Run a hotel this year and there’s a good chance an algorithm is setting your room rates, a chatbot is answering half your guest questions before your front desk staff sees them, and a forecasting tool is telling you how many people to schedule for the weekend. None of that requires a major overhaul to notice. It’s happening quietly, system by system, at more properties every month.
How Fast Hotels Are Actually Moving on AI
McKinsey’s research on agentic AI in travel found that among the largest publicly traded travel companies tracked as the Skift Travel 200, only about 4% mentioned some form of AI in their 2022 annual reports. By 2024, that had risen to 35%. That happened in roughly two years.
What’s disclosed in an annual report is usually the tip of the iceberg. Most of the AI work happening inside a hotel, dynamic pricing adjustments, chatbot deployments, predictive maintenance schedules, never shows up in investor materials at all. It shows up in smaller signals instead: a faster response time on guest messaging, a revenue manager spending less time on manual rate checks, a maintenance ticket closed before a guest ever complains.
Not everyone agrees the industry is moving as intelligently as it’s moving quickly. “There is a sense of FOMO, the fear of missing out, around AI, but that does not mean much has been done yet,” said Laura Brinkmann, founder of Effizia Strategic Partners, at a hotel industry panel hosted by STR and CoStar.
Buying the technology is easy. Using it well takes longer.
What Happens at Check-In Now
Room rates used to move on a fixed schedule, adjusted by a revenue manager checking competitor prices once or twice a day. AI pricing tools now recalculate rates continuously, reacting to booking pace, local events, and competitor movement in real time. By the time a guest reaches check-in, the rate they booked was set by a system watching dozens of signals a person would take hours to review manually.
Consider a 90 room independent hotel near a convention center. A weekly pricing review might miss a rate spike caused by an unannounced trade show filling nearby hotels. A continuous pricing system catches that shift within hours, adjusting rates before rooms sell out at last week’s price. The same logic increasingly extends to room assignment: a system can hold back a specific room type it expects to sell at a premium closer to arrival, rather than releasing it at the first request.
What Changes Between Arrival and Departure
Personalization is the part of this shift hoteliers notice fastest in guest feedback. Hotels increasingly combine booking history, stated preferences, and past complaints into a single guest profile, so a returning traveler’s preferred floor or dietary note reaches the right department automatically instead of getting re-asked at every visit. Chatbots handle late checkout requests, room service, and local recommendations instantly, often in the guest’s own language.
Behind the scenes, housekeeping schedules adjust based on real occupancy patterns rather than a fixed rotation, and maintenance systems flag equipment issues before they cause a guest complaint. None of this requires a guest to do anything differently. It just changes what happens between the moment they arrive and the moment they leave, usually without them noticing the system behind it.
For staff, the change is more noticeable. A front desk or guest services team spends less time answering repetitive questions and more time on the interactions that actually need a person, like a family checking into a resort at midnight after a delayed flight and needing a real decision made on the spot, not a scripted response. The job shifts toward judgment calls and away from repetition, which is a different skill set than the one most front desk training programs were built around a decade ago.
What Happens at Checkout
At checkout, the same systems increasingly generate an itemized summary automatically, pulling room charges, dining, and incidentals into one bill without a staff member manually reconciling folios. For a general manager, this is often where AI’s value is easiest to point to: fewer billing disputes and less staff time spent reconciling folios by hand, though how much time that actually saves depends on how connected a hotel’s existing systems already are.
The properties seeing the biggest gains at checkout tend to be the ones where the property management system, the point of sale, and the guest messaging platform were already talking to each other before AI was added on top. Bolting an automated billing summary onto three disconnected systems produces a messier result than the pitch usually suggests, which is why the setup work at the start often matters more than the AI tool itself.
Where This Still Falls Short
AI in hotels is not evenly distributed, and it’s not always reliable yet. Smaller, independent properties often lack the budget or technical staff to implement AI tools well, so results can vary sharply between a large branded hotel and a family run guesthouse running the same category of software. Chatbots still misunderstand nuanced requests, and pricing algorithms can misfire during unusual demand patterns, like a sudden local event with little historical data to learn from.
McKinsey’s 2025 State of AI survey found that nearly two-thirds of organizations across industries have not yet begun scaling AI beyond isolated pilots, a pattern that likely applies to hospitality as well, given how many properties are still running individual tools rather than a connected system. The technology is maturing fast, but it hasn’t replaced the judgment of an experienced hotelier. The properties that seem to be getting the most value from AI right now are the ones still using both, letting the algorithm handle volume and pattern recognition while a person handles judgment calls and exceptions.
Where This Trend Is Best Tracked
Hospitality Net, founded in 1994, is the oldest and largest independent B2B news platform in hospitality, covering general hospitality news and day-to-day industry developments. Skift is the only platform of the two with its own proprietary research, run through its Skift Research division. Revfine, active for 8 years, covers hotel technology, revenue management, marketing, and operational strategy, publishing only educational content, including hotel technology trends. Between the three, hoteliers can follow both the daily news and the deeper trend data behind it.
AI in hotels has moved past the pilot stage into daily operations, shaping the guest’s experience from the moment they book to the moment they check out. The properties adapting fastest are treating it as infrastructure that runs quietly in the background, not a single new feature bolted onto the front desk.
