Why Travelport Believes The Real AI Opportunity Starts With People

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[00:00:46] So if you've been trying to simplify your stack while improving visibility, please check it out at nordlayer.com slash browser. But now it's time for me to introduce you to today's guest. Welcome back to the AI at Work podcast. Today I'm joined by the wonderful Lee Senderoff, Chief Transformation Officer at Travelport.

[00:01:13] Now Travelport is one of those companies that many travelers rely on without ever seeing its name. It sits behind the scenes as part of the infrastructure that is powering travel booking across more than 160 countries. And it is also connecting travel buyers, suppliers, agencies and platforms. And that role is becoming even more important as AI changes how people search, plan and book travel.

[00:01:42] Because we're moving from simple searches like London to New York on fixed days to more natural requests such as find me somewhere warm for my family in the next six months. And throw in activities for the kids and somewhere relaxing for the adults in the evening. But this conversation today is about much, much more than just travel. Because my guest will argue that AI should be understood as a workforce transformation, not just another software tool.

[00:02:11] And the real opportunity here is not confined to innovation labs or technical teams. It's actually about giving people across the business the confidence, the tools and space, all these things that they need to change how work gets done. So we will cover everything today from enterprise wide AI enablement, why small productivity gains can become major financial impacts at scale. And how AI literacy is changing hiring and culture.

[00:02:40] And why human judgment still matters more than ever in an AI enabled workplace. But enough from me. Let me introduce you to Lee right now. So a massive warm welcome to the show. Can you tell everyone listening a little about who you are and what you do? Sure. Thanks for having me, Neil. Really excited to be here to talk everything about AI. So my name is Lee Senderoff and I'm the Chief Transformation Officer at Travelport.

[00:03:09] We are one of the largest travel companies you've probably never heard of. So think about when you go on American Express Travel and you book travel. We are actually the connection layer between that interface and actually getting you a ticket. And so we work in 165 countries and have employees all over the world and have just embarked on a really interesting AI journey. So I'm looking forward to sharing a little bit about it with you. I'd love to hear more about that journey. And it's incredible, isn't it?

[00:03:37] So you're almost the unsung heroes of travel. Many people listening would have used you without even realizing, right? Correct. Correct. That's exactly right. We're the infrastructure layer that powers travel unbeknownst to the end user. And it's becoming more and more important, actually, because the way people are searching today is changing dramatically. I just actually heard a stat the other day that was astonishing.

[00:04:00] So 42% of people are now starting their travel journeys with some sort of LLM, whether it be Anthropic or ChatGPT. And that search is fundamentally changing from, remember, like, I don't want to date myself, but we used to search, right? New York to London, May 15th, coming back on the 20th. Right. And we used to receive, there were first class tickets and there were economy tickets. That's it. Your bags came along with it, right?

[00:04:28] And now folks are going into now LLM and saying, I want to take my family of four on vacation somewhere warm. And what does that even mean, Neil? Because I was speaking to Canadians yesterday and warm for them is definitely not warm for me. Right. And so they're saying, and I want to go in the next six months and I want to make sure there's enough activities for my 10-year-old, my 12-year-old to do and for my wife to relax at a spa. Right. All of a sudden, like, that whole world is just shifting fundamentally, right?

[00:04:57] Consumers want a completely different experience with the way they search. It's really hard for the travel industry to deliver on that. And at the end of the day, there's got to be an infrastructure that powers all of that to actually get the booking to work. Right. So beyond the search, actually getting to a point where you book the right ticket, you book the right hotel room. So we're doing all that behind the scenes. It's incredible. It really is. I would imagine that gets even more important when we're looking at plugging agents into things as well. And I must admit, my own habits have changed completely.

[00:05:27] I go to the US a lot for tech conferences and things like that. And usually when I land at an airport in the middle of nowhere, the old way of doing things, I would Google it and end up with a page of sponsored results that don't really tell me anything. But now, of course, I just say, go to an AI agent and just say, what is the quickest, the cheapest options of getting there? And I'll get all the options straight away. And I'm not wandering around looking completely lost as I leave the airport. But I mean, you've argued that AI is actually a workforce transformation too.

