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Your Hotel Is Invisible on LLMs, But Not for the Reason You Think

A benchmark study by Americas Great Resorts (AGR) reveals serious issues with AI engines recommending hotels. The study tracked 824 recommendations across ChatGPT, Gemini, and Google AI Mode in six major U.S. markets, finding that AI recommendations are highly concentrated, with an average of just five hotels taking half of all recommendations. More critically, AI recommendations include closed hotels, such as the demolished Mandarin Oriental in Miami. The study indicates that AI search relies on document authority rather than entity facts, leading to stale information. It suggests hotel IT and marketing co-own data governance to optimize public entity records.

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Impact and considerations

AI recommendations are becoming a key discovery channel, but suffer from stale data and concentration; hotels need data governance to improve visibility.

Key points

  • AGR study tracked 824 recommendations, finding high concentration
  • An average of five hotels take half of all recommendations per market
  • AI recommendations include closed hotels, such as Mandarin Oriental in Miami
  • AI search relies on document authority rather than entity facts
  • Recommend IT and marketing co-own data governance to optimize public entity records

Sources and time

Primary source
Hospitality Technology
Other sources
0
First source publication
4 Aug 2026, 05:41
Page published
12 Aug 2026, 14:17
Last updated
4 Aug 2026, 05:41
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