When AI Travel Breaks, It Kills the Guest Experience
Everyone’s excited about agentic travel right now, and honestly, they should be.
The idea that you won’t spend hours researching flights, hotels, excursions, or family logistics is real. Your LLM will know who your kids are, where you like to sit on a plane, which hotel brands you prefer, what loyalty programs you’re part of, and what kind of trips you usually take. It’ll just… book everything.
That part is coming fast.
But there’s another side to this that people aren’t talking about enough — and it’s the part that actually touches the guest during the trip. Because if AI is involved in the experience itself, not just discovery and booking, it has to work really well. And when it doesn’t, the failure isn’t subtle.
It’s loud.
A Small Failure That Tells a Bigger Story
Over winter break, I took my kids to a local resort. It’s one of those places designed for families — indoor water park, outdoor skiing, lots of moving parts. The kind of environment where guest experience actually matters.
They had rolled out a mobile app with a messaging system. The AI agent had a name — Willow. From the jump, it felt surprisingly human. Fast responses, conversational tone, very “concierge-like.” I knew there wasn’t a real person chatting with hundreds or thousands of guests, but the illusion was good enough that you stopped thinking about it.
And that’s the danger.
One day, we were leaving our room and I sent a message asking if housekeeping could come by while we were out. The system confirmed. Twice. “Request sent. Someone will take care of it.”
We came back hours later. Nothing. I messaged again. Same thing. “Something must have gone wrong — we’ll send someone right over.” Still nothing.
Eventually, we called the front desk. They called housekeeping. Housekeeping told us they never received any request.
At that point, I wasn’t annoyed, I was curious. Because I knew exactly what had happened.
When the AI Sounds Smart but Isn’t Wired In
From a technical perspective, this wasn’t mysterious. The AI layer was confirming actions that weren’t actually making it into the operational system. Somewhere between “chat message” and “housekeeping workflow,” something broke — an API, a queue, a timeout, bad error handling.
And once you notice that, you start seeing other cracks. The app was slow. Messages rendered out of order. Older messages would suddenly appear after newer ones. It felt rushed. Like something that was pushed live before it was fully hardened.
Later, someone from housekeeping actually called our room to apologize and asked if I could send screenshots of the chat so they could forward them to IT. That told me everything. This wasn’t a one-off. They needed evidence because they knew the system was failing.
This wasn’t malicious AI. It wasn’t hallucinating. It was worse. It was a confident but broken AI chatbot.
Why This Gets Dangerous Fast
In my case, the impact was minor. We waited a bit longer for housekeeping. Life goes on.
But now imagine this happening with something that actually matters.
An AI confirms an excursion booking. A family shows up the next morning. The operator says, “We have no record of you — and we’re fully booked.” Or airport transportation that was “confirmed” never shows up. Or a dinner reservation never made it into the system on a sold-out night.
That’s when AI stops feeling helpful and starts feeling irresponsible.
And here’s the part people miss: once companies start trusting AI to handle most guest interactions, they start cutting human staff. Fewer front-desk people. Smaller support teams. Less redundancy. Because, hey — AI handles 90% of it, right?
Sure. Until it doesn’t. And when that 1% failure happens, the guest can’t get a human — because there aren’t enough humans left. That’s when the experience really falls apart.
AI Doesn’t Fail Gracefully
Humans mess up all the time. But humans can recover. They can explain, apologize, improvise, and fix things in real time. AI, when it’s poorly implemented, does the opposite. It reassures you while doing nothing. It confirms things that never happened. It creates the illusion of progress.
And that illusion is what breaks trust. I would have preferred the system to say, “Please call the front desk.” At least that would’ve been honest.
This Is the Real Job of AI in Hospitality
I’m not anti-AI in the guest experience. Quite the opposite. I think it’s inevitable and, done right, incredible.
But if you’re a hotel, resort, airline, or experience operator, you have to treat AI like infrastructure, not a feature. That means end-to-end testing, not just pretty UI. Real monitoring, not blind trust. Redundancies when systems fail. Clear, immediate human fallback.
If AI is part of the stay, it can’t be “mostly working.” Mostly working is how you create bad memories.
The Part No One Wants to Pay For (But Everyone Depends On)
Here’s the uncomfortable truth: none of this is a product problem. It’s an infrastructure problem.
AI that touches the guest experience isn’t something you can half-build, outsource cheaply, or rush out the door because a competitor announced something similar. It requires real engineers, real systems thinking, and real money. Not just to launch it, but to make sure it scales, doesn’t silently fail, and doesn’t lie to your customers when something breaks.
This is unsexy work. Message queues. API reliability. Error handling. Monitoring. Fallback logic. Load testing. Redundancy. Humans in the loop. The stuff no guest ever sees — until it’s missing.
And this is where a lot of travel companies get it wrong. They’ll happily spend millions on brand, marketing, and a glossy app, but hesitate to invest in the backend and the technical team required to make the experience actually reliable. So the AI sounds smart, but the plumbing underneath can’t support it.
That’s how you end up with systems that confidently confirm things that never happen.
If you’re serious about AI being part of the stay — not just part of the pitch deck — then you have to fund it like core infrastructure, not like an experiment. That means hiring strong engineers, empowering them to say “this isn’t ready,” and resisting the urge to optimize headcount before the system has earned that trust.
Because in hospitality, AI doesn’t get graded on innovation. It gets graded on whether it works at 9pm on a Friday, when a guest is tired, traveling with kids, and just wants things to function.
Spend the money. Build it properly. Stress it until it breaks — and then fix what broke.
Because the cost of over-investing in infrastructure is measurable. The cost of a broken guest experience is priceless.