AI Hotel Landscape
How leading AI assistants recommend hotels — 616 prompts across 56 destinations, refreshed every Monday.
Conrad Maldives Rangali Island was the biggest mover with 12 mentions (+11 WoW). 3 hotels appeared in the top 200 for the first time.
ChatGPT names twice as many hotels as the next AI
For the same 616 prompts across 56 cities this week, ChatGPT mentioned **3,741 distinct hotels** by name — twice the next AI. Google AI Mode named about half (1,917), but cited **10 URLs per hotel** to back them. Two strategies coexist: breadth (ChatGPT) and source-density (AI Mode, Perplexity).
Same 616 prompts asked of every AI. ChatGPT's 2-step answer pattern gives it room to enumerate more hotels; AI Mode and Perplexity allocate more URLs per hotel — fewer recommendations, deeper sourcing.
The 616 prompts we ask 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
Hotels worth calling out individually. Computed across all 6 AI assistants — when a hotel ranks high here it's mentioned by multiple models, not just one.
Most-mentioned hotel across all 616 prompts this week, blended across every AI assistant.
Wasn't on the radar last week. Now it is.
High-confidence cross-city detection lands with the May 18 run. We'll surface only mentions where the AI-named hotel exists in a different city than the prompt asked about — clean signal, no false positives from address formatting.
| # | Hotel | City | Country | ChatGPT | Gemini | Perplexity | Grok(discontinued) | Copilot | Google AI Mode | Total | Link mix |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | The Fullerton Bay Hotel Singapore | 80 Collyer Quay | SG | 10 | 6 | 7 | — | 8 | 6 | 37 | Direct 84%Other 16% |
| 2 | The Taj Mahal Palace, Mumbai | Mumbai | IN | 5 | 7 | 3 | — | 8 | 8 | 31 | Direct 81%OTA 13%Other 6% |
| 3 | Hyatt Regency Cape Town | Cape Town | ZA | 9 | 2 | 6 | — | 8 | 5 | 30 | Direct 80%OTA 10%Other 10% |
| 4 | QT Gold Coast | Surfers Paradise | AU | 8 | 4 | 3 | — | 8 | 7 | 30 | Direct 63%OTA 13%Other 23% |
| 5 | The Langham Gold Coast | Surfers Paradise | AU | 8 | 5 | 3 | — | 6 | 7 | 29 | Direct 90%OTA 3%Other 7% |
| 6 | Hotel Monteleone | New Orleans | US | 5 | 6 | 4 | — | 4 | 9 | 28 | Direct 79%Other 21% |
| 7 | JW Marriott Gold Coast Resort & Spa | Surfers Paradise | AU | 8 | 5 | 4 | — | 5 | 6 | 28 | Direct 89%OTA 4%Other 7% |
| 8 | Marina Bay Sands Singapore | 10 Bayfront Ave | SG | 5 | 4 | 6 | — | 6 | 7 | 28 | Direct 89%OTA 4%Other 7% |
| 9 | Cairo Marriott Hotel | Zamalek | EG | 10 | 5 | 1 | — | 4 | 8 | 28 | Direct 68%OTA 7%Other 25% |
| 10 | Sofitel Legend Metropole Hanoi | Ha Noi | VN | 8 | 5 | 1 | — | 7 | 6 | 27 | Direct 81%OTA 4%Other 15% |
| 11 | Hotel Adlon Kempinski Berlin | Berlin | DE | 8 | 4 | 1 | — | 7 | 7 | 27 | Direct 74%OTA 7%Other 19% |
| 12 | Cordis, Auckland | Auckland | NZ | 7 | 4 | 6 | — | 6 | 3 | 26 | Direct 88%Other 12% |
| 13 | The Silo Hotel | Victoria & Alfred Waterfront, Cape Town | ZA | 7 | 5 | 4 | — | 3 | 7 | 26 | Direct 77%Other 23% |
| 14 | Park Hyatt Auckland | Auckland | NZ | 9 | 4 | 2 | — | 6 | 5 | 26 | Direct 77%OTA 4%Other 19% |
| 15 | Katikies Santorini - Pelagos House | Oia | GR | 5 | 6 | 2 | — | 6 | 7 | 26 | Direct 69%OTA 4%Other 27% |
| 16 | The Oberoi, Mumbai | Mumbai | IN | 5 | 5 | 3 | — | 7 | 5 | 25 | Direct 84%OTA 12%Other 4% |
| 17 | The Cosmopolitan of Las Vegas | Las Vegas | US | 4 | 8 | 3 | — | 3 | 7 | 25 | Direct 80%OTA 4%Other 16% |
| 18 | Grand Hotel Zermatterhof | Zermatt | CH | 5 | 5 | 6 | — | 3 | 5 | 24 | Direct 79%Other 21% |
| 19 | Grace Hotel, Auberge Collection | Imerovigli | GR | 5 | 4 | 4 | — | 5 | 6 | 24 | Direct 63%OTA 8%Other 29% |
| 20 | Sofitel Auckland Viaduct Harbour | Auckland | NZ | 6 | 3 | 8 | — | 5 | 2 | 24 | Direct 54%Other 46% |
Link mix over time — top hotels
Where each AI sent users in recent weeks: direct site, OTA, chain page, or other.Direct vs OTA — who controls the link?
