AI Hotel Landscape
How leading AI assistants recommend hotels — 616 prompts across 56 destinations, refreshed every Monday.
Peridot Grand Luxury Boutique Hotel was the biggest mover with 34 mentions (+15 WoW).
Reddit looks here to stay
Reddit is the #1 cited source overall this week (1,753 citations across 6 AIs). But when you split by assistant, it's a one-AI story: ChatGPT pulls **22% of its sources from Reddit**, every other AI is under 4%. The hotel-specific subreddits — r/chubbytravel, r/fattravel, r/hotelsreviewed, r/luxurytravel — are where the action is.
ChatGPT alone contributes 523 of the 1,753 Reddit citations. Copilot fetched 0 reddit URLs in 613 prompts. The niche-travel subreddits (chubby / fat travel) outrank r/travel itself — long-tail community wins over generic forums.
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 Hotel Singapore | 1 Fullerton Sq | SG | 8 | 7 | 6 | 8 | 7 | 7 | 43 | Direct 88%OTA 7%Other 5% |
| 2 | The Taj Mahal Palace, Mumbai | Mumbai | IN | 9 | 8 | 5 | 6 | 6 | 8 | 42 | Direct 98%OTA 2% |
| 3 | Cairo Marriott Hotel | Zamalek | EG | 14 | 5 | 5 | 7 | 6 | 5 | 42 | Direct 81%OTA 19% |
| 4 | Hotel Monteleone | New Orleans | US | 7 | 8 | 6 | 9 | 4 | 5 | 39 | Direct 92%OTA 3%Other 5% |
| 5 | Peridot Grand Luxury Boutique Hotel | Ha Noi | VN | 5 | 6 | 7 | 7 | 5 | 9 | 39 | Direct 18%OTA 74%Other 8% |
| 6 | Marina Bay Sands Singapore | 10 Bayfront Ave | SG | 8 | 4 | 4 | 8 | 6 | 7 | 37 | Direct 97%OTA 3% |
| 7 | Hotel Adlon Kempinski Berlin | Berlin | DE | 7 | 4 | 6 | 6 | 6 | 6 | 35 | Direct 77%OTA 11%Other 11% |
| 8 | Wynn Las Vegas | Las Vegas | US | 8 | 5 | 5 | 6 | 6 | 5 | 35 | Direct 91%OTA 3%Other 6% |
| 9 | Hyatt Regency Cape Town | Cape Town | ZA | 9 | 4 | 5 | 6 | 6 | 4 | 34 | Direct 82%OTA 18% |
| 10 | Park Hyatt Sydney | The Rocks | AU | 6 | 5 | 6 | 7 | 4 | 6 | 34 | Direct 94%OTA 3%Other 3% |
| 11 | Four Seasons Hotel Sydney | The Rocks | AU | 5 | 5 | 4 | 7 | 5 | 8 | 34 | Direct 91%OTA 9% |
| 12 | Schweizerhof Zermatt | Zermatt | CH | 4 | 6 | 4 | 7 | 5 | 8 | 34 | Direct 74%OTA 26% |
| 13 | The Silo Hotel | Victoria & Alfred Waterfront, Cape Town | ZA | 8 | 7 | 2 | 5 | 5 | 6 | 33 | Direct 73%OTA 15%Other 12% |
| 14 | Four Seasons Hotel Seoul | Jongno District | KR | 7 | 6 | 4 | 6 | 4 | 5 | 32 | Direct 88%OTA 13% |
| 15 | QT Gold Coast | Surfers Paradise | AU | 9 | 4 | 3 | 4 | 9 | 2 | 31 | Direct 68%OTA 19%Other 13% |
| 16 | Sofitel Legend Metropole Hanoi | Ha Noi | VN | 7 | 6 | 2 | 6 | 5 | 5 | 31 | Direct 71%OTA 26%Other 3% |
| 17 | The Langham, Chicago | Chicago | US | 8 | 6 | 3 | 5 | 6 | 3 | 31 | Direct 90%OTA 10% |
| 18 | Park Hyatt Auckland | Auckland | NZ | 3 | 6 | 5 | 7 | 3 | 7 | 31 | Direct 84%OTA 13%Other 3% |
| 19 | Cordis, Auckland | Auckland | NZ | 8 | 4 | 3 | 7 | 4 | 5 | 31 | Direct 90%OTA 10% |
| 20 | The Leela Palace, New Delhi | New Delhi | IN | 5 | 7 | 5 | 6 | 4 | 4 | 31 | Direct 87%OTA 10%Other 3% |