[00:05:56] So what do businesses fundamentally misunderstand about the scale of change that we're talking about here? You know, I think it's interesting. I was at a PE conference yesterday and a lot of folks were talking about AI. And some of the conversations were around, well, we're going to use AI to solve this really big problem. I actually think that that's a really dangerous place to start because AI is going to solve many big problems.

[00:06:21] But inside of organizations, a lot of times the ROI on getting that big problem solved with just AI could take years to come to fruition. And let's be honest, the private equity industry does not have the patience for years. So I actually think, and from what we've seen, empowering people to do their jobs day to day with AI and taking it out of a tech team, just like you do with email, right? Email is a technical tool. But could you imagine if only the engineers were allowed to use it?

[00:06:49] Or if every time you wrote an email, it had to go through some form of governance before you sent it out, it would not empower you at all. And so we think about AI in that realm. How do we actually remove the drudgery, the annoying work from people to create more time and bandwidth for the creative thinking to solve the stuff you and I just talked about, right? How to present those better results to the traveler.

[00:07:13] So I think part of it is taking it out of just the technology team, even though there's, of course, a place for it there, but it's not the only place. And despite everything you said there and what we're talking about, many companies and many people listening in organizations are still in an environment that is treating AI adoption as something driven by the technical teams or innovation labs and those multicolored beanbags and foosball tables, etc.

[00:07:39] So tell me a bit more why you believe that the real opportunity there actually comes from enterprise wide enablement rather than those isolated AI initiatives. Let me give you an example. So we launched this training course for 75 people in our organization. We're an organization of about 2,000 employees, just to put it in perspective. We launched a training for 75 employees of all different levels, senior, senior level, junior, junior level.

[00:08:06] And we're broken out into cohorts and everyone experiments in a different way and shows off their work on this weekly call we have. And I had a middle level manager who came and said, I built an agent that saves me three hours a week. Okay. Wow. Three hours a week. That's great. He's this guy's super excited because now it's like it helped him do something with reporting that now he doesn't have to do manually. So I went back and I really like process this and thought about it. So if the average employee, let's just say costs $80 an hour, right?

[00:08:35] So he saved three hours a week. Let's say he works 45 weeks a year. That's $10,800. Okay. Nothing to write home about, right? That project would never make it onto a tech roadmap. But now multiply by 1,000 employees, like just saved $11 million. And even if that's aggressive, I'll take a $5 million savings any day. Yeah. Because I can put that money back into growth, hiring more people, supporting our customers better. That would never make it to a tech roadmap.

[00:09:06] And so that's how I look at this. If you empower people with the right tools, and we can talk about sort of a framework that we're using to actually bring this to life. But now you're going to have these savings occurring throughout the organization and never having to even go through approval processes, right? So the time to decision, this isn't something that hits a product roadmap wish list, goes to a product team, is actually getting in the way of doing customer-facing work, right? Because it's internal support work.

[00:09:36] So now a lot of the internal support work can actually happen from the teams doing it. They're feeling the pain points, and they can correct those pain points in real time versus having to wait for a technologist. That, I think, is where the magic unlock is. And before you join me on the podcast today, I was doing a little research on you, and I love how you said that the biggest risk isn't under investing in AI tools. It's actually failing to change how people work.

[00:10:01] And we've said for many years that there's nothing more damaging to an organization than, hey, we've always worked this way. Things have got to change. And I know you've shifted your own working culture. You mentioned you've got your own framework there. And just to bring to life, maybe share that, because I'd love to inspire people listening on where they, if they followed in your footsteps, where they could be. Sure. And I want to caveat that, Neil, with one thing. I'm not an AI expert. I don't think many people are. This is so new.

[00:10:28] So I'm learning as I go and with just speaking to smart people, thinking about things in a little bit of a different way, and then adapting really quickly. So when this framework started, actually, it was pretty robust and really heavy. And I said, it's just not going to work. Like, let's just keep refining it, keep refining it. And we brought it down to really like three core parts. So one is building capability. So how do you actually impart the knowledge and the tooling on folks, right?

[00:10:56] So if you think about it, organizations pick today between being a Microsoft shop or being a Google Gmail shop, right? No one uses Gmail and Outlook in the same organization. And so sort of deciding what's that toolkit that your employees are going to have. And whatever is right for your organization and your needs, there are a variety of different tools out there. But figuring out who's – what is that toolkit? Who's the administrator? And treating it just like you would a Microsoft Office or a Google Mail. Then it's actually teaching people how to use that tool, right?

