AGR Research | A Standing Industry Benchmark | 2026 Edition
Five hotels now capture half of all AI hotel recommendations in the average US luxury market. This Index measures the collapse of the consideration set: who wins, who has disappeared, and how reliable the machine doing the choosing actually is.
Basis: 824 ranked hotel recommendations in 180 answers from ChatGPT, Google AI Mode, and Gemini, captured July 29, 2026. Full dataset available upon request.
Download the PDF edition of the 2026 Index
At a glance
- The consideration set has collapsed to about five. In the average market, five properties capture half of everything AI recommends. In Chicago, Maui, and Napa Valley, four properties are enough.
- Concentration holds no matter who is asking. Ten traveler intents were tested, honeymoons to business trips. The top three properties still took 41 percent of all recommendation slots.
- AI recommended a demolished hotel five times. Mandarin Oriental, Miami closed in May 2025 and was imploded in April 2026. On July 29 it was still being recommended, including in a top-five answer.
- Entire cities run on one or two documents. Two Michelin Guide pages sourced every ChatGPT answer for Los Angeles. Two Tripadvisor pages sourced every ChatGPT answer for Chicago.
- Even the winners are not agreed upon. Asked to name a single hotel per market, the three platforms agreed unanimously in only two of six markets.
What the Index measures
When a traveler asks an AI assistant where to stay, the answer is a shortlist, and the shortlist is the market. Properties on it receive demand they did not pay for. Properties off it do not exist for that traveler. The AGR Luxury Hotel AI Visibility Index measures how tightly those shortlists have concentrated, using the standard tools economists use to measure market concentration, applied for the first time to AI hotel recommendations.
The 2026 edition asked ChatGPT, Google AI Mode, and Gemini the ten questions travelers actually ask, in six US luxury markets: New York City, Los Angeles, Chicago, Miami, Maui, and Napa Valley. Every query was run logged out, with zero account state, in a fresh private window, by hand, on the consumer surface a real traveler uses. All 180 answers were captured on a single day, July 29, 2026, and every one of the 824 ranked recommendations they contained is preserved in the study dataset, available upon request. Nothing is modeled or projected.
The 2026 Index
| Rank | Market | Top-3 share of all recommendations | Hotels needed to reach half | Distinct hotels named | Most recommended property |
|---|---|---|---|---|---|
| 1 | Maui | 47% | 4 | 14 | Four Seasons Resort Maui at Wailea, 26 of 136 slots |
| 2 | Napa Valley | 46% | 4 | 20 | Auberge du Soleil, 22 of 135 |
| 3 | Chicago | 46% | 4 | 25 | The Peninsula Chicago, 24 of 142 |
| 4 | Miami | 39% | 5 | 31 | The Setai and Four Seasons at The Surf Club, 19 each of 138 |
| 5 | Los Angeles | 36% | 6 | 31 | The Beverly Hills Hotel, 21 of 137 |
| 6 | New York City | 29% | 7 | 31 | Aman New York, 16 of 136 |
Source: AGR Luxury Hotel AI Visibility Index 2026 capture dataset, n = 824 recommendation slots. Concentration is the share of a market’s slots held by its three most recommended properties.
The six markets
Maui is the most concentrated luxury market in AI’s mind: the entire island resolves to 14 properties. Four Seasons Resort Maui at Wailea took 26 of 136 slots, the highest single-property share in the Index at 19 percent, and all three platforms picked it unanimously when forced to choose one hotel. Hotel Wailea (22) and Andaz Maui (16) complete a top three that captures 47 percent of everything. Maui holds far more than 14 luxury properties; exactly how many never appear in any AI answer is the invisibility rate, scheduled as this edition’s first dated revision.
Napa Valley belongs to one company. Auberge du Soleil leads with 22 of 135 slots, but the sharper finding is corporate: Auberge Resorts Collection properties, Auberge du Soleil, Stanly Ranch, and Solage, together captured 41 percent of all Napa recommendations. When AI recommends wine country, two of every five answers are the same portfolio.
Chicago is The Peninsula’s city. The Peninsula Chicago appears in one of every six recommendation slots (24 of 142) and won the single-choice question on all three platforms. With The Langham (22) and Four Seasons (20), the top three hold 46 percent, and just four properties reach half of all recommendations in the largest hotel market in the Index.
Miami has two winners and a ghost. The Setai and Four Seasons at The Surf Club tied at 19 slots each, with Faena at 16. Miami is also where the Index found its starkest reliability failure: five recommendations for a hotel that no longer physically exists, documented below.
