We didn't go to HITEC 2026 for the demos. We went for the conversations. We sat down with exhibitors right there on the show floor. No script, no prepared questions, just one starting point: tell us what you do, in plain language. This is where it went with Tanya Pratt, Global Vice President of Strategy and Product Management at Oracle Hospitality.
Vassilis Syropoulos argues that before hospitality can benefit from agentic AI, it needs to solve a problem most organizations are actively avoiding: the data foundation underneath it. Using the Prometheus metaphor to frame both the promise and the danger, he maps a four-quadrant framework that shows why clean data without hospitality context is still dangerous, and why trust — earned incrementally, proven on the record — is the only legitimate path to autonomous action.
A practical guide for independent hoteliers explaining AI booking discovery, hallucination risks, GEO, and how connectivity to AI platforms determines whether bookings land direct or via OTAs.
Major chains have built AI tools to defend direct booking conversions, but the discovery journey now starts on ChatGPT and Google AI, platforms brands cannot see, measure, or control.
We didn't go to HITEC 2026 for the demos. We went for the conversations. We sat down with exhibitors right there on the show floor. No script, no prepared questions, just one starting point: tell us what you do, in plain language. This is where it went with Andrew Pirret, Senior Vice President of Product at Alliants.
Drawing on a background in filmmaking, Kristian Lupinski offers a candid, first-person account of experimenting with AI video generation for hospitality marketing and quickly discovering that creative vision and machine output are far from the same thing. The piece raises an unsettling question for the industry: in a race toward synthetic perfection, are hotels optimizing themselves out of the very authenticity that makes a stay worth remembering?
Hospitality Daily and Destination AI launch a live survey to benchmark real AI usage across hotel organizations, covering investment priorities, measurable outcomes, and frontline employee sentiment.
Stefano Pinci writes from the photographer's perspective on what AI actually does — and does not do — to hotel imagery. The technology has become a genuine problem-solver in post-production, he argues, but its greatest risk is not bad output: it is the seductive pull toward a frictionless, anonymous visual average that makes every property look the same and none of them look real.
The author argues that true AI-native hotel distribution requires live pull architecture and settlement layers, a gap Google won't fill due to its ad-auction model, leaving an opening for a new entrant.
Markus Mueller argues that hospitality's real distribution problem has nothing to do with AI or personalization technology — it lies in an inventory model designed in the 1970s that collapses thirty or forty genuinely distinct room products into five website categories. Until hotels start selling real products instead of generic containers, he contends, no amount of sophisticated technology layered on top will deliver the experience guests actually want.
The author argues that fragmented guest identity data across PMS, CRM, and loyalty systems is the core barrier to effective AI, urging hotels to prioritize data governance over AI tool investment.
Hotels face a hard deadline on AI-native distribution as AI shopping assistants already query inventory in real time, making machine-readable availability and direct booking pipes a competitive necessity, not a future option.
Daniel Melnyk makes the case that group and MICE sales is the single most underserved corner of the hotel when it comes to AI — and the one with the highest potential return. The opportunity, he argues, is not in blasting meeting planners with machine-written outreach, but in using a hotel's own first-party data to prospect intelligently, consistently, and in the seller's voice, without adding to an already overloaded workday.
Klaus Kohlmayr argues that revenue management is undergoing a structural shift from reactive optimization to anticipatory intelligence — where pricing decisions are no longer based on historical extrapolation but on probabilistic futures and real-time guest intent signals. In a world where AI assistants increasingly mediate booking decisions, the hotels that act earlier with better data will outperform those waiting for demand to declare itself.
The author argues that hotel content accuracy across distribution channels has become operational infrastructure, as AI systems now judge content consistency to determine trustworthiness before making recommendations.
As AI agents run thousands of hotel searches per session, the cost of being "looked at" shifts from OTAs to hotels that go direct, exposing a hidden infrastructure cost once buried in commissions.
As AI reshapes how travelers discover hotels, most properties are invisible to these systems, while measurement tools fail to prove what tech investments actually return at the property level.
An executive search professional argues that over-reliance on AI and ATS tools is undermining senior hiring, and calls for more direct human engagement throughout the recruitment process.