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24 Jun 2026 | Félix Pérez

How a Hotel Appears in AI Assistants: The Three Layers of Visibility

Félix Pérez of Mirai breaks AI visibility into three layers — model memory, web search, and dynamic data via MCP — and explains which one matters at each stage of the guest journey, and where hotels should actually invest.

This insight summarises How a Hotel Appears in AI Assistants: The Three Layers of Visibility by Félix Pérez, Head of Operations & Business Strategy at Mirai, published on Hospitality Net in June 2026.

Pérez splits AI visibility into three distinct layers — each with different mechanics, different timelines, and very different levers for hotels.

Layer 1 — Model Memory (LLM knowledge). What the model already "knows" from training. Strong brands surface here without triggering a search, which makes this layer a powerful tailwind for the famous and a slow grind for everyone else. It's also the slowest, most opaque, and least actionable layer — models retrain infrequently and you can't see what they pulled in. Pérez recommends sticking to fundamentals: technical SEO, consistent brand presence across sources, and earned media — not paying for unproven "Generative Engine Optimisation" services.

Layer 2 — Web Search. When the assistant needs real-time specificity, it runs a search. This layer looks like classical SEO but with one critical twist: ranking doesn't equal traffic, because the answer happens inside the assistant. Investments here should focus on brand SEO, technical website health, and specific content describing actual amenities — not generic marketing copy that every competitor also produces.

Layer 3 — Dynamic Data Sources. The most strategically important layer. Via protocols like MCP (Model Context Protocol), assistants can query live, structured data from the hotel's own systems — availability, pricing, conditions, policies. This is the layer that supports conversion and post-booking changes, and it's where serious differentiation will sit over the next few years.

The key insight: importance shifts across the funnel.

  • Exploration: model memory dominates.
  • Qualified discovery: web search adds the specifics.
  • Consideration & booking: dynamic data sources decide whether the assistant can actually transact.

What to do: Don't chase the trendy layer — invest in structured, machine-readable data infrastructure so you can compete at the moment the guest is ready to decide.

Read the full article on Hospitality Net →

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