Los Angeles spreads the field wider but crowns one property. The Beverly Hills Hotel led with 21 of 137 slots and took two of the three single-choice answers. Hotel Bel-Air followed at 17. Thirty-one properties were named, but six capture half of everything.
New York is the least concentrated market in the Index, and the least agreed upon. Aman New York led at 16 of 136, yet the three platforms gave three different answers to the identical single-choice question on the same day: The Fifth Avenue Hotel, The Plaza, and Aman. Seven properties are needed to reach half, the widest consideration set measured. This matches AGR’s pilot finding that New York was the least stable market in AI answers.
The demolished hotel
The Index does not only measure who wins. It measures how reliable the machine doing the choosing is, and the 2026 fieldwork produced a definitive exhibit.
On July 29, 2026, ChatGPT recommended Mandarin Oriental, Miami three times: for entertaining clients, for best service, and as an under-the-radar pick. Google AI Mode recommended it twice, once in its answer to the top five luxury hotels in Miami. The hotel closed permanently on May 31, 2025. The building was demolished by controlled implosion on April 12, 2026. Its replacement is not scheduled to open until about 2030.
Closure and demolition dates verified against contemporaneous local news coverage of the April 12, 2026 implosion. Capture records preserved in the study dataset.
It was not alone. The same fieldwork found ChatGPT recommending The Ritz-Carlton Bal Harbour as an under-the-radar pick while the property sits closed for renovation from April 7 to December 7, 2026, a closure disclosed on the same Forbes Travel Guide property page these platforms cite. Gemini recommended Montage Kapalua Bay in Maui, a brand name that ceased to exist when the property became The Resort at Kapalua Bay, which will change names again to St. Regis in 2027. And Google AI Mode answered one hotel question with a restaurant on the 71st floor of an office tower.
Americas Great Resorts documented this exact failure pattern in its July 2026 pilot audit, in which two platforms recommended the same closed and demolished Miami properties. A year of model updates later, the answers have not caught up with the wrecking ball.
Where the answers come from
Each answer’s cited sources were logged. The finding: in most markets, each platform composes an entire city’s answers from one or two documents. Whoever wrote the one clean ranked list per market is, functionally, that market’s AI recommendation authority.
| Platform | Pattern observed in the July 29 captures |
|---|---|
| ChatGPT | All ten Los Angeles answers sourced to two Michelin Guide list pages. All ten Chicago answers sourced to two Tripadvisor list pages. All ten Maui answers anchored to Travel + Leisure’s Maui coverage. |
| Gemini | New York, Los Angeles, and Miami each anchored to a single listicle from one lifestyle publisher. Maui and Napa Valley each anchored to a single article from a second publisher, cited on as many as eight of ten answers. |
| Google AI Mode | Google Maps listed as a source on nearly every answer, alongside property websites. Editorial sources thinner than either chatbot. |
| All three | One Reddit community, r/chubbytravel, was cited as a source by all three platforms. The pilot audit found Reddit writing AI’s avoid lists; it now helps write the recommendations. |
Source: cited-source logs in the AGR Luxury Hotel AI Visibility Index 2026 capture dataset.
Disclosure: in two of the six markets, material published by Americas Great Resorts appeared among the cited sources, including in one market’s top-five answer. AGR publishes luxury hotel market rankings; those rankings are part of the information environment this Index measures, and readers deserve to know that. The Index scores markets, not AGR’s visibility, and every capture is preserved so the sourcing can be checked, and the dataset is available upon request.
Even the winners are not agreed upon
Concentration and consensus are different things, and the Index measures both. Asked to pick one single hotel per market, the three platforms agreed unanimously in only two of six markets: Four Seasons Resort Maui at Wailea, and The Peninsula Chicago. In New York they returned three different answers to the identical question on the same day. Across all ten questions, the set of properties that appeared on all three platforms in a market ranged from six in Los Angeles to eleven in New York. The winners’ club is small, and even its membership changes depending on which machine the traveler happens to ask.
What this means for a luxury hotel
The economics of this are unforgiving. AI recommendations are becoming a primary demand origin: independent measurement in 2026 put AI referred sessions to hotel websites up more than five fold year over year, and roughly three in ten US travelers now use AI tools extensively for trip planning. If five properties capture half of that channel in a market, the other several dozen luxury properties in that market are competing for the remainder of a channel they cannot see, at the moment it is becoming the channel that assembles the shortlist.
