Easi

Companies that foster an environment that supports professional growth are more likely to thrive and successfully adopt digital innovation. Here are the 100 best places to work in Europe—and how they stay that way.

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<p>Easi ranks 52 on Fortune 100 Best Companies to Work For – Europe 2026 list.</p>

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<p>Easi ranks 37 on this year’s Fortune 100 Best Companies to Work For – Europe list.</p>

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Easi Company Profile, Stock Price, News, Rankings | Fortune

Today’s leaders manage more than companies—they oversee increasingly complex personal balance sheets. But most financial advice wasn’t designed for executives navigating concentrated equity, liquidity constraints, family obligations, and a rapidly shifting macro environment. How should leaders think about timing liquidity events, managing risk across public and private markets, and planning for taxes, philanthropy, and generational wealth transfer? This session brings together experienced operators and advisors to share the frameworks, trade-offs, and decisions shaping how top executives gain greater clarity, control, and choice over their wealth. 

Mitra Best, Founder and CEO, Avvra  
Anna Maria Nekoranec, CEO and Co-Founder, Align Private Capital 
Karla D’Alleva Valas, Head of Private Wealth Management, Fidelity 
Moderator: Claire Zillman, Fortune 

Hosted by Fidelity

The New Rules of Executive Wealth: Clarity, Control and Choice

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The great wealth transfer is reshaping markets, institutions, and influence in real time. As younger generations inherit—and increasingly control—trillions in assets, are they bringing different expectations around investing, philanthropy, purpose, and power? We’ll explore how the next generation of wealth holders could redirect capital and what this means for business, consumers and the broader economy. 

Carmen James Randolph, Founding President and CEO, Women's Foundation of the South 
Beth Meagher, Vice Chair and US Federal Health Sector Leader, Deloitte Consulting LLP 
Diane Brady, Executive Editorial Director, Fortune 

The Next Era of Wealth: Rethinking Influence and Impact

Venture capital has moved from a broad-based bet on innovation to an increasingly narrow one, with a handful of frontier AI companies now absorbing most global investment. Opportunities are emerging well beyond Silicon Valley, even as female and minority founders continue to be significantly underfunded despite evidence of stronger returns. This conversation takes a global view of where capital is flowing next, from who gets funded early to which regions and sectors are poised to define the next wave of growth

Terri Burns, Founder, Type Capital 
Meena Flynn, Chair, Global Private Wealth Management; Co-Head, One Goldman Sachs, Goldman Sachs 
Laela Sturdy, Managing Partner, CapitalG 
Kristin Stoller, Editorial Director, Fortune 