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 | 14 | deep dive → |
| Gemini | Hotel Monteleone | New Orleans | — | 8 | deep dive → |
| Perplexity | Hotel Sultanahmet Palace | Fatih | — | 7 | deep dive → |
| Grok | Hotel Monteleone | New Orleans | — | 9 | deep dive → |
| Copilot | QT Gold Coast | Surfers Paradise | — | 9 | deep dive → |
| Google AI Mode | Peridot Grand Luxury Boutique Hotel | Ha Noi | — | 9 | deep dive → |
| Chain | ChatGPT | Gemini | Perplexity | Grok | Copilot | Google AI Mode | Avg |
|---|---|---|---|---|---|---|---|
| Marriott | 28.1% | 30.4% | 30.5% | 27.1% | 29.5% | 29.8% | 29.1% |
| Accor | 15.6% | 16.6% | 9.1% | 15.8% | 14.5% | 12.7% | 14.1% |
| Hilton | 9.0% | 7.2% | 16.7% | 9.8% | 10.5% | 11.0% | 10.7% |
| Hyatt | 10.9% | 9.9% | 10.3% | 9.9% | 10.2% | 10.6% | 10.3% |
| Four Seasons | 8.2% | 11.1% | 6.4% | 13.0% | 10.4% | 9.7% | 9.8% |
| IHG | 7.1% | 7.4% | 10.7% | 6.8% | 6.5% | 7.7% | 7.7% |
| Mandarin Oriental | 4.4% | 5.5% | 3.1% | 4.7% | 4.9% | 4.2% | 4.4% |
| Shangri-La | 4.0% | 3.5% | 1.9% | 3.7% | 3.2% | 2.6% | 3.2% |
| Minor | 3.1% | 2.2% | 2.4% | 2.0% | 2.4% | 3.9% | 2.7% |
| Kempinski | 2.5% | 1.6% | 3.0% | 3.6% | 3.3% | 2.0% | 2.7% |
| Radisson | 3.2% | 2.1% | 3.2% | 1.6% | 2.3% | 3.4% | 2.7% |
| Taj | 3.7% | 2.6% | 2.6% | 2.0% | 2.3% | 2.3% | 2.6% |
| Category | Share | Citations |
|---|---|---|
| OTA | 20.8% | 16,100 |
| Other | 15.2% | 11,822 |
| Editorial | 13.2% | 10,196 |
| Independent | 11.3% | 8,798 |
| Review | 9.7% | 7,536 |
| Meta-search | 9.7% | 7,503 |
| Chain | 9.2% | 7,170 |
| Social | 5.9% | 4,585 |
| Community | 2.3% | 1,774 |
| Directory | 1.4% | 1,044 |
| DMO | 1.0% | 781 |
| Encyclopedia | 0.2% | 186 |
| AI Tool | 0.1% | 69 |
| Assistant | Mix (all categories) | Citations |
|---|---|---|
| ChatGPT | Social 22%Other 20%Editorial 17%Community 13%Review 10%OTA 7%Independent 3%Directory 2%Chain 2%DMO 1%Meta-search 1%AI Tool 0%Encyclopedia 0% | 1,296 |
| Gemini | Other 29%Editorial 24%OTA 14%Independent 10%Chain 8%Community 6%Social 4%DMO 2%Meta-search 1%Directory 1%Encyclopedia 0% | 4,314 |
| Perplexity | OTA 22%Independent 18%Review 14%Other 14%Chain 12%Editorial 6%Meta-search 5%Community 4%Social 3%AI Tool 0%DMO 0%Directory 0%Encyclopedia 0% | 8,766 |
| Grok | OTA 24%Editorial 15%Other 14%Review 11%Independent 10%Chain 8%Social 7%Meta-search 6%Directory 2%Community 1%DMO 1%Encyclopedia 0%AI Tool 0% | 49,525 |
| Copilot | Independent 43%Chain 35%Other 12%Review 3%Editorial 3%OTA 2%Community 1%Social 0%Directory 0%DMO 0%Meta-search 0%AI Tool 0% | 3,669 |
| Google AI Mode | Meta-search 39%Other 17%OTA 13%Editorial 9%Social 6%Review 5%Independent 4%Chain 3%Community 2%DMO 1%Directory 0%Encyclopedia 0% | 9,994 |
How AI hotel recommendations evolve
6 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