This dedicated AI in Hospitality section explores how AI is reshaping the industry, from guest communication and marketing personalisation to revenue management, operations, staffing, cybersecurity, and the evolving role of data and automation across the hotel and travel ecosystem. It brings together practical use cases, expert insights, product and partnership news, leadership viewpoints, and real world lessons from properties and brands of all sizes, helping hospitality professionals separate substance from hype and make informed decisions about where AI delivers value today and what to prepare for next.
Ahead of HITEC, this opinion piece warns hoteliers not to repeat big tech's costly "tokenmaxxing" mistakes, urging outcome-based AI evaluation over vendor-driven consumption metrics.
Canary Technologies' new Agentic Sales Coordinator autonomously handles hotel group and event sales workflows from first inquiry to confirmed booking, debuting at HITEC 2026 in San Antonio.
dailypoint adds MCP support for AI assistants like ChatGPT and Claude, plus Zapier integration connecting to 9,200+ apps, to bring guest intelligence into hotel workflows without manual development effort.
Drawing on HRI researcher Helen Hastie's live robot trials, the article identifies five trust principles hoteliers must apply when deploying robots: calibration, graceful failure, transparency, appropriate form, and genuine utility.
A live webinar on June 25 will gather hospitality operators and robotics leaders to discuss ROI, adoption barriers, and real-world deployment of robots across U.S. hotels.
MMGY Travel Intelligence's 2026 study finds 52% of UK travellers use AI for trip planning, up 12 points year-on-year, the fastest growth among five major European markets surveyed.
A Lighthouse study of 4,545 ChatGPT prompts across 9 destinations finds most hotels are invisible to AI recommendations, with luxury brands and major chains capturing a disproportionate share of mentions.
Despite AI's proven revenue impact in sales, senior commercial leaders resist adoption because AI threatens the structured judgment that built their authority.
Simple Booking's MCP connector suite integrates its CRS with AI agents like Claude and ChatGPT, enabling natural-language queries of booking data, rate parity checks, and demand analysis across 7,000+ properties.
The author argues AI won't replace core hotel systems but will transform the analytics layer, eliminate spreadsheet workarounds, and let hotels use AI agents to build custom workflows without waiting on vendors.
The author proposes Token Cost Per Guest (TCPG) as a standard metric for hospitality AI spend, drawing parallels with healthcare to argue that metered, per-unit AI cost tracking is essential across all industries.
The author argues that hospitality's next competitive advantage lies not in visibility but in maintaining consistent, trustworthy information across every digital touchpoint from discovery through arrival.
The piece argues hotels deploy visible AI features without redesigning underlying operations, creating "AI Theatre" that impresses owners but fails to improve business metrics.
KITRO, active in 500+ kitchens across 40 countries, is scaling internationally as new EU binding targets require a 30% per-capita food waste cut by 2030, with Spain's Ley 01/25 adding national urgency.
A critical reading of Booking.com's partner messaging argues its "protection" pitch to independent hotels masks a platform dynamic where independents are the foundation being guarded for Booking's own benefit.
The author introduces TCPG (Token Cost Per Guest) as a discipline for hotel operators to meter AI spending, arguing most deployments fail because costs are invisible inside bundled platform contracts.
TRAVHOTECH's HumAIn Framework proposes a four-layer AI architecture for hospitality, separating data infrastructure, software automation, physical robotics, and human strategic oversight.
Lighthouse's Ernest connects frontier AI models to hotel-specific data, systems, and workflows, offering commercial teams intelligence, recommendations, and automated actions across 500+ hospitality platform integrations.
Generally, more people with access to AI will not mean better solutions, it will mean more noise in the market, more fragmented and badly deployed technology - just like the last decades, but at a bigger scale, and the people who suffer are hotel employees and guests. I do believe that to stand out from the pack and deliver something truly remarkable, you need genuine innovators to bring all these solutions together in a coherent ecosystem that is open, collaborative, and truly end-to-end in how we serve guests. The best technology partners will build closer partnerships at the backend layer, while hoteliers can build complete AI workflows on the frontend.
By HITEC 2030, AI will not have eaten established hospitality tech. It will have eaten the repetitive workflow layer around it. Hotels will still rely on PMS, CRS, RMS, payments, distribution, and other systems of record. Those systems are too operationally critical to disappear quickly.
2030 is a long time from now, especially in AI-years, which are only about 60 days long!If I think about the current trajectories and strategies of the bigger companies that will lead this movement, I see larger travel enterprises implementing foundational agentic backbones like Frontier from OpenAI or Claude Enterprise from Anthropic.
Booking Holdings and Airbnb are each funding separate AI travel ventures as hedges, raising the risk that hotels will soon rent visibility from the same parent that runs both the OTA and the assistant.