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No Priors: Artificial Intelligence | Technology | Startups
Amex Global Business Travel: The World’s First AI Take Private with Long Lake CEO Alexander Taubman
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Foreign,
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B
We're joined by Alex Topman, the co founder and CEO of Long Lake Management. Long Lake recently announced their intent to acquire American Express Global business travel for $6.3 billion and what I believe is the world's first AI take private. They have previously bought around 30 companies and they transform and optimize them with AI. So we're very excited to have him on board today. Alex, thanks so much for joining us at Enterprise.
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A
Pleasure to be here. Thank you for having me.
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B
Lad, you just announced what I believe, and I could be wrong on this, but I think it may be the world's first ever AI take private, where you've agreed to acquire Amex Express Global Business Travel, the world's largest corporate Travel platform, for 6.3 billion, which is pretty amazing. And before that, You've already done 30 acquisitions under this premise that you can buy businesses and transform them with AI. What some people are referring to as AI driven rollups or AI driven buyouts. And so it's very exciting to have you here and learn more about your business. You mentioned you have this Nexus platform which helps your employees serve their customers better and automates a lot of their work. Could you give examples of some of the things that that automates or how it helps them in the context of hoa? And I know you're now in four other verticals or three other verticals, and so what you do kind of crosses across the different businesses you're involved with.
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A
Yeah, that's right. So we've taken an approach since the beginning of investing very heavily in our horizontal AI platform, which we call Nexus. I'd say roughly 80% of the infrastructure is shared across the verticals. And then there's a lot of work to take it and deploy it into those end markets. And the deployment involves mapping workflows, understanding data sources, cleaning up data sources, integrating with them to make them easier for the models to access. And sort of our next platform sits in between the models on one side, and we're model agnostic. And the data sources, the skills, the workflows of the business. And so that takes a lot of customization and significant applied AI engineering capabilities, which we've built at Longlake. So once we can take that platform, we buy a company now or partner with a company now very quickly. You know, in the beginning, it took us over a year with our first acquisitions to actually, you know, find the real potential of AI and see it in the, in the business outcomes. But now, within days of partnering with a company, we can deploy this very quickly and See immediate impact.
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B
So you can buy a company and then within a couple of weeks you have instant margin lift because the employees of that new acquisition just go on a platform you've already built for similar businesses.
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Yeah, what we see is instant time savings. And then the question is how do we grow to give our team members. So we actually invest very heavily in growth. We're actually not really, you know, we're not focused on cost saving. We're actually focused on driving growth and customer experience. That's our big. And what we've seen, it's a much more powerful model because it's our view of AI is it's incredibly positive. Sum. I know this is a little bit of a narrative violation, but we actually think AI makes people more productive and we have more productive people. You want more of them. When your customers are happier, you grow faster, you actually create jobs and everybody wins. And so we're seeing this in our companies. We're fastest growing company in the industry now. We are growing organically. We, when we invested in the businesses, they're typically growing 0 to 5% a year in terms of volume. We're now growing 20 plus percent a year. And that's because we've made our team members, we've given them extra capacity to go and serve more customers and we actually have better, more attractive customer acquisition economics because we can serve those customers at incrementally lower costs with better products and services. So we've been able to take sort of the software style playbook of go to market and apply it into these sleepy industries. And I think it's a win, win, win.
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B
It must be hard for your employees to go and work anywhere else in the industry then because if they're dramatically more productive, they're doing less busy work. Have you found that you've decreased employee churn or about other things?
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A
That's right. We've seen very, very high retention of our team members across all of our acquisitions. And actually this is the vision. This is the vision. Long Lake. We want to basically be the best place to work in every industry that we operate so we can give the best people the best tools with the best customers. And that flywheel becomes self perpetuating. Because if you now leave Long Lake or you leave one of our partner companies to go to a competitor, have to start doing all this mundane work again, that you 25% of your day, 30% of your day, you have to go do that again. And the thought of it's like giving up email or something, you're not going to, it's just so actually we've started to become a real talent magnet in these industries in our companies. And by the way, we can pay people the most because they're the most productive, they're actually making more money and we're delighted about that. So we can pay you the most, give you the best tools and we're growing the fastest. Um, you know, that's part of our vision is it's just, it's, it's really making things better for team members and customers. And by the way, the other important thing is you give your team members superpowers with AI, the customers are much, much happier. So we're seeing customer retention going up, we're seeing response times much faster, errors going down in sort of things like board reporting, budgeting, email, you know, and that's driving up customer retention.
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B
That's so cool. Why do this via acquisition versus just offering software to people? In other words, the traditional Silicon Valley playbook would be, you know, you find the HOA industry, you realize that there's a need in terms of software. You build software for the industry and then you sell it as a vendor and in this case sell it as a sort of AI product or tool. Yeah, why not do that? Or why did you decide to go down the acquisition path?
