AI Hotel Landscape
How leading AI assistants recommend hotels — 616 prompts across 56 destinations, refreshed every Monday.
+ 44 more
The 616 prompts we ask Copilot every week
56 destinations × 11 templates. Each prompt has structured dimensions: city, country, region, persona (couples / families / solo / business), budget (luxury / mid / budget), and location zoom (wide city vs neighborhood vs landmark). Control prompts are unmodified baselines.
Every destination below gets the same 11 question types — just with the city name swapped in. That's how 56 destinations × 11 templates = 616 prompts per platform per week.
- luxury hotels in <city>
- family friendly hotels in <city>
- hotels in <city> with rooftop pool
- hotels near <neighborhood>, <city>
- boutique hotels in <neighborhood>, <city>
- best hotels in <city> for solo travelers
- best hotels in <city>
- affordable hotels in <city> under $200
- best hotels in <city> for couples
- best hotels in <city> for business travelers
- best hotels in <neighborhood>, <city>
- hotels near <city> National Park
africa4 destinations · 44 prompts
americas14 destinations · 154 prompts
Each destination is asked the 11 prompt patterns above (11 prompts × 14 cities = 154 prompts in this region).
asia16 destinations · 176 prompts
europe17 destinations · 187 prompts
oceania5 destinations · 55 prompts
Each destination is asked the 11 prompt patterns above (11 prompts × 5 cities = 55 prompts in this region).
Named hotels of the week — Copilot
Hotels Copilot talked about most this week, with week-over-week movement. Filtered to Copilot only — switch tabs to compare across models.
When Copilot hands out a hotel link, where does it go?
Every URL the AI returned for a named hotel, classified into direct (the hotel's own site), OTA (Booking / Expedia / …), chain page (marriott.com / hilton.com / …), or other. Chain folds into direct in the headline number because chain pages are still brand-controlled.
Where Copilot pulls hotel information from
Every URL Copilot retrieved classified into 12 buckets: OTAs, editorial, chain sites, direct hotel pages, social, meta-search, AI tools, community, government, directory consortia, and other.
Independent Hotel lottehotel.com 34% · qthotels.com 34% · electrahotels.gr 32% | 36.2% | 1,461 |
Chain marriott.com 45% · fourseasons.com 31% · hilton.com 24% | 33.0% | 1,332 |
Other fity.club 41% · theluxevoyager.com 29% · travoh.com 29% | 18.8% | 760 |
Editorial travelplusstyle.com 40% · forbestravelguide.com 33% · guide.michelin.com 27% | 3.7% | 150 |
Review Site tripadvisor.com 70% · tripadvisor.co.uk 22% · tripadvisor.ca 8% | 3.6% | 147 |
OTA & Aggregator booking.com 70% · agoda.com 20% · hotels.com 10% | 2.0% | 82 |
Community myboutiquehotel.com 59% · therooftopguide.com 30% · hotelierschoice.com 11% | 1.3% | 51 |
Hotel Directory auckland-hotels.co.nz 69% · slh.com 19% · designhotels.com 13% | 0.5% | 21 |
Social Channel pinterest.com 84% · uk.pinterest.com 11% · facebook.com 5% | 0.5% | 20 |
Government / DMO experiencegoldcoast.com 33% · maldives.com 33% · nyctourism.com 33% | 0.2% | 9 |
Meta-search hotelscombined.com 50% · kayak.com 25% · trivago.com 25% | 0.1% | 4 |
AI Tool wonderplan.ai 100% | 0.0% | 2 |
Top hotel parent groups by Copilot mentions
Each Copilot mention matched against Google Places, then rolled up to parent group (Marriott = Ritz-Carlton + Westin + Sheraton + EDITION + …, etc.). WoW delta vs last week. Detection via 175+ brand-domain rules.