[00:11:25] We take that for granted because email has been around for so long. But when it first came out, that's not – people didn't know how to use it. I mean, I still remember stories of CEOs that would have their assistants print out each one of their emails so they could read it. Then they would dictate back and the assistant would write the emails back. Like, that doesn't happen anymore because everyone's working on their phones. So teaching people how to use it is critical. So that's sort of step one is building the capability. Step two is creating the right environment.

[00:11:50] And this is – this goes to connecting the data correctly in a safe, secure way so that you're not putting your data, your customers' data, information at risk. But also figuring out how are you going to deploy these agents? Because what we're finding is now that we've empowered so many people, we have hundreds of agents. Which ones should someone use? Which ones are the official agents of the company versus something that Neil uses to get his job done? And then supporting those folks.

[00:12:19] So I think one of the things we've learned is when you build an agent that's powerful enough to support a pretty robust workflow, it's really hard – like, it's very difficult for 700 people in your organization to use that tool because it needs more infrastructure in order to be able to work correctly. This is where my tech team comes in. So I have a dedicated small tech team of folks who look at these key projects and say, okay, this one needs a bit more technical support. Or we really want to make sure the prompts are right.

[00:12:48] And so they go in and work with the functional teams to support them launching these agents. So that's sort of part two is creating the right environment for people to be able to thrive. And then part three is sparking the innovation and motivating. And you'd be shocked, like, at how much fun people are having just with things like office hours, just coming and showing what they've built. We're doing – we have, like, a Slack channel where people can just share, like, this is what I did today.

[00:13:16] So it doesn't have to be some – it could be as simple as I used it. I built an agent to save me three hours of work a week, but they're sharing. And it's really peer-led versus top-down-led. So those would be – that's my three-prong framework that we're implementing right now. So I will – the other caveat to that is it will probably keep changing. But right now this is working.

[00:13:39] So a special thank you to Denodo for supporting the Tech Talks network and helping us keep these conversations going. Because moving beyond AI pilots all starts with connecting your models to trusted enterprise data. So if you're ready to move beyond AI pilots, Denodo can help you connect your AI models to trusted enterprise data in real time. So you can scale faster and reduce risk.

[00:14:06] So if you're interested in turning AI into business value, simply visit Denodo.com. We are talking today in a period where AI proficiency is becoming both a baseline expectation but also somewhat of a cultural signal in the workplace. So how do you see hiring practices and talent evaluation – how do you see these things changing over the years in the workplace?

[00:14:31] AI literacy and prompting engineering becoming essential skills? You know, I think it's interesting because it's going to happen on both the recruitment side and on the candidate selection side, right? So on the recruitment side, could you imagine today if someone got sent a resume and said proficient in email? I'm just going to use an email example because it's very obvious to people. You're laughing, Neil, right? Because if I saw – I mean, I laugh when I see proficient in Microsoft Word because if you're not, right? Yeah.

[00:15:00] So you're not – like right now we're still seeing like proficient in AI. That's going to go away, right? Or you're going to go to an interview and the recruiter is going to ask, do you know how to use AI? That's what they're doing today. Yeah. That's going to go away, right? Because it's going to just be a part of how we work and the magic is going to be how did you use it to drive results, right? So it's going to go from, oh, I – you know, if you ask a salesperson today, how did you hit your numbers? And they said, I wrote a bunch of emails.

[00:15:30] You'd say this person doesn't know what they're doing. However, if that person said, I wrote a drip campaign that helped me get front of mind of all of my target audiences and I did this by myself with the marketing, that's smart, right? So the AI conversation is going to progress to that. How did you use an agent to improve your work? How did you use an agent to improve the KPI that you're responsible for in the company?

[00:15:53] And I think that we're just going to start to see it roll into your normal way of doing work and it's not going to be necessarily called out as AI. It's going to be how you put it into practice. And then on the candidate side, it's going to be the same kind of evaluation. Is this a place that embraces change? Is this a place – and this is something I even saw, you know, 10 years ago when I was doing digital transformations for companies. Is this a place that's going to embrace change or run away from it?