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A
We, we think that you can drive better win win business outcomes with deeper alignment. And so by actually owning the companies and owning those customer relationships directly, we can drive better, better results. Software companies are wonderful, we partner with many of them. But when you're just selling software and you don't actually then care what happens with the business outcomes, you just don't see the same business outcome.
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B
And your engineers are just viewing your employees as their customers in some sense then, is that correct?
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That's right. Our team views our employees and our team members in the field as the customer. And that feedback loop internally, that's the other point is we have a much tighter feedback loop. So you know, the old skunk works thing of you want the engineers in the factory to be co located so you can have more innovation. That's what we have along lake. So our team members and our engineers are together in the field all the time. I think there's of our engineering team, they're probably in 20 different states right now sitting with team members across our architecture business, across our HOA business, across our HR services or you know, specialty tax business. And so they're sort of, and there's a deep amount of change management that's involved. So this is a lot of you know, sitting with the team members, understanding their pain points. And so there's a real like solutions orientation of how do we take the pain point. We and then we build a tool within Nexus to solve it. And that feedback loop is really important so you get to better outcomes this way.
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B
Now it's pretty amazing because I think one of the biggest issues for actually adoption of AI is change management. Changing processes, changing organizational design. And I guess if you own the actual company then you can make those changes. If you're just selling software, you can't really impact it very much. I think in general in order to do this very well and I've talked to dozens of people trying to do different forms of AI rollups and things like that is you really need three competencies, it seems like, it seems like you need some folks who are great at the private equity style motion of purchasing things. You need somebody who's great at engineering and building out the AI stack and then you need really good change management. How were you able to pull those three disciplines together? Because it's very rare and again I've seen very, very few, very few companies in this area who've done this. Was it a magic initial founding team? Was it just how you've hired? I'm sort of curious how you, because you've also gotten exceptional engineers which most folks aren't able to get in this industry.
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A
Yeah, well thank you for saying that. Yeah. So because we were purpose built from day one to kind of be this cross functional company with technology and DNA change M and A, we're able to attract, you know, the right type of people from network. And So I think 100% of our first 20 people were through network, knew them really well and people from you know, places like Paler Ramp, Robin Hood, you know, some of the top glean, some of the top sort of modern AI and data companies. And so you know Rasmus, our, our co founder and cto, he and I were connected through one of our know, early investors and board members who've, we've all known each other for kind of 15 plus years. We all started our careers together and
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B
it's really rare by the way I think for many business people to have those deep technical networks. Like what I've observed is that often these are separate worlds and technologists are very bad at hiring business people early on, at least in their careers and vice versa. Business people tend to be awful at hiring engineers and so you end up with these mismatches on the early team. So it's pretty amazing you were Able to pull people out of some of these great companies.
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A
Yeah, well, thank you. I mean I think it's a re. What. It's a really exciting project. I think that's, you know, the idea of bringing AI into the real world. There's a lot, I mean what the labs are doing is extraordinary obviously and they're enabling all of this and all the, you know, hundreds of billions of investment that's going in, models are getting. Part of our thesis was the models are going to get better every day. There's going to be a tremendous amount in the trillions of investment. But who's going to take all that and actually make it work in the real economy? There felt like a huge, huge gap. And so a lot of the folks that came together for our founding team actually were founders before in technology. Many of them had their own startups on the engineering team. They were either the co founder, the CEO or CTO of an applied AI company. But what people realized is it's actually for the reasons we talked about earlier, it's actually really hard to sell software into these services. Much better to. It's like if you can't beat them, join them. And so we're building sort of a team of founders and we want Longlake to be a place where, where entrepreneurial applied AI engineers can come and do some of their best work.
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B
And then you also have pulled, I think some people out of great private equity firms. What are some of the places that those folks have come from?
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Yeah, our private equity team comes from, you know, our M and A team comes from top private equity firms like so many. One of our co founders and M and A lead came from gtcr. He actually worked on the most profitable deal in their history the month before he left to come to Long Lake. He might get embarrassed for me saying this, but I think he was named employee of the month at GTCR the month he resigned. But you know, gtcr, one of the top performing large cap bio funds. We have folks from Blackstone, tpg, hig and mostly the reason they come to Longlake is because, you know, even though these firms are extraordinary firms at what they do, they're not AI native. And so I think for those subsegment of those M and A professionals that really believe in our thesis, there's, there's not many places that look like long like today. And so we can provide a unique environment for them to deploy AI into all these companies.