When an AI hands a user a hotel link, does it send them to the brand (own site or chain page) or to an OTA reseller? Bars fold chain into direct.How the 6 AI assistants compare
Same prompts, same week — different answers. Each model's top hotel, brand mix, and source preferences side by side.
| Assistant | Top hotel | City | Chain | Mentions | |
|---|---|---|---|---|---|
| ChatGPT | Cairo Marriott Hotel | Zamalek | Marriott | 10 | deep dive → |
| Gemini | The Cosmopolitan of Las Vegas | Las Vegas | — | 8 | deep dive → |
| Perplexity | Sofitel Auckland Viaduct Harbour | Auckland | Accor | 8 | deep dive → |
| Grok(discontinued) | — | — | — | 0 | deep dive → |
| Copilot | Four Seasons Hotel Sydney | The Rocks | Four Seasons | 8 | deep dive → |
| Google AI Mode | Hotel Monteleone | New Orleans | — | 9 | deep dive → |
| Chain | ChatGPT | Gemini | Perplexity | Grok(discontinued) | Copilot | Google AI Mode | Avg |
|---|---|---|---|---|---|---|---|
| Marriott | 29.5% | 32.2% | 29.7% | — | 29.9% | 28.6% | 29.9% |
| Accor | 12.7% | 17.8% | 10.3% | — | 14.6% | 13.6% | 13.8% |
| Hyatt | 10.9% | 8.9% | 11.6% | — | 10.2% | 11.6% | 10.6% |
| Hilton | 11.8% | 6.9% | 13.5% | — | 8.6% | 8.7% | 9.9% |
| Four Seasons | 8.9% | 11.8% | 7.0% | — | 8.9% | 12.4% | 9.8% |
| IHG | 8.5% | 7.9% | 10.5% | — | 7.7% | 6.8% | 8.2% |
| Mandarin Oriental | 4.0% | 3.8% | 3.0% | — | 4.7% | 4.2% | 4.0% |
| Shangri-La | 3.8% | 2.4% | 2.2% | — | 3.3% | 3.1% | 3.1% |
| Minor | 2.8% | 1.3% | 3.7% | — | 3.2% | 2.9% | 2.8% |
| Radisson | 1.9% | 2.3% | 4.5% | — | 2.6% | 2.7% | 2.7% |
| Langham | 2.2% | 2.7% | 2.1% | — | 3.3% | 3.1% | 2.7% |
| Peninsula | 3.0% | 2.2% | 1.9% | — | 2.9% | 2.4% | 2.5% |
| Category | Share | Citations |
|---|---|---|
| Other | 18.2% | 7,652 |
| Meta-search | 15.6% | 13,025 |
| Independent | 15.4% | 5,590 |
| OTA | 13.3% | 6,395 |
| Chain | 12.9% | 4,345 |
| Editorial | 9.1% | 3,182 |
| Review | 6.4% | 2,799 |
| Community | 4.6% | 1,860 |
| Social | 1.8% | 741 |
| Directory | 1.3% | 472 |
| DMO | 1.0% | 497 |
| AI Tool | 0.3% | 131 |
| Encyclopedia | 0.1% | 33 |
| Assistant | Mix (all categories) | Citations |
|---|---|---|
| ChatGPT | Other 24%Independent 19%Chain 15%OTA 10%Editorial 9%Review 7%Community 7%DMO 2%Social 2%Meta-search 2%Directory 2%AI Tool 1%Encyclopedia 0% | 13,627 |
| Gemini | Other 25%Editorial 25%OTA 16%Independent 8%Chain 8%Community 7%Social 4%Directory 3%DMO 2%Meta-search 1%Review 0%AI Tool 0% | 4,014 |
| Perplexity | OTA 24%Independent 18%Review 18%Chain 13%Other 11%Community 5%Meta-search 4%Editorial 4%Social 1%Directory 1%AI Tool 0%DMO 0% | 8,741 |
| Grok(discontinued) | no citations captured | 0 |
| Copilot | Independent 30%Chain 29%Other 20%Review 6%Editorial 5%OTA 4%Community 3%Directory 1%Social 1%DMO 0%Meta-search 0%AI Tool 0%Encyclopedia 0% | 2,668 |
| Google AI Mode | Meta-search 69%OTA 12%Other 11%Editorial 2%Independent 2%Chain 1%Social 1%Community 1%Review 0%DMO 0%Directory 0%AI Tool 0%Encyclopedia 0% | 17,672 |
How AI hotel recommendations evolve
13 weeks of history. Lines aggregate across all 6 AI assistants.
