, you have to be on hold again. Or I get somebody else who can solve that problem. Which then you want to throttle 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 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 want in the end. It's always what's best for the customer.
- [22:50]
B
Yeah, that makes sense. And I think you said on your Q1 call, the customer service costs are already down about 10%. Well, we are, per reservation.
- [22:58]
A
Let's just go. Let's go. This just in 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 want a human being and some customers are happy as leads to AI.
- [23:24]
B
Yeah, that makes sense. I think you also mentioned that you're investing something like $550 million of cost savings into AI and platform on that same quarterly call. Where are you investing it or where are you putting the brunt of that? Both capital and effort.
- [23:40]
A
Yeah. So 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 developing more AI, though. AI, there's definitely money going into, call it tech enablement, but they're different projects, different areas. I would not put that all into a. Oh, you're investing in technology. That's not correct. There are lots of areas of investing. We talked to them on the call. That's not. What's important is the idea that you've got savings, you've got money, you got cash flow. How much should you be Putting in, reinvesting in the company. How much should you be looking perhaps acquisitions and how much should be handing back to shareholders. And that's always a balance, trying to figure out what's the right ratio, what is it really is. The first thing is do we believe investing in the company 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.
- [24:49]
B
Makes a lot of sense. And I think you folks did something like a record 4 billion in Q1 in terms of buybacks and other sort of returns to investors.
- [24:58]
A
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 shares. 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 worth of stock. We gave out approximately over 300 million in a dividend. And in addition, we also were paying for the taxes for the equity grants that vested. And you had to pay the taxes, do it by withholding shares, that part of the assets, another 300 million or so. A lot of money making insurance going back to the shareholders. If we don't think that we can use it properly ourselves. Me from an investment banking background, maybe back then, or maybe trading, where 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 of mine, that doesn't seem like the right thing.
- [26:02]
B
I think one last thing 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 an enormous scale and that's kind of underappreciated as an asset. And so as an example, and you close 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 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 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?
- [26:54]
A
So on that one, 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 accommodations area, obviously big player is someone who invested in very early air. Congratulations on your part. But a lot of you 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 all total company, you see that we are approximately 3/4 the size of Airbnb and that's just our alternative accommodation with a whole, much bigger hotel business on top of that. And you know, over the last 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 going fast for the last five years. It's a great product, great thing, it's going very well. Your question though, does that give us an advantage? Sort of be against somebody who comes in. All they're doing is creating a nice AI agent type system. 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 what I try and get across to the team. I've got 25,000 employees. I try and get this across the everybody that 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 wind 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 universally 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 that we're helping them a lot. Again, a lot of people understand the complexity involved. It's not just getting the inventory, load it into some database. Anybody can do that. That's nothing. We got thousands of people who are dealing with hotels and other property managers. How can we do your business better? What do you need? Where you need more demand? Where are you hurting? What, what can we do in terms of your systems better? It's so much more complex than I believe many other people who look at this industry from afar. And what secondly, and this I know 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. Okay, got it. And it's not near plane your airlines such that that, oh it's you know, not drug discarded but it is very regulated and it's complex and you've got to meet it. And if you want to be Mercury record in travel, you got to adhere to a whole bunch of rules, etc. And by the way, around the world, much more than the US around the world those regulations are increasing or necessarily so 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 think you should really understand what business is before you decide to commit your capital.
- [30:20]
B
So I guess 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 that you're working on and doing.
- [30:32]
A
In fact, I think we're just at the start, right? This is, I tell you, this is the most exciting time ever, ever because of the ability to build these new things.
- [30:41]
B
Yeah, I agree. I mean, I think this is a transformative moment totally in terms of this technology and 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. You know, you joined Priceline to your point when it was in the hundreds of millions. The stock is now, you know, $130 billion plus company it was $180 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.
- [31:07]
A
If we do what we're supposed to do.
- [31:09]
B
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, forwards. Although obviously you think about that quite a bit. I'm just sort of curious like, you know, what is the right measure in general that you're measuring yourself against or how you're thinking about the next couple years.
