How AI Recommends Restaurants and Hotels

The question "where can I eat well downtown" or "a charming hotel near the beach" is no longer asked only in search engines. Many people put it straight to ChatGPT, Gemini or Perplexity and expect a short list of specific recommendations. In hospitality this changes the rules: the model acts like a concierge who has read thousands of reviews and listings before answering.

The good news is that the signals driving that recommendation are largely the same ones you already work on for Google. The difference lies in understanding how AI uses them.

Where AI gets its recommendations

When you ask for a restaurant or a hotel, the model combines several sources. It draws on your Google profile with its reviews and rating, on directories and travel platforms, on guides and articles like "the best places to eat in this city", and on scattered mentions in blogs and local press. The more your name appears across all those sources with a positive tone, the more likely you are to show up.

That is why a business can have great food and little AI visibility: if its digital presence is thin or inconsistent, the model has no material to name it with confidence.

Your Google profile is the foundation

The Google business profile remains the central piece. AI reads it as a reference for basic data and reputation. It pays to keep it spotless.

Reviews carry a lot of weight

For eating and sleeping, other people's opinions are almost everything. AI looks not only at the average score but also at volume, freshness and what people actually say. A restaurant with many reviews mentioning "warm service" or "generous portions" stands a better chance of appearing when someone asks for exactly that. Nurture a steady flow of genuine reviews and reply in your own voice. Fake reviews get detected and end up costing you.

Beyond Google

Sticking to a single site leaves you exposed. AI cross-checks sources, so it pays to be present, with consistent data, in directories and platforms relevant to your sector and area. For a hotel that may mean travel portals and destination guides. For a restaurant, food aggregators and local listings.

The detail that makes the difference is consistency. If your name, address and hours are identical everywhere, the model trusts you. If it finds three different versions, it hesitates and leaves you out.

Your own content that AI can quote

A site with useful information helps more than it seems. A page explaining your menu, your allergens, your pet policy or which kind of traveller enjoys your hotel gives the model concrete phrases to use when describing you. Think about the real questions your customer asks and answer them in clear text.

Check whether they already recommend you

Before investing effort it helps to know the starting point. Ask each engine the typical queries for your area ("where to eat well in", "family hotel in") and see whether you appear, alongside whom and with what description. A manual review gives a snapshot. To track the evolution daily there are tools such as Bee LLM that record what each engine says about your business.

With that information you stop assuming. You know which queries ignore you, which competitors take the recommendation and which weak signal to reinforce first. In hospitality, where a well placed suggestion fills tables or rooms, being in the AI's answer is a channel you can no longer ignore.

Keep reading: AI search visibility metrics and KPIs · tools comparison.