AI Hotel Landscape
How leading AI assistants recommend hotels — 616 prompts across 56 destinations, refreshed every Monday.
NIZUC Resort & Spa was the biggest mover with 15 mentions (+14 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.
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 | Copilot | Google AI Mode | Total | Link mix |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | The Fullerton Bay Hotel Singapore | 80 Collyer Quay | SG | 11 | 6 | 5 | — | 7 | 9 | 38 | Direct 79%OTA 8%Other 13% |
| 2 | Marina Bay Sands Singapore | 10 Bayfront Ave | SG | 7 | 6 | 5 | — | 7 | 9 | 34 | Direct 82%Other 18% |
| 3 | The Taj Mahal Palace, Mumbai | Mumbai | IN | 7 | 8 | 4 | — | 6 | 6 | 31 | Direct 87%OTA 6%Other 6% |
| 4 | The Langham, Chicago | Chicago | US | 7 | 5 | 5 | — | 7 | 6 | 30 | Direct 77%OTA 3%Other 20% |
| 5 | Hotel Monteleone | New Orleans | US | 7 | 6 | 3 | — | 4 | 8 | 28 | Direct 71%OTA 4%Other 25% |
| 6 | The Langham Gold Coast | Surfers Paradise | AU | 6 | 7 | 3 | — | 5 | 7 | 28 | Direct 89%Other 11% |
| 7 | Four Seasons Hotel Istanbul At The Bosphorus | Beşiktaş | TR | 8 | 6 | 1 | — | 6 | 6 | 27 | Direct 74%OTA 15%Other 11% |
| 8 | Hotel Adlon Kempinski Berlin | Berlin | DE | 6 | 5 | 5 | — | 5 | 6 | 27 | Direct 78%OTA 4%Other 19% |
| 9 | The Silo Hotel | Victoria & Alfred Waterfront, Cape Town | ZA | 7 | 6 | 2 | — | 5 | 6 | 26 | Direct 69%OTA 4%Other 27% |
| 10 | QT Gold Coast | Surfers Paradise | AU | 6 | 3 | 7 | — | 5 | 5 | 26 | Direct 69%OTA 4%Other 27% |
| 11 | Mont Cervin Palace | Zermatt | CH | 6 | 7 | 2 | — | 5 | 6 | 26 | Direct 85%OTA 4%Other 12% |
| 12 | The Cosmopolitan of Las Vegas | Las Vegas | US | 6 | 7 | 3 | — | 3 | 5 | 24 | Direct 92%Other 8% |
| 13 | THE OMNIA | Zermatt | CH | 7 | 5 | 4 | — | 4 | 4 | 24 | Direct 83%Other 17% |
| 14 | The Oberoi, Mumbai | Mumbai | IN | 6 | 4 | 3 | — | 5 | 6 | 24 | Direct 79%OTA 4%Other 17% |
| 15 | Park Hyatt Sydney | The Rocks | AU | 7 | 6 | 2 | — | 4 | 5 | 24 | Direct 75%Other 25% |
| 16 | Palacio Duhau - Park Hyatt Buenos Aires | Buenos Aires | AR | 6 | 5 | 2 | — | 4 | 6 | 23 | Direct 87%Other 13% |
| 17 | The Rees Hotel, Luxury Apartments & Lakeside Residences | Queenstown | NZ | 4 | 3 | 5 | — | 6 | 5 | 23 | Direct 87%OTA 9%Other 4% |
| 18 | The Peninsula Beijing | Dongcheng | CN | 6 | 4 | — | — | 7 | 6 | 23 | Direct 83%OTA 4%Other 13% |
| 19 | Four Seasons Hotel Buenos Aires | Buenos Aires | AR | 3 | 6 | 3 | — | 5 | 6 | 23 | Direct 87%Other 13% |
| 20 | Park Hyatt Auckland | Auckland | NZ | 8 | 4 | 2 | — | 4 | 5 | 23 | Direct 87%Other 13% |
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 | The Fullerton Bay Hotel Singapore | 80 Collyer Quay | — | 11 | deep dive → |