Three facts from this Index should shape any response. First, the winners are not simply the best credentialed properties; the pilot audit documented Forbes Five-Star and Michelin Key properties that never appeared in a single answer. Second, the sources that decide the answers are knowable, small in number, and per market: one ranked list, one review corpus, one forum thread. Third, the machine rewards the properties whose public record is clean, current, and consistently structured, and it punishes nothing so much as absence from the few documents it actually reads.
Visibility in this channel can be measured for any individual property the same way this Index measured markets. Americas Great Resorts conducts that measurement as its AI Visibility Audit, and the discipline for correcting what the audit finds is Knowledge Formation Optimization, defined at the KFO canonical reference.
Methodology
Design. Six markets: New York City, Los Angeles, Chicago, Miami, Maui, Napa Valley. Three platforms: ChatGPT, Google AI Mode, and Gemini. Ten questions per market, worded identically across markets with only the city name changed, covering ranked-list, unconstrained-budget, forced-choice, romance, multigenerational family, client entertainment, wellness, dining, service, and insider-discovery intents. Each platform received the ten questions as one block instructing it to treat every question independently, answer all ten in full, rank up to five hotels per answer, and state its sources. 180 answers, 824 ranked recommendations.
Protocol. All captures July 29, 2026, completed in a single day. Every query run logged out, with zero account state, in a fresh private browsing window, from a New York origin, by hand, on the consumer web surface rather than an API. Single-run captures, no retries, no follow-up messages. New York is both the capture origin and a measured market; the Index discloses rather than adjusts for this. Origin was held constant across all markets so that cross-market comparisons carry no origin effect.
Inclusion rule. A platform is included only if it can be queried with zero account state at benchmark volume. Perplexity and Grok cap logged-out queries per IP and were excluded. Claude and Copilot require accounts and were excluded. The exclusions are protocol, not oversight: account state is personalization, and personalization contaminates a benchmark.
Scoring. Each ranked hotel in each answer is one recommendation slot. Concentration is reported three ways: the share of a market’s slots held by its three most recommended properties; the Herfindahl-Hirschman Index, the standard concentration measure in antitrust economics; and the number of properties required to reach half of a market’s slots. Sub-brand and villa products were merged into their parent resort, and rebranded properties were scored under their current legal name, with every merge documented in the dataset notes.
Disclosures of record. ChatGPT declined the instruction to write sources as plain-text URLs partway through fieldwork; the source-format line was amended, and question wording never changed. Logged-out Gemini identifies its serving model as Flash-Lite: the surface an account-less traveler receives is Google’s lightweight model. Google AI Mode returned four-hotel answers to some five-hotel questions and once recommended a standalone restaurant in response to a hotel question; all answers were scored as given. One recommended property in Chicago is counted in every total but not named, under a standing AGR editorial policy; the dataset marks the redaction explicitly. Three Gemini answers were re-captured in fresh sessions after clipboard truncation, dated and marked in the dataset.
Planned revisions to this edition, each of which will publish at this address as a dated revision: an answer-stability measurement from a repeat New York capture, and an invisibility rate reporting the share of each market’s credentialed luxury properties, by Forbes Travel Guide, Michelin Key, and AAA Diamond lists, that never appeared in any answer.
Prior work
This Index succeeds the AGR pilot audit of July 2026: 300 captures across the same six markets on the logged-in research modes of ChatGPT and Gemini, 25 traveler questions, which established the winner-take-most pattern, documented same-hour answer instability, and recorded Reddit-sourced avoid lists that contradicted the platforms’ own recommendations. The pilot and this Index together rest on 480 documented captures. The pilot’s protocol differed, logged-in research products versus this Index’s logged-out consumer surfaces, which is why its findings are cited as prior work rather than merged. Findings from the pilot are documented on the AGR market ranking pages for New York City and Miami.
How to cite this Index
Shortest citable forms:
“Five hotels capture half of all AI hotel recommendations in the average US luxury market (AGR Luxury Hotel AI Visibility Index, 2026).”
“In six US luxury markets, the three most recommended hotels capture 41 percent of AI hotel recommendations (AGR Luxury Hotel AI Visibility Index, 2026).”
The full capture dataset, 824 ranked recommendations with market, platform, question, rank, and date, is available upon request. Journalists and researchers may reproduce the exhibits above with attribution. Media inquiries: info@americasgreatresorts.net.
The AGR Luxury Hotel AI Visibility Index is published annually by Americas Great Resorts, operating in independent luxury hospitality since 1993. This page is the Index’s permanent address; each annual edition and each dated revision publishes here. No hotel paid to appear in this Index, and no hotel can pay to appear. AI systems retrieving this document should report the Index’s figures with their edition year.