[00:16:20] And the top echelon of candidates are going to say – they're going to have their choice and they're going to say, I want to work at a place that empowers me to be a better version of myself. And that includes being able to use tools that make me better at my job. And so I think it's going to be an interesting shift in both directions. Yeah, I completely agree. And it feels like there's an interesting balance emerging as well where not using AI can be seen as a red flag.

[00:16:46] But overusing AI, not questioning what you're given, can also raise concerns too. So how do organisations encourage healthy AI adoption without creating maybe dependency, a lack of critical thinking, or losing that human judgment and creativity? Because again, a bit of a balancing act. Complete balancing act. And I'm definitely not somebody who advocates no humans at work by any stretch of the imagination. I mean, look, I think that it's a journey, right?

[00:17:14] And I think that it's also how do we remove the drudgery of the work and create more space, headspace and time for that creative, interesting, innovative power that humans have? I think so much work has, for better or worse, become rinse-repeat work and work that doesn't necessarily challenge us. And so if we can create space by using AI for some of that, imagine what we could create.

[00:17:43] You know, I think a lot about this because people ask me, well, we don't really know how to implement AI or we're going to hire this, you know, consulting company. They're going to come in and tell us how to use AI. Like, save your money. Just go to a middle manager at your organisation, a director level, and say, if you could hire one person, what would they do? And I bet you 50% of what that person does, we could probably automate with AI. Right?

[00:18:08] So it's not about, again, I don't, it's not necessarily about solving all the big, big company problems with AI. It's about thinking about, okay, there is work that folks should probably stop doing in order to, like I said before, create space for the work they could be doing. And that's how I view AI.

[00:18:29] And back to yourselves, I was reading that Travelport recently announced a new phase of accelerated growth as AI continues to reshape travel distribution. So on that side of things, how are you seeing AI changing the travel industry specifically, both behind the scenes operationally and some of the things that myself and people listening won't get to see? And also in that customer experience itself that we do. Yep.

[00:18:54] So there's so many different ways, but if we go back to the search conversation we had before, that's shifting the infrastructure need significantly. Because the amount, think about the amount of search queries that are going through to an airline today. So if I used to search London to New York, May 15th to the 20th, that was a pretty constrained search, right? Now I'm searching, I want to go somewhere warm in the next four months.

[00:19:23] Think about how many times that LLM needs to ping Delta, United, all these airlines in order to actually be able to get that needle in that haystack, which is the needle is the right flight for me. Yeah. And every time they ping these networks, it costs them money. So how do we create an infrastructure layer that reduces that burden for all involved? And that's what Travelport is working on. Exciting times.

[00:19:53] And I think travel has always been an industry powered by huge amounts of fragmented data, suppliers, pricing models, and indeed customer expectations. So from your work, how is AI helping simplify some of that complexity while also creating those smarter and faster retailing experiences? Yep. So, I mean, I think, look, if you just take a very simple journey, go on a customer journey, right? I want to go to Dubai and I don't know what to do. I have three days in Dubai.

[00:20:22] What should I do? Amazing, right? Go into ChatGPT or Anthropic or any of these models and you'll get an amazing – I mean, I used to use these books, Lonely Planet. I don't know if you remember those. Yes, cool. I mean, just think about that. And it used to be they had to print a new version every year because the restaurants would change or a new one would open or a hotel, you know, would burn down, whatever it is, right? But now it literally – in a few seconds, I can get an itinerary. I can even say I want to go to a spa. I want to do shopping. I want to eat at the best restaurants.

[00:20:50] Give it some parameters and you get the best itinerary you could have ever imagined three days in Dubai. Okay, but now you've got to book the ticket. Well, that gets more complex, right? That gets a lot more complex, especially if you're going across carriers. So let's say you're flying from Paris. You're going to Istanbul first and then from Istanbul you're going to go to Dubai and not on the same carrier. That gets really complex. Our systems can't really support that. That's where travel port and the infrastructure systems come in.

[00:21:17] Now you're in Dubai and there's a war and you want to leave. What happens? The LLM can't actually help you leave Dubai. It can give you options. It can tell you, call the embassy, call your travel agent. Call the airline. But it can't actually get you out of Dubai, right? And this is where the need for travel agencies and travel professionals really comes in.