| Gemini | The Taj Mahal Palace, Mumbai | Mumbai | Taj | 8 | deep dive → |
| Perplexity | QT Gold Coast | Surfers Paradise | — | 7 | deep dive → |
| Grok | — | — | — | 0 | deep dive → |
| Copilot | Marina Bay Sands Singapore | 10 Bayfront Ave | — | 7 | deep dive → |
| Google AI Mode | Marina Bay Sands Singapore | 10 Bayfront Ave | — | 9 | deep dive → |
| Chain | ChatGPT | Gemini | Perplexity | Grok | Copilot | Google AI Mode | Avg |
|---|---|---|---|---|---|---|---|
| Marriott | 29.2% | 32.3% | 27.9% | — | 28.3% | 27.4% | 29.0% |
| Accor | 14.0% | 15.4% | 13.2% | — | 13.2% | 14.1% | 14.0% |
| Hyatt | 12.7% | 9.4% | 11.1% | — | 9.8% | 10.5% | 10.8% |
| Four Seasons | 8.4% | 12.2% | 7.8% | — | 10.5% | 12.0% | 10.2% |
| Hilton | 10.9% | 6.7% | 11.7% | — | 11.8% | 9.0% | 10.0% |
| IHG | 7.4% | 8.2% | 10.6% | — | 7.0% | 6.6% | 7.7% |
| Mandarin Oriental | 4.4% | 3.7% | 3.4% | — | 4.1% | 4.0% | 4.0% |
| Langham | 2.3% | 3.0% | 3.1% | — | 3.5% | 3.8% | 3.1% |
| Shangri-La | 3.0% | 2.4% | 2.0% | — | 3.7% | 3.6% | 3.0% |
| Radisson | 2.8% | 1.9% | 4.6% | — | 2.8% | 2.8% | 2.9% |
| Peninsula | 2.0% | 2.6% | 2.0% | — | 3.4% | 3.1% | 2.6% |
| Minor | 2.7% | 2.2% | 2.6% | — | 2.1% | 3.2% | 2.6% |
| Category | Share | Citations |
|---|---|---|
| Other | 18.1% | 6,606 |
| Meta-search | 15.9% | 12,757 |
| OTA | 14.3% | 5,911 |
| Independent | 14.0% | 3,357 |
| Chain | 13.4% | 3,211 |
| Review | 9.4% | 2,983 |
| Editorial | 7.0% | 2,332 |
| Community | 4.4% | 1,515 |
| Social | 2.1% | 765 |
| DMO | 1.5% | 626 |
| Directory | 1.3% | 477 |
| AI Tool | 0.7% | 164 |
| Encyclopedia | 0.1% | 36 |
| Assistant | Mix (all categories) | Citations |
|---|---|---|
| ChatGPT | Other 26%Chain 12%OTA 12%Editorial 11%Independent 10%Review 10%Community 7%DMO 4%Directory 3%Social 2%Meta-search 2%AI Tool 1%Encyclopedia 0% | 12,162 |
| Gemini | Other 21%Chain 18%Independent 16%OTA 16%Editorial 13%Community 6%Social 3%Meta-search 3%DMO 2%Directory 2%Encyclopedia 0%AI Tool 0% | 877 |
| Perplexity | OTA 28%Review 21%Other 12%Independent 10%Chain 7%Community 6%Editorial 5%Meta-search 5%Social 3%Directory 1%AI Tool 1%DMO 0%Encyclopedia 0% | 7,351 |
| Grok | no citations captured | 0 |
| Copilot | Independent 32%Chain 28%Other 21%Review 7%Editorial 4%OTA 4%Community 2%Social 1%Directory 0%DMO 0%Meta-search 0%Encyclopedia 0% | 2,916 |
| Google AI Mode | Meta-search 70%OTA 13%Other 10%Editorial 2%Independent 2%Social 1%Chain 1%Community 1%Review 0%DMO 0%Directory 0%Encyclopedia 0% | 17,434 |
How AI hotel recommendations evolve
10 weeks of history. Lines aggregate across all 6 AI assistants.
Need a specific week's snapshot? Pick one from the weekly archive.
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).
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