Over half of hoteliers use artificial intelligence (AI) to generate pricing suggestions, but just one in 10 let the technology make the final call.
The findings come from RoomPriceGenie’s 2026 State of Revenue Management Report, which included responses from 450 hoteliers involved in revenue decisions across Europe, North America and Asia Pacific.
Of the hoteliers using AI to help set room prices (53%), 16% use it extensively. The remaining 35% said they are piloting AI or considering it, and just 11% said they’re not using AI at all.
Approximately 77% trust the technology with varying degrees of confidence, but just 10% of these respondents trust AI to make most pricing decisions on its own.
The remaining respondents have low trust in AI and only use recommendations as guidance (16%), don’t trust AI and wouldn’t use it (4%) or don't know how AI can help with revenue management (3%)
“Technology is moving faster than trust,” the report reads. “RMS adoption and AI curiosity have climbed sharply across the industry. But confidence in AI hasn’t kept pace. If you’ve adopted a system but still second guess what it tells you, you’re in the majority.”
To facilitate trust, RoomPriceGenie, a PhocusWire Hot 25 Travel Startup for 2022, pointed to separate research conducted with RMS, which found that the issue may be hotels’ own incomplete or low-quality data. If users don’t understand why prices are changing, they’re more likely to question or override AI’s recommendations, the report suggests.
“Automation should keep hoteliers in control, not hand control over to a black box,” David Heigl, chief product officer at RoomPriceGenie, said.
“AI can take that further, surfacing insights in plain language and giving recommendations the whole team actually understands, not just the specialists. That’s what turns a system into a sparring partner, rather than something hoteliers just have to trust blindly.”
Technological infrastructure presents another issue. RoomPriceGenie found that 43% of surveyed hotels lack a revenue management system and price rooms based on instinct or fixed seasonal rates (14%) or use spreadsheets and historical data with little automation (29%).
The lack of automation goes beyond revenue management for hotels.
Another recent report from H2c found that 69% of hotels still have staff manually entering guest preference data, compared to 19% using AI-driven extractions from guest interaction. Additionally, the State of Distribution 2026 report from New York University, RateGain and HEDNA found that over 80% of commercial teams still spend one to two days weekly producing reports manually.