AI Is Already Deciding Where Guests Stay And Where They Eat by Dawn Gribble MIH MCIM
/Before a guest reaches your website, an AI system may already have formed an opinion about your business.
A hospitality operator contacted me recently about a situation that will feel familiar to many. Midweek service was steady. Delivery volume was normal. No marketing campaigns had changed and no prices had moved. But staff were dealing with a constant stream of clarification. Guests were asking whether dishes still came with sides that had been removed months earlier. Delivery customers were questioning prices they were certain they had seen somewhere else. Some were arriving expecting offers that the restaurant had never run.
Nothing was technically wrong with the marketing. Menus were live, platforms were active, and reviews were still coming in. Yet the decisions were already being made somewhere else.
Right now, more than half of consumers say they are using AI tools to help decide where to eat. The same behaviour is rapidly appearing in travel and hotel search as well. For hospitality businesses, that means the first interaction with your brand is increasingly not your website, your booking engine, or your menu.
It is a summary. A recommendation. Sometimes a shortlist produced in response to a simple question such as Where should I stay tonight? or Where should I eat nearby?
How The Guest Journey Has Changed
For years the hospitality buyer journey followed a familiar sequence. Guests discovered ideas through inspiration, often on social media, through recommendations, or travel content. They moved into planning, comparing options through search engines, maps, review platforms, and brand websites. Finally they confirmed details before committing to a booking or an order.
Each stage depended on different information and different triggers. Good marketing worked because it supported those moments in sequence.
AI has compressed much of that process into a single interaction. A guest asks a question and the searching, comparing, and shortlisting happen at the same time.
The system gathers information from multiple sources and presents an answer. Verification has not disappeared. It has been automated. Before recommending a venue, AI systems cross-check menus, room information, reviews, images, opening hours, policies, and other operational details across the sources they consider reliable.
The result is that many hospitality decisions now happen before the guest reaches your own digital channels.
AI Doesn’t Read Marketing. It Verifies Information.
AI systems are not trying to interpret brand tone or creative positioning. They are trying to answer a question quickly and reliably. To do that, they look for information they can confirm. Menus, prices, availability, opening hours, amenities, facilities, and policies are compared across multiple sources. When those details align, the business becomes easy to recommend.
When they do not align, the system does not pause to resolve the discrepancy. It simply moves on.
In this environment marketing content stops behaving like persuasion. It becomes operational input. If pricing is unclear the system cannot compare. If availability is vague it cannot confirm. If information appears fragmented across platforms it cannot transact with confidence.
When that happens the business does not necessarily appear incorrect. It simply becomes harder for the system to recommend.
The Hidden Profile Every Hospitality Business Now Has
AI systems are already building working profiles of hospitality businesses from the signals they can observe. Those signals include information across websites, menus, listings, reviews, policies, photos, and historical material.
Together they form something I often describe as an AI credit score. It is not based on what a brand says once. It is based on patterns across the entire digital estate. The system asks whether it can confidently answer practical questions that guests have.
Is this hotel suitable for families?
Does the restaurant offer vegetarian options?
Is the bar open late?
Is delivery reliable during busy periods?
When information is consistent and current, the system can place the business into those categories with confidence. When details are unclear or contradictory, that confidence drops.
When confidence drops, the business appears less often in recommendations, even if it offers exactly what the guest is looking for.
When AI Gets It Wrong, Operations Feel It First
In many hospitality businesses, AI mistakes show up on the floor long before they appear in analytics dashboards.
Across OTAs and delivery platforms, operators have already encountered situations where AI systems created promotions that never existed, menu items were rewritten incorrectly, listings contained fabricated offers, or customers submitted AI- generated images to support refund claims.
These situations create very real operational pressure. Staff lose time explaining discrepancies. Guests become frustrated when expectations do not match reality. Refund disputes increase and reviews reflect confusion that the business never intended to create.
The New Discipline: Hospitality Data Management
The hospitality businesses that perform best in this environment are not necessarily the most creative. They are the most consistent.
AI systems favour organisations whose information is clear, structured, and aligned across channels. That requires a different discipline behind the scenes. The most effective approach is maintaining a single source of truth that defines how the business actually operates.
This working document should include core operational facts such as opening hours and service modes, menus or room types and pricing rules, facilities and accessibility information, approved images and visual assets, and policies covering reservations, cancellations, and complaints.
Anyone publishing on behalf of the business, including marketing teams, agencies, delivery partners, web developers, and PR teams, should be working from the same reference.
When something changes operationally it should be updated there first. That is how you prevent multiple versions of the same business appearing online.
Conclusion
AI is not evaluating creativity or brand intention. It is assessing whether a hospitality business appears clear, stable, and reliable enough to recommend. That judgement is formed by comparing signals across everything the system can see, including menus, listings, reviews, images, policies, and recent activity.
The work that removes confusion inside the business now directly shapes how confidently that business is represented outside it. In hospitality clarity has always mattered. In the age of AI search it determines whether your business is even considered.
Dawn Gribble MIH MCIM
Hospitality Marketing Insight
www.hospitalitymarketinginsight.com
Dawn Gribble is a hospitality marketing strategist with more than 25 years’ experience working with restaurant groups, operators, and hospitality brands internationally. She publishes the weekly Hospitality Marketing Insight newsletter, where she writes about marketing strategy, AI, and digital performance in hospitality.