| 1 | Wyndham | 7 → 16 | +129% |
| 2 | Peninsula | 7 → 16 | +129% |
| 3 | Mandarin Oriental | 17 → 37 | +118% |
| 4 | Shangri-La | 14 → 30 | +114% |
| 5 | Accor | 72 → 124 | +72% |
| 1 | Belmond | 17 → 7 | -59% |
| 2 | Taj | 16 → 12 | -25% |
| 3 | Minor | 31 → 24 | -23% |
| 4 | Meliá | 10 → 8 | -20% |
| 5 | Langham | 17 → 16 | -6% |
| # | Brand | Mentions | Hotels | W/W | |
|---|---|---|---|---|---|
| 1 | Marriott | 228 | 129 | ↑ 9.1% | |
| 2 | Accor | 124 | 72 | ↑ 72.2% | |
| 3 | Hilton | 99 | 55 | ↑ 15.1% | |
| 4 | Hyatt | 96 | 57 | ↑ 33.3% | |
| 5 | Four Seasons | 88 | 32 | ↑ 29.4% | |
| 6 | IHG | 76 | 45 | ↑ 13.4% | |
| 7 | Mandarin Oriental | 37 | 15 | ↑ 117.6% | |
| 8 | Shangri-La | 30 | 16 | ↑ 114.3% | |
| 9 | Radisson | 27 | 17 | ↓ 3.6% | |
| 10 | Minor | 24 | 16 | ↓ 22.6% | |
| 11 | Kempinski | 17 | 8 | ↑ 70.0% | |
| 12 | Wyndham | 16 | 12 | ↑ 128.6% | |
| 13 | Langham | 16 | 7 | ↓ 5.9% | |
| 14 | Peninsula | 16 | 8 | ↑ 128.6% | |
| 15 | Taj | 12 | 6 | ↓ 25.0% | |
| 16 | Rosewood | 9 | 6 | ↑ 28.6% | |
| 17 | Meliá | 8 | 5 | ↓ 20.0% | |
| 18 | Barceló | 8 | 4 | ↑ 300.0% | |
| 19 | Rocco Forte | 7 | 4 | ↑ 75.0% | |
| 20 | Belmond | 7 | 4 | ↓ 58.8% |
Of the hotels named this week: how many resolved to a chain (Marriott / Accor / …), an independent property, a vacation rental, or stayed unmatched.
What every metric means
Plain-English definitions for each number on this page. For deeper visuals + examples, see the annual landscape report linked at the bottom.
- Captures
- Number of AI responses we collected this week. Target = 616 per platform (one per prompt). Less when there are upstream errors.
- Web search
- Did the response trigger a live web fetch? Detected from the underlying response stream’s search-result events, not the unreliable top-level flag. We do NOT force web search — this is organic model behavior.
- Map widget
- Did the response render a hotel-card map (the Google-Maps-style widget ChatGPT shows for travel queries)? Each card is a "map entity" with its own provider.
- Sponsored placements
- Paid sponsor placements. Detected from real single-advertiser ad units in the response stream. Excludes ChatGPT’s organic shopping cards (which are unpaid product carousels). US/AU/NZ/CA only as of May 2026.
- Sources / response
- Distinct URLs the model consulted while answering — the URLs that show up in its retrieval log, regardless of whether it cited them inline. Computed only over web-search responses (otherwise the answer is from training data, no sources to count).
- Citations / response
- Subset of sources that the model rendered as inline footnote pills in the answer. A source becomes a citation when the model explicitly references it.
- Fanouts / response
- Number of sub-queries the model spun up internally to answer the prompt (e.g. "best hotels Paris" might fan out to "hotels Paris Marais", "luxury hotels Paris", "rooftop hotels Paris", …).
- Map entities / response
- Hotel cards inside the map widget. Each carries a provider (Google Places, TripAdvisor, Yelp, Foursquare, SERP) and a place ID where applicable.
- OTA
- Online travel agency (Booking, Expedia, Hotels.com, Agoda, Trip.com, Priceline, etc.) — commission-based booking sites.
- Direct
- A hotel’s own website. Computed at request time by matching the cited domain against Google Places.
- Chain
- A hotel chain’s brand website (hilton.com, marriott.com, ihg.com, …). 175+ chain-domain rules.
- Editorial
- Travel media (Condé Nast Traveler, Time Out, Lonely Planet, Forbes Travel Guide, NYT, etc.) and city-specific travel blogs (santorinidave.com, theurbanlist.com, etc.).
- Directory
- Multi-property hotel consortia / brand collectives (Small Luxury Hotels of the World, Design Hotels, Preferred Hotels, Virtuoso, …). Aggregate hotels under one umbrella but aren’t a single OTA.
- Review
- TripAdvisor, Oyster, Yelp, Trustpilot, Holidaycheck — review-first platforms.