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And I think this led to this really unique opportunity which is taking private 110 year old business, which is American Express Global Business Travel. And again, I mean I haven't seen anything of this magnitude happen in the AI world up until now, which is pretty impressive. I think it's a $6.3 billion potential take private. How did you all come up with the idea to do this? And I know there's only limited things you can say since this is a public company and it's going through this transition but you know, whatever you can share in terms of the thinking behind it.
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A
Well, we've admired this company for, you know, as long as I, you know, I think I've been a customer. Many of us, you know, involved in our, some of our investors, you know, that have traveled a lot in their careers have used this company as a customer.
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B
And by the way, this company I think got started when the only thing you could book on it was like railways and, and boats. Again, it's been around for a while. I think this predates air travel.
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A
That's right, yeah. This is a 111 year old company. It was started in 1915 by American Express as a way for them to get their travelers checks customers out of Europe during World War I. And actually some parts Carlson Wagon Leet, which they acquired late last year was founded I think in 1876.
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B
Wow.
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Wagon Leet stands for sleeping cars in the train. It's French. So I mean these are, these are businesses have navigated a century plus worth of technology transformation and so and we think they're going to be, it's going to be an extraordinary franchise for, for another century to come. But the, the way we came up with the thesis is we'd actually been, you know, we have a prepared mind approach at Long Lake. We, there's, we have a whiteboard of call it 1520 industries that we think are very high value for us to focus on and travel was always one of them. And the reasons are, you know, it's a mission critical service. It's high cost of failure. Most trips are revenue generating and you know, if you miss you know like a podcast with your favorite, you know, podcaster, for example.
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B
Tragic, right?
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So you know, this is a, the customer trust that this franchise has built over 100 years is really extraordinary. And I think and the company actually and publicly reported has done a really great job charting its future with AI transformation. And we just think we can double down on that and drive a lot of customer excellence.
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Is there anything I know again you can't say much because of, you know, it's a transaction in progress for like a public company. But is there anything you tell us about how you're thinking about where you want to take this?
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Yeah, and I've said this, you know, publicly in the press release, is that our vision is to really double down on the company's existing AI transformation strategy. And we see it as, you know, any industry that we operate in, we see our Nexus platform is giving our team members superpowers, deliver better customer service outcomes, faster response times, faster, you know, disruption, resolution. And imagine basically your travel counselor with AI superpowers. That's kind of the future we envision for MXGBOTS customers.
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B
So I know that there's a few different versions of people who will buy companies to operate them or improve them. The traditional private equity playbook tends to be very short term, right. They'll buy a business for a couple years, they'll put, they'll load it up with data. In many cases they may cut costs aggressively or teams aggressively and then flip the business. And I think you've taken an approach which I would view more as in the Berkshire Hathaway mold, which is you want to buy businesses you can own and hold for a very long time and you kind of want to invest in these businesses over time. Where do you want to be in 10 years or 20 years? Or how do you think about, you know, where this, this all goes?
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Well, look, I think it's a really big market opportunity. This is 20 plus trillion Tam, like I said before. And I think we'd like to be the market leader in every segment that we're operating in. And I think there's a lot of segments to potentially, you know, add value to. So part of what inspired us always about, you know, the Danahers of the world is they were able to compound, they developed a differentiated operating model, in their case started manufacturing and then life sciences. But they were always able to drive better growth, better customer satisfaction, better employee retention and ultimately better productivity. And that allowed them to continually consolidate all these industries over a long period of time with a lot of outperformance. And so our vision is to sort of follow in the footsteps of some of those great companies within the, and do it within the services sector and with our sort of AI platform as our advantage. And I do think that there's something about the long term nature of what we're doing. You know, it's really hard. What we're doing is actually really hard. And doing it, you can't do this in a year, you can't do this even in two years, three years. This is a multi year Transformation. These are, these, these are sort of compounding effects where as you, as we talked about earlier, as you sort of give your people better tools, you get better people and then you can pay them more and then they can deliver better customer outcomes and then you can grow faster. That's not a one month, two month cycle, that's a two, three, four, five year transformation cycle. And then what are you going to do? You're going to do all that, you're going to build the best company in the industry and then you're going to sell it. That just doesn't make sense to me. I'd want to own that company forever and compound on that advantage for decades to come and then extrapolate it into ancillary areas and other service lines. And so our vision really is to be a long term owner partner to world class services companies. And by the way, if I was a founder owned business who had built a great business over 50 years, I'd love to know that the next steward of that company is going to be a long term investor and a long term steward of, of, of of the employees and the customers. And so that's part of our vision as well. We, we've designed Long Lake. Part of it is, you know, I grew up in a family of entrepreneurs and we had a family business that my grandfather started, my dad and uncle ran for, for, for 75 year old company that we recently exited actually. And when we designed Long Lake, I designed it with that mindset of sort of build the product you yourself would want to use, which is I would love to be, you know, if I was a seller of an asset partnering with Long Lake. And that's our ambition.
