AI transformation in travel: Ante Dagelić of Travelier

Rapid evolution of artificial intelligence (AI) is already changing the travel industry and how companies operate both externally and internally.

Over the coming weeks, PhocusWire is checking in with executives about where AI is making the biggest difference in their businesses.

At ground and sea transportation platform Travelier, the technology is top of mind, according to VP of AI Ante Dagelić. Speaking with PhocusWire, Dagelić shared his thoughts on the future of AI, its impact on Travelier's recruitment processes and more.

Editor’s note: This interview has been edited for style, clarity and length.

What's the biggest impact AI has had on your organization so far? Please provide a concrete example of AI in action.

At Travelier, we look at AI as a shift in company culture and process: an AI-first mindset applied on every layer of the organization. Because of that, initiatives come both top-down and bottom-up. We run hackathons and AI O'Clock meetups, have 'AI Champions' and 'AI Builders' inside the business units and make AI fluency part of performance reviews.

I can point to two recent examples.

The first is Jarvis, our internal AI data brain, which has had a significant impact on our ability to understand and improve the business. Any employee can ask any product, marketing or business growth question and get a detailed analysis back, in the full context of Travelier and how we actually operate.

The second is a set of automations related to supply. We operate in fragmented, fast-moving markets across Southeast Asia and Latin America, where much of our supply is small local operators and a large share of the relationship runs over instant messaging that is unstructured, ad-hoc, and touches multiple departments internally: business development, operations, customer support. We've built several agents resolving approximately 95% of previously manual tasks resulting in saving tens of thousands of working hours a year.

These automations get developed and improved every day and allow people to focus more on creativity, critical thinking and business impact.

Trivago recently said it increased its investment in internal AI tools more than fivefold in the first seven months of 2026. How does your AI investment compare?

Our tooling and token spend has grown on a similar trajectory, and I'd expect that to be true for most serious players, with models becoming significantly more capable and significantly cheaper per unit of work.

But the most critical investment is in onboarding and training people, changing our processes and the way we work to this new era. Token spend simply follows the speed and quality of that adoption. One of the key changes we made back in 2025 was founding a dedicated AI department, which sits outside the regular team structures and joins other teams to help them improve the way they work.

The way we look at it, tokens are an operating cost with a measurable return, and we hold ourselves to measuring it. In R&D we're seeing efficiency multiples of up to 50x on what the same work used to take. One team refactored its entire tech stack onto a new technology in a month and a half, something that would have been unheard of a couple of years ago. Another delivered a project estimated at 7,000 man hours in two weeks, and simple automations built within a month now save 40,000 human hours a year.

How do you see AI evolving?

How AI evolves is a billion dollar question, and I'd be careful with anyone who answers it too confidently. My guess is that models keep getting faster and more efficient, that more of them shift to running locally and that at some point a new architecture stands out and we look back at LLMs as the thing that kicked it all off.

What I'm far more confident about is that every organization will have to change. AI is moving from being a tool that people use to being something closer to a team member. It takes work end to end, it has context, it makes decisions within the scope you give it. Most companies aren't structured for that. Team sizes, han-offs, seniority levels, approval chains: all of it encodes assumptions about how work was done over the last few decades, and a lot of those assumptions simply don't hold anymore.

It's also much harder for organizations that were messy to begin with. AI doesn't fix inconsistent data or undocumented processes—it exposes them. You can't automate something that only ever existed in someone's head.

On the customer side it isn't fully there yet, but behavior is clearly changing—we're already seeing more than 2x year-over-year growth in revenue from direct LLM redirects. I expect the whole customer acquisition game to adapt to new channels over the next few years. It's hard to say exactly how it will play out, but what we're seeing so far suggests brand perception—how these models collect and distill data about companies from first-party and third-party sources—will play a major role in it.

How has AI changed your recruitment process?

The most important change is that AI fluency became one of the things we actively evaluate. In interviews we make room for a dedicated conversation about it. What does the candidate use, how do they use it, where has it actually changed the way they work. It's an important piece of the conversation for any role we hire for. We believe in hands-on management when it comes to AI, because we don't think a manager can promote an AI-first culture without being hands-on themselves.

The second change is how we look at know-how. We increasingly ask what that person will do to the level of everyone around them. Someone bringing new approaches to working with AI raises the bar for an entire team. A strong individual who is also strong hands-on with AI stands out far more today than the same person would have a few years ago, and the difference in output is much bigger than it used to be. Identifying those people early in the process is one of the things we try to keep track of.

What other technological innovations are you exploring beyond AI?

Almost any technological work you do now has AI somewhere inside it, so the line between 'AI projects' and 'everything else' isn't really there anymore. What I can say is that our biggest investments aren't in models or tools. They're in infrastructure, data, quality, access and organizational structure. That's the unglamorous work: making sure our data is correct and available, that our systems are properly documented and connected, that ownership is clear, that quality is measured rather than assumed.

We do that for two reasons. The first is that it makes our products better on its own terms, independently of AI. The second is that it makes us a far better environment for agents to operate in. An agent is only as good as what it can access and trust. Companies that invested in this over the last years are the ones able to move quickly now, and I expect that gap to keep widening.

Stay tuned for additional interviews with chief AI officers, e-commerce execs and CTOs as part of PhocusWire's ongoing AI Transformation in Travel series. Catch up on our previous conversations with Velit Dundar of Radisson and Javier Cabrerizo of HBX Group.