93% of AI-Using Travelers Turn Problems Into Quick Fixes

If you ask people how AI fits into their trips, many will give you a similar answer. At some point before the trip, someone asks ChatGPT for a five-day itinerary or a shortlist of places worth exploring. 

Maybe they asked it to compare flight prices across three dates, or to explain which parts of a city are walkable versus which require a rental car. It’s the kind of research that happens at a kitchen table weeks before departure.

Among travelers who use AI for trips, 60% used it to find hotels or vacation rentals before leaving, and 54% used it to research local restaurants or activities.

But people aren’t done with AI after they finish planning. Vogo surveyed 1,034 U.S. adults who used AI to plan a leisure trip in the past 12 months, and found that 91% used it again once the trip was underway. That tracks with travelers’ broader shift toward shorter, more spontaneous trips, where more of the trip gets figured out after arrival.

That in-the-moment mindset shows up even more when something actually goes wrong. When a mid-trip problem arises, 93% of travelers who already use AI reach for it to help sort things out. AI has moved beyond answering simple questions and into suggesting changes that involve real money. This raises questions about how far travelers will let AI go, and where they still want the final say.

When a Trip Falls Apart, 93% of AI Users Hand the Problem to AI

If you travel enough, something will eventually go sideways during a trip. Among mid-trip AI users who ran into a problem, 93% turned to AI to recover or adjust, and 82% said it helped. 

That reliance holds even though AI doesn’t always get it right, especially for younger travelers. Eighty percent of 18-29 mid-trip AI users hit at least one inaccurate recommendation, compared with 23% of travelers 62 and older. The 18-29 group is also far more likely to say that AI made their trip worse (29% vs. 2% for the 62-and-older group). This suggests that AI isn’t reliable enough to skip a second check. That’s exactly where a real booking platform fits in.

Travelers aren’t just using AI to manage problems, though. They lean on AI for plenty that has nothing to do with a crisis: finding a restaurant or activity on the spot (54%), getting directions or navigation help (48%), renting a car or hailing a taxi (29%), translating text (27%), and translating speech (27%).

Industry coverage has treated AI as a tool for deciding where to go. But our data shows that travelers are increasingly turning to it to help with a broader range of issues, even after they’ve arrived, whether that’s a canceled activity or a hotel that falls through.

Trust in AI Goes Up When the Stakes Increase

Thirty-seven percent of travelers who use AI in the middle of a trip say they trust it more during the trip than they did while planning at home, and 57% put that trust about even.

There’s a catch, though. That trust is about finding information in the moment, and some of what looks like growing trust is really just the easiest option available. When you’re standing in a terminal at 11 pm, stressed about your flight that was just canceled, an AI app can take a messy question and return something actionable in seconds. A help line has a hold time, and a search engine hands you multiple links to sort through yourself.

“It’s less that people trust AI in a crisis versus other options, and more that it’s the best option available,” said Heath Hammett, CEO of Vogo. “AI can do things other sites and sources can’t. One app, any complex question, and a consolidated answer pulled from multiple sources. Almost nothing else works that way.”

That need for speed also shows up just as much in smaller, everyday calls, like picking a restaurant or figuring out how to get across town. Nearly 7 in 10 mid-trip AI users went with AI’s recommendation on decisions like these without checking reviews or comparing options, and a third did it either always or almost always.

But AI’s decisions are also starting to cause friction with the people on the trip, and it doesn’t seem to matter who you’re traveling with. Forty-two percent of travelers say relying on AI has caused a disagreement with their travel companions at least once, and that number holds steady across every travel party type, from 40% among couples without children to 47% among friend groups.

Still, travelers who use AI trust it enough to lean on it in the middle of a trip. But where they draw the line is revealing, and it stops well short of the checkout page.

More Than Half Have Already Let AI Find Them a Place to Stay Mid-Trip

Accommodations are where actual money comes into play. More than half (53%) of travelers have used AI to find or rebook a hotel or vacation rental mid-trip. Of those, most booked what AI recommended, but 20% of mid-trip AI users booked something different. Even with AI’s recommendations, plenty still shop around.

There’s also room for AI to grow in this regard. Another 32% haven’t used AI in this way yet but would consider it, and only 15% have ruled it out entirely. So 85% of AI-using travelers are at least willing to let AI help them find a place to stay mid-trip.

