Mews Reports Wpread AI Use in Hotels

According to the Mews Hotelier Survey 2026, conducted between December 2025 and March 2026 across more than 500 properties globally, 98% of hoteliers reported using artificial intelligence in their operations within the prior six months (Hotel Business; Hospitality Trends). The survey measured AI involvement across 19 common hotel tasks and found AI participates in an average of 11 tasks and handles more than half the workload in those tasks (Hospitality Trends). Adoption spans front office, commercial, food and beverage, and leadership functions, with highest reported use at upper-midscale, upscale, and luxury properties (Hospitality Trends).

Hospitality Trends summarizes the survey's usage matrix and governance metrics: 92% of respondents said they are optimistic about AI and 83% trust AI tools to support decision-making, while 41% reported having no formal AI policy, relying instead on verbal guidelines or nothing at all (Hospitality Trends; Hotel Business). The survey shows a correlation between governance and trust: properties with a formal AI policy reported 92% strong trust in AI versus 49% among those without formal guidelines (Hotel Business).

On Mews' podcast episode summarizing the research, Madeline Bushbeck, Senior Product Manager at Mews, said, "The hotels that will win with the new AI space aren't the ones who found the best vendor; they're the ones who actually understand their own operations well enough to know what to automate, what to protect, and how to make AI technology actually theirs and work for them" (Mews podcast transcript).

Editorial analysis: The survey documents widespread operational adoption while highlighting selective resistance to automating guest-facing welcome moments, with 59% of hoteliers preferring human-led check-in and welcome experiences (Hotel Business). The data indicate that experience with AI increases both comfort and discernment about which moments to automate, rather than simple blanket enthusiasm (Hospitality Trends).

Editorial analysis - technical context: Responses in the survey show hoteliers increasingly demand property-specific intelligence rather than one-size-fits-all models. Hospitality Trends reports Mews is developing a semantic layer intended to surface institutional knowledge held in spreadsheets, staff memory, and disconnected systems so AI tools can act on property-specific signals. This reflects a broader industry shift toward combining local data context with vendor models.

According to the survey, revenue growth is the primary outcome sought by the most AI-proficient properties: 52% of those properties cited revenue growth as their top objective for AI, ahead of efficiency or cost reduction (Hospitality Trends; Hotel Business). The report also finds properties with stronger AI capabilities index higher on outcomes such as increased guest spend and upselling.

Observers should monitor three indicators: adoption of formal AI governance across properties, vendor capabilities for property-specific modelling and semantic integration, and measurable business outcomes such as revenue-per-available-room and upsell rates tied to AI initiatives. Reporting highlights the governance gap-41% with no formal policy-which practitioners and vendors will likely flag as a risk area.

Editorial analysis: For practitioners in hospitality and adjacent verticals, the Mews data illustrate a common transition stage where broad experimentation yields pockets of meaningful value but governance, data integration, and property-specific modelling remain rate-limiting. Vendors promising out-of-the-box revenue improvements will increasingly be judged on their ability to ingest and act on property-level institutional data.