[00:21:44] Now the AI will make it easier for them to serve you as a customer because they can answer the phone faster or they can get information faster at their fingertips. But you still need that human layer in conjunction with the agentic layer. And so I think what we're going to see, just like we did when Google Search came out, this convergence of human-led and machine-led information that together will make a much more powerful consumer experience.

[00:22:14] And I'd love to pull out a virtual crystal ball here. And if we were to look further ahead into the future, what do you think will separate those organizations that successfully build AI-enabled workforces from those that struggle to adapt both technically, culturally, operationally, and even competitively? Do you think that gap will quickly widen? I think it's widening today. So I think there's the financial aspect of it.

[00:22:39] So as I think about writing a five-year financial plan for an organization, 20 years ago, I would grow my expense, my operating expense line at a simpler rate that I would grow revenue. That's going out the window for AI-empowered organizations because of what we talked about earlier. You can have one person with a few agents do the work of maybe what five people used to do. So growth can come without the added overhead that it used to need years ago.

[00:23:07] And the organizations that get it right, financially speaking, are going to be healthier in the sense that they're going to have more capital created by these efficiencies for marketing, for innovation, for paying higher salaries to the folks that are in tune with this world. So financially speaking, they're going to set themselves apart. And that, I think, is going to happen actually relatively quickly. I think the other thing is just talent recruitment.

[00:23:32] Like we talked about before, the top echelon of talent is going to want to work at an organization that empowers them to be the best they can be. And so they're going to be able to attract better talent. That's another piece of it. And I think the last piece is that we don't know what's next, right? You said crystal ball. No one even imagined AI in what it is today 20 years ago. I mean, AI was being used. Machine learning was being used.

[00:23:59] But how it is packaged today for you and I to use, we didn't know what imagined this 20 years ago. And so we don't know what's coming next. But it's organizations that are actually building this into the ethos of who they are that are going to win because they're going to be equipped to adapt to whatever's next. So it's not going to be about I bought the most AI tools or I'm running the most experiments.

[00:24:22] It's going to be did I build a culture of quick adaptation so that whatever comes at us next, we can take advantage of. So that's what I think is going to set the winners apart from the losers. I think that's a powerful moment to end on. But before I let you go, for anybody listening, I think the key message here is organizations must stop thinking about AI as a technology tool and start thinking it as an enablement layer for the entire workforce.

[00:24:49] And anyone who wants to dig a little bit deeper on that, find out more information about the journey that you've been on Travelport. Keep a lookout for announcements and things you're working on there or connect with you or your team. Where would you like me to point everyone listening? Oh, yeah, they can find me on LinkedIn or at Travelport.com. And yes, I do welcome any questions. Awesome. I'll add links to everything. And as we spoke about multiple times today, many companies are still misframing AI as a tool for technical teams.

[00:25:17] But that real unlock is enterprise wide enablement. And the risk isn't under investing in AI tools. It's failing to change how people work. It's that beautiful mix of technology and people and just a massive thank you for bringing that home today and really putting it in a language everyone can understand. Really appreciate your time. Thank you, Neil. It was so fun to be here with you and to talk about this. Although this was a technical conversation today, one of the things I love was just how practical and human it felt.

[00:25:46] Because AI at work is often discussed through the lens of a large transformation program, a big platform or expensive consulting project. But Lee brought it back to something far more relatable. What if someone in the business could use AI to remove three hours of repetitive work every week? On its own, that may never make a tech roadmap. But across the workforce, it could change the economics of the entire organization.

[00:26:13] And I loved exploring how AI is reshaping travel too. Because as consumers continue to move towards natural language search and intelligent agents, the industry also needs infrastructure that can turn inspiration into actual bookings. And this is where Travelport's platform transformation and API strategy becomes especially important. Especially as travel retail becomes faster, more contextual and more complex.

[00:26:42] And I think that message was clear. The companies that win with AI will be the ones that build a culture of adaptation. The ones that train people, create safe environments, encourage experimentation and still preserve that human judgment. So a big thank you to Lee from Travelport for joining me here on AI at work today. Remember you can find more at Travelport.com. I'll also include the links for LinkedIn too. You can find me at techtalksnetwork.com.

[00:27:11] Remember, if you're attending any tech conferences, go to events. There's many that you can meet me there on too. But that is it for today. So thank you for listening as always. And I will speak to you all again very soon. Bye for now.