The State of Venture

fortune_most_powerful_women_summit

fortunemostpowerfulwomensummit

Hello everyone, how's it going? So thank you 3 for being here with me. I wanna start, uh, with, with one question about a question, um, which is what is the top question you are being asked the most right now, Nina from your clients, Terry and Leila from the CEOs and founders that you back, and let's start with you, Nina. Are we in a bubble right now? Are we in an investing bubble, whether that's the markets more broadly or whether that's AI specifically? Yep, makes sense, Terry. Um, I often get, uh, do you invest in traditional seed rounds or the 2026 version of a seed round? And what is the 2026 version of a seed round? Much, much larger, you know, we're seeing $100 million dollar seeds and preseeds, and so founders are wondering as they are trying to assess investors which type of seed do you do? Mm, OK. And Leila, I'd say the most common question I get from CEOs is how can we move faster. I think the thing that's changed the most in the growth tech landscape over the past year or two is the speed at which companies are moving. So the top decile companies, we have many that have scaled to 100 million in ARR in under a year, whereas in the fast generation that would take 5 or 6 years for the very best companies. So everyone is focused on speed and how they can build the technology faster, how they can hire faster. how they can get to market faster. Yeah, excellent, and I'm gonna stick with Mina's bubble question because I'm sure you all get asked it every day, as Mina said, but I do have to ask because so many people right now are warning that this first wave of overfunded AI companies is gonna disappoint. They're scared about this bubble. Leila, you sit in the seat. You're writing some of the biggest checks in AI. What is your take on this supposed AI bubble we're in? Is it real? Is it not? Well, I think I'll start with the numbers because I think the numbers are astonishing. The, the last data point I saw was that expectations for Capex spilled out in 2028 top $1.5 trillion. And so when you look at that as a percentage of GDP, it's, it's, I think it's around 2.8%, which is Higher 2 times what it was during the telecom build out and higher than the average during the railroads, so good reason to be asking questions. I think when you talk to the builders of the technology and again the companies themselves that are fueled by AI, the business results are quite compelling. So this revenue growth that we're seeing, um, early signs of, of ROI both. Enterprise use cases as well as you know, further afield things like robotics, life sciences, the, the efficacy of the products and the excitement around adoption is unlike anything we've seen. So we, we see really great, um, you know, reasons to invest in the companies that we've backed are making real business traction, but the scope of the investment is very considerable. And I wanna come back to some of those investments in a bit, but Mino, for the client side, when clients come to you being very scared about an AI crash, what are you saying to, to talk to them about this? Yeah, so I would say the first thing is when you look at the public markets. There is, uh, a lot of support from evaluation perspective when you actually look at the underlying earnings, especially in large cap. And so when you look at, you know, the top 10 names in the S&P, um, the, the revenue and earnings generation is, is spectacular to Leyla's point, like to the extent I mean Capex is significant and it's, it's. Almost more than 100% of cash flow, but to the extent that they needed to, they could turn that off. And so I actually don't think in large cap public markets that we're in a bubble. I think it's actually, um, you know, these valuations are attractive relative to the amount of revenues and earnings. Um, I think the one, you know, the, the thing that's important. As we work through this market cycle, this economic cycle, whether it's in public markets or in private markets, is really to think about not trying to time any one market environment or vintage or cycle. And so to put a finer point on that, actually for our clients for their private portfolios, we actually take 5 years to invest their money to get to a strategic asset allocation. And that's across a venture growth buyout private credit, etc. um, but when you really think about being really disciplined from that perspective, it gives you more confidence that you're gonna be able to withstand any one economic or vintage cycle volatility. Excellent. And Leila, one more for you before I come to you, Terry, which is I, I wanna talk about one of those investments that you've been making. Um, one of your big bets is. In isomorphic labs, which for those that don't know it's a Google DeepMind spin-off that uses AI to design new drugs, just raised $2.1 billion but the drugs are not yet, um, in, in human trials. So I'm wondering if you talk to us a bit about, you know, when will someone in this room take a medicine that AI designed and what makes you willing to bet on something before there's an actual product involved. Yeah, I'm glad you asked that question because I think, um, one of, uh, many of the most exciting applications of AI in my opinion are in these industries outside of just, um, enterprise workflows and certainly outside of asking a chatbot questions and health life sciences health are probably the application most of us as humans are, are, are most excited about. So there are many steps on the path to getting a drug, as many of you in the room know that work in biotech and pharma, um, and it's quite easy to actually see the efficacy of models that are purposely built for drug discovery, which is what the, you know, the isomorphic team has been working on for many, many years. The founding team got a Nobel Prize for the. Um, the science they did around, uh, protein folding model. So this is many, many