- [31:42]
A
Yeah, well, look, I am, I'm very blessed. I've been very lucky in my life that I'm in a position that I can pretty much do what I'd like to do. And, and sometimes people ask me why do you continue to do what you're doing? And I said because I think, I think 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. 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 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. That's great. I want to be part, I want to help do that. I do believe that's adding something and you know, that's part of the thing 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 people don't have choices at all. That's the only job they have to afford to be able to support their family. I got that. I'm believe that. I know that. 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 as long for going that path. That's great. My biggest fear too much is people who taking paths that in the end they're middle aged or later and they're a little bit wistful about you. I wonder if I done X. I'll be probably honest and I hope not to my law school classmates, you know, 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. Lawyer. I didn't, but many people did and then it paid really well and it was easy in their comfort zone and later in life it's kind of like Gee, what did I do? And that's what I think everybody should really hard about making sure you choose wisely.
- [33:58]
B
You know, one thing we've talked about quite a bit is the AI impact on jobs. And you know, there's this claim jobs apocalypse and all these other things coming. Would love to hear your views on that and how you think about that.
- [34:09]
A
So it is really interesting. I mean we take it in terms of the general sense of technology being job replacement. That's something that happened forever. We look at the way the agrarian societies went more towards urbanization. There's technology, advanced industrial revolution. We can go through anything like that. And so we know that happened. 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@booking.com or we acquired booking.com they were doing hotel reservations in over 40 languages which meant all the content, all the scripts, everything was in 40 languages and the same customer service, 40 languages and all that is wonderful. And there were a lot of people involved that because all the translation this is now in the odds. It's like 2005. All the translations are be done by human beings. There's no machine translation at all. And all those customer service human beings. We had enough people in all these 40 different languages. That was a big deal. Now now we have machine translations. All those downs are gone, there's nobody. All those jobs disappear. So what happened to those people? Where they go? What jobs are they now taking? What are they doing? So that's an example where we see that happen in real time. Now we have the issue not only of that but now the fear of well, will I get a job coming out of university? Because although jobs seem to be gone because what was necessarily an analyst at a financial department, bank or incorporation of jobs not being done through basically AI. So those jobs aren't in a sense what's going, how it's going to play 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 problem is the speed of job disappearance and new job creation. Those rates are not happening, probably the same rate. And the second thing is what about the people who are not able to make that change? So I think I always think about the typical person I think about is a 50 something year old truck driver. And when the person who was making a very nice living, it felt very good. About himself because he or she is driving an 18 wheeler across the US and being responsible, helping contribute. Good job. And now sudden that's completely automated. You're out of a job. What are we gonna, how are we gonna retrain that pro with that person? That person could feel really bad. And we've seen in society how these type 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. Societies hold absolutely. It's always benefit from technology and create it, be able to do more things. But we have to. How are we going to deal with the flip side, the cost that come with it?
- [37:19]
B
Do you have a specific viewpoint or proposal in terms of what we should be doing there?
- [37:22]
A
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. And I'd say every day I'm talking with my head of ca, my CA over head of how can we do the best training? How, how can we get people so they are ready for the future? How do we get them so they become AI literate? There's probably a word that means I don't 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 out of life for somebody to be able to use new tools in a better way. They're more productive. 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 50 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 hear more conversation about how to do it because, because I do. I am concerned if we end up in a situation where people start rejecting technology because of fear that will end up being bad for us as society. And by the way, other parts of the world are not going to have that problem and then we'll be disadvantaged. I assure you we're not in China. They're 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 the right conversation and do not end up on the bad side of people coming out and rejecting what actually are going to be good for society.
- [39:16]
B
That makes sense.
- [39:16]
A
Yeah.
- [39:17]
B
It's interesting too because I know that 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 using ChatGPT 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 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 and how do we make sure that people can participate? And that's very different from taking a pure doomer view or taking a pure sort of negative view on what's coming. So I appreciate your perspective on that.
- [40:10]
A
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 seeing what they believe, but they believe we'll give them a vote. And that's also problematic in favor of democracy. But I'll be in favor of people be a little bit more honest what they're saying.
- [40:30]
B
Yeah, yeah. What's the real purpose? Yeah, 100%. Thank you so much for joining today. Really appreciate, you know, you sharing your various views across all these topics. It's been really great chatting with you.
- [40:40]
A
Well, thank you and congratulations on all the things that you've accomplished. It's pretty impressive. Find us on Twitter at nopriers Pod subscribe to our YouTube channel. If you want to see our faces, follow the show on Apple Podcasts, Spotify, or wherever you listen. That way you get a new episode every week and sign up for emails or find transcripts for every episode at nopriors.
- [41:03]
B
Com.