However, the age splits are sharp. Sixty-one percent of travelers aged 18-29 have used AI to find or rebook accommodations mid-trip, with 37% booking what AI recommended and 25% booking something else. Only 24% of travelers 62 and older have used AI to find or rebook accommodations mid-trip, with 18% booking based on recommendations and 6% doing something else. 

The pressure isn’t the same for everyone. A solo traveler can take whatever room is left. A family that needs two beds and a pool at a family-friendly resort they carefully selected has a much narrower set of options when they show up to a hotel at 9 p.m. to find that their reservation fell through.

The easy assumption is that older travelers don’t like AI as much because they use it less often, but the data says otherwise. Travelers who used AI viewed it positively at similar rates across all age groups. Fifty-two percent of 18- to 29-year-olds, 59% of 30- to 45-year-olds, 58% of 46- to 61-year-olds, and 62% of travelers 62 and older said AI improved their trip and actually gave it the highest marks.

This makes the case for AI and booking platforms working together, not one replacing the other. AI is good at narrowing an urgent issue into a short list of possibilities, but plenty of travelers still go elsewhere to compare options before they book. You can see that division clearly in the payment data below.

Travelers Will Let AI Handle the Small Stuff, but Want Final Say on Booking

People are more comfortable letting AI handle smaller, less consequential tasks. This is consistent with what travelers have actually done. For example, 52% are comfortable letting AI find a restaurant or activity on the spot, and 54% have actually done so. Forty-eight percent are comfortable with getting directions from AI, and 48% have done so, so comfort and behavior line up almost exactly here. 

Comfort drops once the stakes start to rise. When asked where they’d be least comfortable relying on AI mid-trip, travelers named decisions involving a significant amount of money (40%) and sharing personal or financial information to complete a booking (35%).

Payment draws the sharpest line. Only 20% would let an AI assistant book and pay for a stay without reviewing the final choice. Another 25% would allow it, but only up to a set spending limit. Eighteen percent would never let AI handle payment at all. Everyone else falls somewhere in between, wanting some kind of approval or limits before AI can spend their money, or only allowing AI to book and pay for low-stakes stays that are cheap or refundable.

Some of that caution is warranted. When AI recommended a place to stay, 45% of travelers found the price matched what AI told them, but almost a third didn’t (16% found the price higher and 15% lower). For anyone using AI to find affordable places to stay, it’s the higher-price surprises that sting. What travelers want from AI is speed with an accurate price attached.

“A simple way to stress-test a recommendation is to ask the same question again with slightly different wording, or run it against a different set of travel dates,” said Hammett. “If the answer changes, that’s worth noticing before you book.”

AI Narrows the List. The Booking Platform Handles the Rest.

AI’s role in travel has changed shape entirely over the past two years, moving from a research tool people consulted before a trip into something they keep reaching for once they’ve actually landed. A mid-trip disruption requires a quick answer, and AI is good at narrowing a broad question into a few workable answers. Handing over the actual booking is a different matter.

“Booking on someone’s behalf takes permission, setup, and trust, not just a good suggestion,” said Hammett. “Expect real progress on that over the next year and a half, but low-risk bookings, like a rideshare or a dinner reservation, will go automated long before accommodations do. Travel is emotional, and it will be hard for people to hand that off.”

AI is good at plenty of mid-trip tasks, but pricing isn’t where it has the edge. Checking what a vacation actually costs on the live booking page takes about a minute, and it’s more accurate than a quoted estimate. And it involves real money, so most travelers want to make that final call themselves. That’s the moment a booking platform earns its place.

Rising travel costs make checking the real price against AI’s estimate more valuable every year, especially when plans fall apart, and you need to see what’s available and what it costs, right now. Compare stays across booking sites on Vogo and book with confidence, whether you’re planning six months out or six minutes after your flight gets canceled.

Methodology

The survey was conducted by Centiment for Vogo. The survey was fielded between July 15, 2026, and July 18, 2026. The results are based on 1,034 completed responses from U.S. adults aged 18+ who have used AI to help plan a leisure trip or find information mid-trip in the last 12 months. Respondents were recruited using nationally representative quotas on age, gender, and region, with natural fallout for additional demographic breakdowns. Data is unweighted, and the margin of error is approximately +/-3% for the overall sample, with a 95% confidence level. Certain questions were shown only to respondents who reported using AI mid-trip (n=943). Disruption-specific figures are based on respondents who reported experiencing a mid-trip disruption (n=874). Q7 figures reflect only the answer choices representing distinct mid-trip AI tasks.

Fair Use Statement