years in the making, and, um, I don't know the exact timeline of when there are the, the reality of AI is there is discovery and there is the, um, the technology milestones that we meet with the with the technology itself and then there are many human milestones like clinical trials and regulatory, um, work that needs to be done, but I believe that we'll continue to see promising. Releases in terms of of um the progress that the models are making in areas like life sciences also other areas in the real world like robotics autonomy you know Waymo is another big investment of ours. I think we'll see the impact of this technology in cities in urban design in health and um that's where some of the most exciting applications lie. I, I would just agree with. About 100% in terms of our perspective is what's gonna help the the intersection of healthcare and AI especially with life sciences in terms of new drug discovery as well as um more use cases for existing drugs um really you know sets up for uh a healthier you know economic environment as well as a global population. But also, um, it's the one area actually health care in general where we see that there's gonna be more labor force needed versus other sectors and so a lot of people also are worried about what's gonna happen from a jobs perspective and just given the amount of innovation and the amount of opportunity it's also an area just from a jobs perspective as well as from an investment perspective where we think AI could have a significant. Benefit and we could do a whole other panel on that and then I want to later but Terry, I first do wanna come to you because this is a stat that I think has been thrown out today already, but studies are showing that female founded startups generate more revenue per dollar raised, yet teams made up of only women get, you know, around 1% of US venture dollars last year. So why is no one taking the easy money and talk to us about what, what the problem is and what you're kind of doing to fix it. Yeah, I think that you know when you look at at the broader market we are seeing a lot of concentrated dollars and that means a lot of dollars are going into very few companies, a lot of dollars are going into very few sectors, and we're seeing this across a number of different asset classes, but of course we think a lot about venture and we're seeing this in venture in particular, um, when you look at. The way that companies are ultimately underwritten, particularly in private markets, uh, there's always this bias towards repeat founders, folks who have done this before, folks who have preexisting networks, and frankly I think that that's a fairly logical way of, of underwriting. There's actually been a, a, a number of statistics that have shown outcomes from repeat founders versus, uh, versus first time founders. But we all know what history looks like, right? And so if we continue to double down on the way things have been done, even though there are some opportunities for some great economic outcomes, we obviously will see these downstream impacts for female founders and other demographics. That makes sense. Um, I, I wanna talk to you about. To Mina, because I, I think you know women are projected to control $34 trillion in US assets by 202,030. Does that close the gap, or do women investors end up backing the same founders that men do? And, and what are you seeing? I would say that there's, um, there's a lot of talk about women, our female clients wanting to back female investors, call it 5, 10 years ago. I don't think there was a number of managers out there as there are now and I think that there wasn't the conviction level, but I would say there's really in the last 1-2 years been a little bit of a uh a change that we've started to witness and I think it's gonna continue to propel going forward as it relates to investing in I would say areas that are specific to um females and so like for example health care. Female health care, um, women's health care is an area where there is a lot of women that are passionate about that and are looking for ways and are investing with, um, with, with female DC managers because they tend to understand it. Right, that makes sense. Now Leila, one question for you and then I'm gonna turn to the room. So if you have a question over here, just raise your hand and someone will bring a microphone over to you. Um, but companies are taking longer than ever to go public right now. It's, for example, Leila, you led Stripe Series D back in 2016. Uh, 10 years later it's still not public, but now it's worth $159 billion. What does this mean for the venture ecosystem? Why are we in this place? Yeah, um, it's one of the, uh, you know, most profound changes I think in the capital markets between public and private investments just how long these, uh, particularly blue chip private companies have stayed private, um, and look, I think, um, the reality is every single CEO Stripe is a great example, um, will face the choice of whether building his or her company in the private markets or the public's markets is more beneficial to executing the strategy. And I think Stripe is a good example of um a company that has repeatedly said hey we are getting access to everything we need huge capital in the in the in the private markets to the tune of billions of dollars that no one expected they would be able to erase maybe you look maybe 10-12 years ago that amount of capital just wasn't available for private um private companies um and the benefits of being able to do that arguably for a lot of CEOs is that they can be much more innovative in the private. Markets they can take longer term bets they're not answering to quarterly, uh, earnings calls on shareholders asking about their capital allocation. They've been able to make massive acquisitions. So Stripe just bought another one of our companies, Open Router, uh, a couple weeks ago, um, so you see the things that traditionally were