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B
So one of the things that I've noticed is that often it seems like you, you win a lot of the companies that you are bidding on in a competitive process or in some cases you're the only person people want to sell to. Could you explain why that is or how that's shifted over the last two, three years?
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Yeah, thank you. We have had a really good, our message has really resonated with, with business owners and management teams I think because I think it is solving a really important need which is having a long term permanent capital partner is already a wonderful thing. But having that partner with deep applied AI engineering expertise and a platform that you can deploy day one because these
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folks never see anything like that, right. In terms of the industries that they're currently.
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A
Yeah, we have to, you know, AI is very, very under penetrated. It's probably around 1% penetrated in terms of real enterprise AI use cases. And when you think about sort of the, you know, the overall economy, first of all, 99% of businesses in America are small businesses and they don't have access to the resources of big companies. But even big companies, you know, are having a hard time figuring out, you know, how to drive maximum impact from AI. So we are sort of a, we're solving many needs and you know, in terms of the, you know, the philosophy I mentioned before of we've kind of tried to design, you know, the product you want to use as if we were a seller or if we were a management team to be the optimal partner. And that's, that's how we've designed Longlake. And so we have this cross functional team. They become your partners day one. I mean you get to partner with Varun or you get Varun, Tas Pratik and you know, Jason and our extraordinary engineering team will basically live in your office for the next two years helping you fix all your problems. It's a pretty good value prop. And so, and then we also encourage rollover and equity alignment from existing shareholders or management and founders. And so in our first four verticals, service lines that we've gone into, we have significant rollover participation from the original
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founders and leaders of the business. Gets a piece of the new business in some sense so that they benefit in the upside or the change.
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That's, that's right. We were very open to that and we've been encouraging of that because we like to win together. I mean this goes back to super positive sum about AI. We think we can make everyone happy here. Customers, team members, know, and the business founders and management who participate alongside us in the productivity increase. And so that's why I think we've been a differentiated partner. And I, my view is as we prove this out more and more over time and the capital markets start to understand kind of our vision and what we're doing, I, I'd like to think our cost of capital will keep coming down as well, which then further makes us a better partner to these folks because we can actually pay more than anyone else. Because, you know, and this is sort of what Danaher proved and Transdigm and all these great operators over many years is that, you know, if you can establish a currency, you can actually, you know, not have to lose deals overpriced because you can operate the deals better. And then, you know, you, you have a diversified platform that's more valuable and growing faster with, you know, better financial metrics.
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B
I guess the other thing that's related to this is you tend to grow the business as you buy. So you're not really focused as much on how do we cut costs as much as possible. You're often focused on how do we grow top line, how do we grow revenue, how do we make our employees more productive in terms of sales and serving customers. Can you talk a little bit about that and how you approach that?
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Yeah, we're, we are, for us, growth is, and customer experience and growth and expansion is the top priority.
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So. And by the way, this is very true for tech companies, but it's not very true for many other types of companies, I think.
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Well, it's interesting, I'll tell you. So this kind of a non obvious thing that I've observed, which is actually most of these service companies are growth oriented and most of these founders built these companies from their bootstraps over 20, 30, 40 years by knocking on doors and, you know, figuring out how to, you know, convince people to use their service in a certain market. But it's actually now it's really painful to grow because in these industries that are very labor intensive, if you grow 20%, you might need to go hire another 20% people. And then you got, first you got to find them, you got to train them, then you have to manage them. And if you're already making a lot of money and you're kind of, you know, you don't, you know, it's, it's this. And then by the way, so you do all that work to hire those people and then you only keep 20 cents on the dollar of every incremental dollar of revenue that comes in because you know, most of it goes to incremental labor. So that's like a very high marginal tax rate essentially on the growth activity. So what we've done with AI is when you make your existing teams 30, 40% more efficient and they can handle more customers, it changes the whole mindset of the organization. Now you're growing, you look like a software company now where you're now growing with high incremental margins and that allows you to invest more in growth, be more growth oriented. And that actually is one of the most, one of the most interesting and exciting things about sort of this whole AI flowing through the ecosystem is we're seeing our partners and you know, you could call any of our CEOs and some of them have been running their businesses for, for decades. I think they'd tell you they're having the best time of their career now with us because we're actually growing, you know, like a software company. And we're seeing our team members are getting paid more and are happier and our customers are happier. So it's been a lot of fun.
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B
Thanks so much for joining us on no Priors.
- [21:36]
A
My pleasure to be here. It was a lot of fun. Thanks for having me.
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B
Great first interview.
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A
Thank you, thank you, thank you.
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C
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