In Fieldwork. Q4 2026

US Hotel AI Recommendation Report 2026

A study of how guest reviews, word of mouth and public evidence reach AI hotel recommendation in the United States.

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Report overview
Market
United States
AI Engines
5 channels
Status
In Fieldwork
Expected
Q4 2026
What this report answers

Four questions the US hotel market has not answered.

01
Which US hotel brands does AI recommend for which occasions?
Tested across family travel, business stays, luxury, wellness, location-specific and value segments.
02
What evidence does AI rely on when recommending a hotel?
Which review platforms, third party sources, editorial coverage and owned evidence appear most in AI outputs.
03
Where do strong guest review scores fail to translate into AI recommendation?
The disconnect between what guests prove in reviews and what AI associates with a property.
04
What do AI recommended hotels have in common that others do not?
Evidence patterns, source types, review characteristics and positioning approaches that correlate with AI recommendation.
Report structure

When published, this report will include.

All sections below will contain original data from Cited fieldwork. No illustrative data will be presented as real findings.

Executive Summary
Methodology & Sample
Recommendation Leaders
Guest Review Themes
Public Evidence Analysis
Sources AI Uses
Trust to Recommendation Gaps
What Leaders Have in Common
Implications for Hotel CMOs
Register for early access.
We will send the full report as soon as fieldwork is complete. No illustrative data will be shared as real findings.
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