associated with being the benefits of being a public company like, uh, deep capital markets for, um, to build. Your investor base and to do acquisitions are now available in the private markets so you're seeing a lot of founders making that choice. Um, we will see if that continues. I think there are also a lot of benefits of going public. We have a lot of amazing, you know, public companies in our capital G portfolio. There's a lot of advantages, particularly if you sell into the enterprise, but there's also some real limitations in terms of ability to execute your strategy, especially. and rapidly changing markets and platform shifts like we're in right now so it's a trend that has been building steadily over the last couple of years and um if the capital keeps showing up in the private markets I don't really see it going away. I, I will add though and I, I don't know if this is um the case in your example Leila, but I do think that this is an increasing challenge and maybe divergence of um. Uh, incentives for both founders and for investors, you know, throughout venture capital history, the vast majority of dollars that were returned to LPs were through IPOs and so having public exits was something that was really, really helpful for private industry. Now what we're seeing, I, I can't remember the stat off the top of my head, but in the last two years, the number of secondaries and the, the total amount that is. Traded in secondary to something like way beyond what it's been throughout all of secondary history and that's really challenging for founders and for CEOs, right, because now you have markets that are trading on a company that you have no say or control over and so I think it's really interesting to see how this is going to play out over time because there are are both benefits and downsides for both investors and CEOs and I, I think the other thing just to add to the alternative investment landscape whether it's. You know what, how long it takes to go public is, is one point, but what you're seeing is that we, we actually recommend our clients have 30% of their assets roughly into alternative investments. And the reason why is what Leyla was saying about is that there's so much value creation. There's so much access to capital. The average company is staying uh private 11 years now. That's like almost double what it was, you know, a. A decade ago and so you want to be able to take place in that value creation. There's also so many more private companies outstanding than there are public companies, so your investable universe is more substantial. And then the other, the other point is that there is on the emotional side of investing when you see a portfolio that goes like this every day and when you have an alternatives portfolio that doesn't mark to market on a daily basis. It puts that emotional side to the side and encourages clients to stay invested and so it's one of the things where you know to the extent that you have access to alternatives you size it right in your portfolio I think there's a tremendous amount of value creation that can happen there absolutely and and maybe one thing I would just add to bridge that because I completely agree and I think um we talk about some of the biggest and the best private companies that have generated uh uh substantial. amount of the returns over the past decade. There's also the hundreds maybe even thousands of companies that have raised a lot of capital and the public markets aren't really open to them. They're either too small, they're not growing fast enough, their financial profile is not attractive enough, and in the landscape that we're in right now, both public and private investors are very focused on scaled assets. They're they're trying to understand a lot of complexity. You have, you know, pub public analysts that used to cover software names that are deep covering semis and hard tech and so to get the attention of investors you really need to be growing at much higher rates than you, uh, used to. So some people say you have to be growing at 30% plus for example to be a software company going public and so the window is open for a few but not necessarily open for many. Which is another dynamic that we see um as to you know why there are so many private companies that have to access the secondary markets and other things now because we're sadly winding down to our last few minutes, Terry, I'm gonna come back to you because one of the things I find most fascinating about, especially because you talk to a lot of Gen Z founders, a lot of, a lot of first time founders, um, a lot are bragging, you know, with AI, I don't need the amount of people in my company. I can build a company with one person. I don't need 30 people. Um, if that's true, do the best young founders even need to, to raise capital anymore? And what's your pitch to the ones who are deciding not to raise and saying, you know, AI can do it all for me? It's a really good question. Um, we, we hear this a lot, and it's our job as investors to try and determine what, what is marketing versus what is really true. Um, to Leila's point, not only are so many scale-ups doing. So at a much faster rate than ever in history they are doing it with much smaller teams than before in history and so I do think that there is truth to this claim. Um, the challenge though is if you are building a fundamental app layer or dev tool AI company, uh, you need compute and so that is a huge cost for a lot of these early stage companies. So even though that they're, they're smaller teams. They still need just as much if not more capital. Um, what happens over time as we see costs go down I think will be really interesting, um, to, to sort of see what it looks like for really small teams to build big businesses and in particular the cost basis that's gonna be needed for that over time. That makes sense. Well, thank you three so much. Thank you all for listening, uh, I appreciate it.

