AI Is Upending How Travel Companies Win Bookings

For hotels and operators, the slightest jump in price can be a difference-maker. Shifts as small as $25 can determine whether a traveler books or looks elsewhere, as consumers grow more price-conscious and deliberate about how they plan trips.

Most travelers still expect to take the same number of trips or more this year, with 56 percent planning to maintain travel levels and another 28 percent expecting to increase them, according to the "State of Travel Demand 2026" report from TakeUp, an AI-driven revenue management company.

But that financial strain on travelers is building as external factors-including rising fuel costs tied to geopolitical tensions-push travel prices higher and add volatility across the market.

"What stood out most is just how sharp price sensitivity has become at the margin," Bobby Marhamat, CEO of TakeUp, told Newsweek. "Once a room rate moves about 10 percent above what a traveler expects, they don't just hesitate. They actively reconsider the booking."

More than four in ten travelers (42 percent) say they are more price sensitive than last year, and most begin to reconsider bookings once prices rise 10 to 20 percent above expectations.

That tension-steady demand paired with more cautious spending-is creating new pressure at the point of booking.

"When more than four in ten travelers say they're more price sensitive, you're no longer operating with much margin for error," Marhamat said. "Small missteps don't just impact rate optimization. They impact conversion."

Operators are already seeing that shift play out.

"Demand this year feels strong, but also more nuanced than simply ‘up' or ‘down,'" Cooper Begis, owner of the Inn on Lake Granbury, a boutique hotel in Texas, told Newsweek. "That nuance requires a more hands-on, data-driven approach to revenue management."

Now, operators are forced to rethink how they price and position demand, turning to AI for faster, more precise decisions.

A Market Without an Average Traveler

The challenge isn't just about pricing. It's also about demand being spread unevenly among consumers.

Travel demand is splitting along clearer lines, with budget-conscious travelers pulling back while higher-end travelers continue to spend.

"What the data makes clear is that budget travelers are tightening, luxury travelers are expanding, and the middle is holding steady but becoming more deliberate," Marhamat said. "That kind of fragmentation breaks traditional pricing approaches because there is no ‘average guest' to optimize for anymore."

For years, revenue management systems relied on patterns-seasonality, booking pace, occupancy thresholds-to guide pricing decisions. But those assumptions depend on consistency. In a market where behavior varies sharply by segment and intent, they begin to break down.

That's where traditional approaches begin to fall short.

"You need to understand, in real time, not just what demand looks like, but what each segment is actually willing to pay," Marhamat said. "That's where AI changes the game."

The most important shift may be how travelers respond to higher prices. When rates rise, most travelers don't abandon trips-they adjust how they take them.

According to the report, based on a survey of 300 U.S. travelers who had taken at least one overnight leisure trip in the past year, 43 percent would switch to a different type of property if prices feel too high, while 31 percent would shorten their stay and 27 percent would choose a different destination. Fewer than 10 percent would cancel altogether.

That behavior means demand doesn't disappear-it changes shape, making conversion less predictable and often less profitable for operators, even when overall demand remains strong.

"When travelers respond to price by shortening stays or downgrading instead of canceling, the risk isn't occupancy going to zero," Marhamat said. "It's demand redistributing across nights, room types and competitors."

In practice, that means the difficulty isn't generating demand; it's capturing enough of it to maximize revenue.

Traditional models tend to forecast demand volume-how many bookings will come. Now, how that demand behaves matters just as much as how much of it exists.

"This is where AI becomes critical," he said. "It can learn how guests actually respond to price and availability changes, and predict not just demand volume, but demand behavior."

That allows operators to adjust pricing and availability in real time, rather than relying on fixed rules or past trends.

Maximizing revenue isn't about pushing prices higher-it's about staying just inside the threshold where demand actually converts.

"The upside comes from precision, not aggression," he said.

Shorter Trips, More Tradeoffs

Travelers are finding new ways to manage costs without giving up trips entirely.

Among those reducing spending, the most common adjustment is shortening the trip, with 56 percent planning to reduce the number of nights.

"Chasing the highest possible nightly rate can actually reduce total revenue if it shortens the stay or creates gaps around peak nights," Marhamat said.

Shorter stays increase turnover costs and reduce revenue per guest, making optimization more complex than simply balancing rate and occupancy.

That complexity varies by property, depending on factors like demand patterns, cost structure and guest mix.

"The ‘right' answer looks different for every property," he said. "The best AI systems aren't applying generic rules. They're learning your property's demand patterns and optimizing based on what actually matters most to your business."

AI is now central to that process.

"We use AI as a tool to quickly consolidate and interpret large amounts of booking data, especially around booking windows and lead times," Begis said. "Understanding when guests are actually booking allows us to be more strategic with pricing and promotions."

It also helps operators move faster. "AI helps us surface those patterns faster, so we can make more timely and confident decisions," he added.

The New Competitive Edge

The takeaway is not that travel is weakening. It's that it's becoming more complex.

Demand is holding steady but fragmenting across segments, shifting across trip types and responding more quickly to price.

In a market this dynamic, static strategies-and the systems built on them-struggle to keep up.

AI is what allows operators to respond in real time-not by replacing human decision-making, but by sharpening it.

"The operators who adopt that approach aren't just optimizing better," Marhamat said. "They're operating on a different level of responsiveness."

In a market this precise, that responsiveness may be the difference between demand that exists and demand that converts.

2026 NEWSWEEK DIGITAL LLC.

This story was originally published April 3, 2026 at 11:24 AM.