Need a specific week's snapshot? Pick one from the weekly archive.
What's tracked + what's coming
The dashboard launches with ChatGPT. Five more models follow on the same cadence, plus deeper analysis on top.
- ✓ChatGPT — live now, 2,300+ captures every Monday across 56 destinations and 37 countries.
- ✓616 hotel-search prompts per platform per week — 11 question patterns × 56 cities (luxury, family, romantic, design, neighborhood, landmark, …).
- ✓Source mix — every URL ChatGPT cites is bucketed into OTA, editorial, chain site, direct hotel page, review, social, meta-search, AI tool, community, government, or directory.
- ✓Brand share — top hotel chains by mentions, week-over-week deltas.
- ✓Map widget — chain vs independent split, and where the map data comes from (Google Places, Yelp, TripAdvisor, …).
- ✓Sponsored placements — paid ad slots tracked separately from organic recommendations.
- Five more AI assistants
Gemini, Perplexity, Grok, Copilot, and Google AI Mode are already being scraped on the same weekly cadence. Their dashboards unlock as we validate the data — same depth as the ChatGPT view, plus side-by-side comparisons.
- AI Consistency Score
How stable is a hotel's ranking across the week, across queries, and across models? A single number per property that brand teams can track over time.
- Hotel of the Week + Hallucination of the Week
Recurring stories from the data: the property AI is currently obsessed with, and the funniest mistake it made (e.g. a hotel returned for the wrong city).
- Per-destination drilldown
Click any city to see exactly which hotels each AI recommends, which sources it cites, and how those choices have shifted week over week.
- Multi-week trend lines
Charts on every metric so you can see whether OTAs are gaining ground, which chains are climbing, and where ad density is heading.
How this dashboard is built
Full transparency on data collection.
What "mention" means
Hotel mention = a real-world hotel property that the AI named in its answer, after we matched the name against Google Places. A hotel mentioned multiple times in the same answer counts once.
Parent group mention = a hotel mention rolled up to its parent group via the chain taxonomy. A stay at the Ritz-Carlton counts toward Marriott; a stay at Sofitel counts toward Accor.
Citation / source = a URL the AI fetched from the web during the answer. Tracked separately from mentions. The Source mix charts answer "where does the AI get its information," not "which hotels does it recommend."
Link = the URL the AI gave specifically for a recommended hotel (its booking link). Classified as direct (hotel-owned), OTA (Booking, Expedia, …), chain page (Marriott.com, Hilton.com, …), or other.
Prompts. 616 hotel-search prompts, 56 destinations × 11 templates (e.g. "best hotels in Paris", "family friendly hotels in Cancún", "hotels near Big Ben").
Web search is NOT forced. We measure organic behavior. The web-search rate displayed here is derived from the underlying response stream's search markers, not the unreliable top-level flag.
Hotel matching. Each named hotel mention is matched against Google Places to resolve it to a real property (with address, website, and chain when applicable). The "Direct" source bucket is computed at request time against the same data.
Country. US proxy. As of May 2026, OpenAI's paid sponsor placements are rolling out in the US, Australia, New Zealand, and Canada — the test pool may expand. Geo coverage on this dashboard expanding to match.
Data is directional. Some prompts retry due to upstream variance; absolute counts can shift ±5% week to week. Trends are honest; single-week spot reads should be taken with that grain of salt.
Refresh. Cron runs every Monday at 02:00 UTC. Page revalidates hourly.
Want a deeper read? See the in-depth annual report