What does AI look like through the eyes of a CFO? At Booking Holdings, the answer is increasingly visible in the numbers. CFO Ewout Steenbergen will share how he evaluates the economics of AI investment, decides which bets deserve more capital, and how he's using AI to create value, not just manage costs, as the technology reshapes the economics of travel itself.  


Ewout Steenbergen, Executive Vice President and Chief Financial Officer, Booking Holdings 
Sheryl Estrada, Senior Writer, Fortune 

Funding the Revolution

eyeonai

fortuneaiweekly

Well, good afternoon, everyone. So great to see you all and good afternoon to you too. Thank you, Cheryl. Good afternoon. So great for you to have you join us. Uh, so the first question I'd like to ask you, how do you think AI will fundamentally change the way that people travel? Yeah, that's a very big question. I can almost talk the whole 15 minutes about that, but I, I will keep it very short because I know you have a lot of other questions you want to work through. Um, so first of all, maybe quickly introduce the 30 seconds explanation. Booking Holdings, we are the largest technology travel platform in the world. We have, uh, many brands like Booking.com, Argoda, which is the largest travel platform in Asia, Priceline, OpenTable for restaurant reservations, Skyak, and many others. So that's a little bit quickly about the company. I think fundamentally, The way how travel will happen in the future is not going to change with AI, but what is going to change is the experience for travelers. What we see is a lot of people now these days use AI to do research. What they did maybe in the past with traditional Google search and many other platforms, on average, everyone does about goes to 5 different platforms and sites to do research before they actually book. But what AI can do is make that experience much better because it's much easier to get inspired, build your itinerary, do the planning, and then from that go to the booking and then also really all the experience in travel and pre-travel. What is going to be really a fundamental difference is that it can become so much easier, so much more convenient, because we all have experienced in our personal lives that travel sometimes can be painful. Something goes wrong. The airline is delayed and now your restaurant reservation doesn't work anymore or your rental car or things happen with travel and we believe with AI it's going to be so much better to create that really peace of mind because everything can be updated, everything is linked together. This is what we call the connected trip vision because now it all is really seamlessly hanging together. I think that's probably in terms of Consumer experience, a traveler experience is going to be, be different, but of course, the hotel is still the hotel and the airline is still the airline, and the rental car is still the rental car. Well, speaking of consumer experience, if consumers increasingly use AI agents to discover, compare, and purchase, you know, hotels, airlines, air, uh, flights, etc. uh, how does that change the economics of customer acquisition? Uh, that's a really important point that we think about, uh, a lot. Um, so about 1/3 of the, uh, Consumers that come to us is what we call come through pay channels. So the search engine marketing, we spend about 8 to $9 billion.08 to $9 billion a year on that, and that could be social media or the different auction platforms that Google's having or the metasearch companies or many others, so. What we really like with this is what we know for sure there are going to be more AI tools agents out there that people are going to use. There will be OpenAI. There will be cloud. There will be Google. We now have Muse and there's Instinct now recently. So for us we will have a much more diversified number of channels that we can work with to get customers to us. By the way, the other 2/3 of the traffic comes direct to us, so we are of course also including a lot of those AI tools in our own. Platforms to make sure that people still come direct to us so for that 2/3 of the traffic, but for that 1/3 of the traffic, we think more diversification of the channels from a unit economic perspective will be in the end a positive for us. How important is consumer feedback to kind of the techniques that you use at booking? It's very important. So I see ourselves as a very scientifically driven company. We test and learn everything. We do every day what we call A B testing, and so we show half of the consumers one way, the other half of the consumers the other way. We look at what works, what works better. If you think about that 8 to 9 billion. That I just mentioned before, we run very large optimization models in terms of where to spend that in the best way to get the highest return. So that is, that is very important and where we see with AI tools what is really encouraging and it's very early stage, so it's not a lot of data. But our traveler customers that come to our platforms and using our AI tools, we see that the time to book is a little shorter. The conversion levels are a little bit higher and the cancellation rates are a little bit lower, so early stage, but those economics of those steps in the end are are are really, I think, encouraging signs. Sounds like a lot of useful data that you're acquiring in this process that helps you inform your decisions exactly so. Uh, there's an enormous pressure to invest in AI. Uh, but not every opportunity will create kind of the durable value. How do you decide which investments require significant capital and maybe which should just remain experiments? Yeah, I, I would like to go back to the first speaker we had here today, Diana from Service now, because she said it really in the right way. I think we are coming out of a period of maybe 2 years that every organization we saw a lot of experimentation, proof of concepts. Small areas where people are testing and learning AI and that's great because we want people in the organization, our colleagues, to get familiar with these tools. But the next phase is going to be really different because now when we really want to harvest the benefits of AI from a productivity perspective we need to start to rethink and redesign processes end to end really from a white sheet and completely rethink how we do it and take the benefit of AI. Let me give two examples of that. So we have, for example, done that in our customer service area and for the last period what we have seen is we see our units of bookings going up by a lot, so at a high single digit level, and our actual costs. For customer service is slightly down, so the average cost per booking has come down by a lot, and the customer satisfaction is actually up at the same time. So it's the best. So and from an economics perspective, very positive, but also much better experience for the customer at the same time. So I think that's real power of AI that we that we're seeing in our business. Another example is in our engineering community. So what we are seeing is our engineers, and we have about 9000 technology engineers. They are using those AI tools a lot. They are putting much more code out, and we have seen about 30% more code that is put in production, so merge requests that are being put in production. It's not what is written, but also what is ultimately tested and the quality control. So ultimately what is really put in production. 