Exclusive Feature: A guest opens Claude on their phone and types: 'Best hotel restaurant for local seafood in Dubrovnik', your property has been serving Adriatic fish for fifteen years, your head chef sources from local fishermen by name, your wine list is built around Croatian producers but none of that appears in the answer.

This is not a technology problem. It is a content structure problem. And it is more urgent than most hotel F&B managers realize.
What AI engines actually do when someone asks about your hotel

When a traveler asks an AI assistant about your property, the model does not visit your website. It draws from what it has already processed: editorial mentions, structured content, reviews, forum discussions, industry publications. If those sources say nothing specific about your F&B offer, the model has nothing to work with.

Alberto Chierici, founder of AQURA, a GEO strategy agency working with hospitality brands, explains the mechanism: when an AI engine receives a query, it does not process it once. It expands that query into 10 to 50 parallel sub-queries, then corroborates the results across all of them. If there is no corroboration of sources saying the same thing about your property, the model has nothing to cite with confidence.

This is the structural difference between SEO and GEO. Search engine optimization is about ranking. Generative engine optimization is about being cited. A hotel can rank well on Google and still be invisible to ChatGPT, Claude, or Perplexity, because the content that ranks may not be structured in a way that AI engines can extract, synthesize, and cite with confidence.

Why hospitality content fails AI engines

Most hotel F&B content was written for human readers and Google crawlers. Menu descriptions, seasonal announcements, chef bios. This content exists, but it is rarely written in a way that gives an AI engine something citable: a clear claim, attributed to a source, consistent across multiple surfaces.

Chierici identifies three layers where most hotel properties fall short.

The first is volume: many hotels do not have enough content outside their own website.

The second is structure: even when content exists, it is not formatted in a way that AI engines can parse and cite.

The third is distribution: most hotel marketing teams assume that Instagram and Facebook are sufficient surfaces, while ignoring industry publications, local press, forums, and review platforms, which are the sources AI engines actually draw from.

The implication is counterintuitive. A hotel with modest Google SEO but strong third-party editorial presence may perform better in AI-generated recommendations than a hotel with an expensive, perfectly optimized website and no external citations.

What content AI engines trust most

The data makes the hierarchy clear. According to Similarweb’s 2026 Generative AI Landscape report, travel is the highest-citation category in AI search: ChatGPT includes citations in 22.6% of travel answers, compared to a cross-category average of 6.8%. When those citations occur, the source breakdown is unambiguous. News and publisher sites dominate. Reviews and user-generated content come second. Brand-owned pages account for roughly 5 to 10% of what AI engines reference, while earned third-party sources account for approximately 84%.

The implication for hotel F&B is direct. A property whose story lives primarily on its own website is competing for the 5 to 10% of AI citations that draw from brand-owned content. A property whose story appears in trade publications, regional press, and review platforms is competing for the 84%.

Chierici frames the mechanism precisely: disseminating consistent messaging across different third parties is powerful because AI models expand your query into ten to fifty parallel sub-queries and corroborate results across all of them. If there is no corroboration of sources saying the same thing about your property, the model has nothing to cite with confidence.

This gives hotel F&B managers a structural advantage they are not using. Publishing operational expertise in industry press is not a branding exercise. It is a citation signal. A piece in a hotel management publication that describes your sourcing philosophy, your seasonal menu logic, or your food cost approach creates exactly the kind of structured, attributed, third-party content that AI engines trust.

The first step for a hotel with zero GEO strategy

For a property that has decent Google presence but has never thought about AI visibility, Chierici recommends starting with competitive observation rather than content creation. Search for a nearby competitor by name in an AI assistant. Notice how it is described, which sources are cited, and whether those sources are ones your property uses. Then search by category, not by brand name.

Ask the questions a traveler who has never heard of your hotel might ask: best seafood restaurants near the old town, hotels with locally sourced menus, where to eat like a local in this city.

Notice which properties appear consistently across multiple queries over a period of days. Those are your benchmarks. The sources they appear in are your targets.

The observation exercise costs nothing and takes less than an hour. It tells you exactly where the gap is between what AI engines currently know about your property and what they know about the properties they recommend instead.

What this means for hotel F&B specifically

The F&B department has a structural advantage in GEO that most properties are not using. Food, sourcing, culinary identity, and dining experience are high-interest topics for travelers. Guests ask AI assistants about restaurants and dining far more often than they ask about room configurations or loyalty programs. A hotel whose F&B story is well-documented across multiple credible surfaces has a significant discovery advantage over a hotel whose food offer is described only in its own marketing materials.

The content gap is specific. Most hotel F&B managers have deep operational knowledge that has never been written down in a discoverable format. The sourcing relationships, the seasonal logic, the food cost philosophy, the decisions behind the menu. This knowledge exists in practice. It does not exist as citable content.

Writing it down, publishing it in relevant channels, and ensuring it appears consistently across multiple sources is the operational definition of a GEO strategy for hotel F&B. It does not require a technology investment. It requires a decision to treat operational expertise as content.

Dr. Alberto Chierici is an entrepreneur, AI expert, and writer focused on the human edge in an AI-driven world. He helps founders and organisations adopt AI in ways that are effective, trustworthy, and deeply human. His latest work includes helping personal brands with visibility in AI search.

Leo Ljubicic is a master chef, master pastry chef, F&B Manager, and culinary instructor at RCK Dubrovnik (since 2013). He is a WorldSkills Croatia evaluator and founder of LPI LABS, an independent hospitality intelligence platform. He writes on F&B operations, AI in hospitality, and Adriatic market dynamics for HotelExecutive, FSR Magazine, Forbes Croatia, and 4Hoteliers.com. Contact: legal@lpilabs.io / linkedin.com/in/leo-ljubicic

This is strictly a 4Hoteliers.com exclusive feature. Reproduction in any shape or form without explicit permissions is prohibited.