30% more that is being put in production. So again, that's a huge benefit that we're seeing and obviously as a CFO I'm very happy with the returns on that. Speaking of returns, uh, how are you measuring the financial returns on investment? I know ROI is a is a big topic. Yeah, and I think in this area, there isn't a perfect answer. I have to say that in advance. I even think that the hyper scalers that spend hundreds of billions on the development of their uh large language models. They don't really know what is going to be the ROI. They have maybe some assumptions and some hypotheses, but the whole point is you don't want to fall behind. I think the good news is for all the rest of the companies in the world, if you're not a hyperscaling, you have to develop those models, but you're a user of the models, it's much cheaper to use those models. But you have to pay attention to the token cost and the licensing costs because you don't want to make sure you want to ensure that those run out of control. So we do something that we call cost. Um, model cost, uh, routing, effective model cost routing in order to make sure that the organization is using, uh, basic models, open source models for simple tasks. And then more advanced models, more expensive models for very complex tasks, and we have different metrics that we are using within our engineering world to really keep an eye on that. So I think that is really important. The returns will be there for those processes that are being. Redesigned end to end, but you also have to make sure that those costs on the other hand, are not going out of control. So you're able to watch that token spend and kind of exactly and we have so incentives in our system to achieve that. For example, I was just speaking about that 30% more productivity. Another metric that we have given to our engineering groups is the cost, the total IT cost per merge request. So that's both the human cost and the AI token cost. So maybe the AI token cost is going up, but if you also have 30% more productivity, you of course want to look at that ratio in the end because even if the token cost is a little bit more expensive, if it's still overall cheaper. To put the same amount of of merge request out. So we are trying to build that into our uh our metrics so that that really that trade-off decision as an incentive is embedded in that for our engineering organization. I'm gonna come to the audience for a question in just a moment, but I have an additional question for you. As a CFO, do you find that you are At the center of being tapped to create value of AI or or coming up um with a systematic way in which to do that. I think the role of the CFO in this world is going to be only more reinforced. CFOs that have to think strategically, CFOs that have to be very disciplined, CFOs that have to really track the performance, CFOs that need to be agile because this is moving so fast, so you have to change all the time. CFOs that have to be disciplined with respect to capital allocation, all of that was already there in the past, but is even more important is even moving faster in an in an AI world plus of course what you do for yourself within the finance organization and even for yourself as as a leader. So uh just to give you two examples of that, so uh I have the pleasure of having an AI AI coach. Because I think everyone has to learn this. No one knows this. And so I have a coach, and I'm talking about it internally to the organization to make everyone feel comfortable. Like if I have to learn and I have a coach, it's very normal that everyone has to learn. So that is one example. The other example is I have actually two agents working for me. One I call the strategic thought partner, so it's helping me with big strategic reports or if I have to give presentations to the board or prepping Q&A. Or if I get big strategic plans to assess those, so that is one, and the other is the critical equity research agent. So this is basically playing the role of helping me preparing for earnings goals and doing the sparing with with me on on that and I learned a lot from from those two agents. That's excellent. Is there any questions in the audience? Um, we have a question, uh, up front here. Hi, Rick Chevia Via. How do you see using AI to be able to develop unique bundles, vacation packages, all that kind of thing, you know, it changes so rapidly. What's, what might be the role in that to be able to improve your margins, improve your, uh, penetration? Um Thank you for that question, because for me that's actually the most interesting question, not so much about productivity and cost, but how does AI change your growth profile as a company? How does it change your business model? How does it change the customer experience in the end? And we think for travel this will be a completely different experience because Travel today, as I said before, can be really complex. Things go wrong and if we can connect the dots between all those different elements, it can be proactive. It can be personalized. It can be much more higher frequency because people today come to our platform and it's more transactional and we can become a much more high frequency business. So to give a few examples to make that concrete. Uh, someone has a trip to Paris organized and we see that the weather on Wednesday is going to be bad and we can proactively say, hey, shall we change your schedule around on Wednesday it's bad, so why don't you do the Louvre tour then and your outside walking tour on Thursday so we can say that or your uh your flight is delayed, we can say. Hey, press here. We already have pushed out your restaurant reservation, or we can even proactively make suggestions of, hey, we know you like to do active sports, and this day it seems like you have no activity planned. Do you want us to organize some kite surfing activity or something else? So it can be much more a very Um, very much proactive personalized experience that was very hard to organize in the past, but with AI that will be possible and we think that will be ultimately great for our supplier partners, for our traveler partners, but also, uh, of course great for us as a as a company because it will create more loyalty, more trust, and, and more brand value for us. Well, that was a great discussion. We're, we're out of time, but, uh, thank you so much for joining us and sharing your perspective.

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