We Analyzed AI Visibility Across 55 Travel and Hospitality Brands. Here's What We Found.

Travel is one of the highest-intent categories in AI search. People don't ask ChatGPT or Claude about hotels out of curiosity. They ask because they're booking a honeymoon, planning a family trip to Orlando, or trying to figure out which car rental company won't nickel-and-dime them at the counter. These are bottom-of-funnel questions with real money attached, and they're happening constantly.

We ran GEO reports across 55 travel and hospitality brands: hotel chains, luxury hospitality groups, online travel agencies, car rental companies, cruise lines, theme parks and attractions, tour operators, and vacation rental platforms. Each report tracked 20 to 25 queries across 7 AI providers (OpenAI, Anthropic, Perplexity, Google Gemini, Grok, Microsoft Copilot, and Google AI Mode), producing 140 searches per brand and over 7,700 data points in aggregate.

The pattern that emerged is straightforward to state and harder to fix: AI models are comfortable naming travel brands. They're much less comfortable linking to them.

Across 55 brands, the average brand mention rate was 43.3% and the average URL citation rate was 15.8%. That's a 27.5-point gap between being named in an AI answer and being linked to as the source.

That average hides how lopsided this gets at the extremes. The widest individual gap in the dataset came from a major car rental brand: a 76% mention rate against a 0% citation rate. A leading theme park resort posted a nearly identical story, 71% mention and 0% citation. Several other category leaders, spanning car rental, casino resorts, cruise lines, and theme parks, posted gaps above 50 points. The single highest raw mention rate we recorded anywhere in the dataset, 84%, still only converted to a 24% citation rate.

The through-line: the brands most people would call “the biggest name in the category” are often the ones with the least to show for it in citations.

Four brands in this dataset posted a 0% URL citation rate. Not low. Zero. Across 140 tracked searches each, not one produced a citation back to the brand's own domain, despite mention rates ranging from 16% up to 76%.

One of them is worth a closer look because it shows the gap isn't always a content problem. In one case, the brand's own domain was actually the single most-cited domain across its entire report, ahead of Tripadvisor and Forbes. But its official citation rate still came back at 0%, because the canonical URL on the analyzed page pointed to a mismatched internal URL (a corporate press page) instead of the consumer-facing page AI models were actually referencing. The content is working. The plumbing underneath it is broken.

A second case looks more like a pure authority problem than a technical one. A major theme park resort, one of the most recognized leisure brands in the world, is losing nearly all of its discovery and trip-planning citations to independent third-party travel-planning sites. When a brand is already the “gold standard” in a category, AI models seem comfortable naming it without feeling any obligation to link to it. Familiarity breeds citation laziness.

Every vertical we analyzed has its own dominant third-party citation source, and the consistency within each vertical is the notable part.

Cruise lines: cruisecritic.com, branded in AI citations as “The Independent Traveler,” was the single most-cited domain in 6 of the 7 cruise line reports we ran. The one exception was a brand whose own domain topped its own report, and which also showed up as a top-cited source in three of its competitors' reports. That's rare in this dataset: a brand earning real citation authority even when a rival is the one being searched for.

Hotels: Tripadvisor was the top or second-most-cited domain across nearly every major hotel chain report we ran. Forbes and Forbes Travel Guide showed up consistently in the luxury tier.

Luxury hospitality: Forbes and Architectural Digest dominate citations for the ultra-luxury brands in our sample, playing the same “editorial validation” role that Michelin plays specifically for high-end culinary hospitality.

OTAs and metasearch: Reddit shows up constantly as a cited source, which says something about how much AI models now trust crowdsourced travel advice over brand marketing copy.

The through-line: whichever aggregator has built the most structured, comparison-friendly content in a given travel category becomes the default citation, regardless of how much a brand spends on its own content.

This is the most distinctive pattern in the dataset, and it's specific to one category.

Across all 7 car rental reports we ran, the top cited domains were overwhelmingly other car rental companies' own websites, not independent third parties. It was common to see a rental brand's top three cited sources made up almost entirely of its direct competitors' domains, with no independent review site or aggregator in the mix at all.

In every other vertical we studied, the citation competition is between a brand's own domain and independent third parties: review sites, editorial publishers, aggregators. In car rental, the competition is brand versus brand. AI models seem to treat the major rental companies as interchangeable reference points for each other, which means a generic query about “best car rental company” is likely to surface a citation to one of your two biggest competitors before it surfaces you. Winning this category isn't about beating Tripadvisor. It's about beating the other guy at the airport counter.

We broke the 55 brands into 9 categories and averaged the mention-citation gap within each:

Online travel agencies and metasearch tools post the smallest average gap in the dataset by a wide margin, less than half the gap of hotel chains and a quarter of the gap posted by attractions. The two highest individual citation rates in the entire study, both 41%, belonged to an OTA and a vacation rental marketplace.

This makes structural sense. An OTA's core product is comparison content: structured listings, filters, price tables, and specific answers to specific questions (“hotels in Barcelona with free cancellation under $150”). That's exactly the format AI models prefer to cite. A theme park or a hotel brand's core content is inspirational and brand-forward: hero images, lifestyle copy, broad category pages. AI models can recognize that content easily enough to mention the brand, but there's rarely a specific, structured answer on the page worth linking to.

Attractions posted the widest average gap in the dataset, pulled down by a couple of brands with elite mention rates and near-zero citation rates. Category-defining brand recognition, in this vertical more than any other, appears to work against citation conversion rather than for it.

This kind of segment-level split isn't unique to travel and hospitality. In Gradial's airline AI search visibility study, Gulf carriers converted awareness into citations far worse than European legacy carriers, even though the airline industry's overall average gap (61 points) dwarfed anything we found here. Whichever sub-segment has built the most structured, question-answering content wins the citation fight, no matter how big the parent brand is.

Brands that own a narrow, well-defined niche consistently outperform brands trying to lead a broad category.

One all-inclusive resort brand posted the highest citation rate of any brand outside the OTA and vacation rental categories, on the strength of very specific, high-intent content: overwater bungalow availability, butler service details, adults-only Caribbean specifics. It didn't need to compete on “best vacation” in general. It owns “best Caribbean adults-only luxury” specifically.

One brand most people would call the definition of ultra-luxury hospitality posted one of the weaker performances in the luxury tier overall, with its lone strong signal coming from a genuinely narrow niche (heritage residences on UNESCO-protected sites) that it has fully claimed. Everywhere else, quiet luxury interiors, travel skincare, wellness retreats, it was invisible, losing to smaller, more specialized competitors.

Tour operators as a category outperform their size, averaging a 22.2% citation rate against a 51.5% mention rate, a smaller relative gap than much larger competitors post. Sustainability certification content in particular (B Corp status, ethical-travel scoring) punches above its weight in this category, showing up as a real citation driver even for smaller brands going up against much bigger, better-funded competitors.

AI models cite definitive answers to narrow questions. They don't cite broad claims to leadership, no matter how big the brand behind them is.

This is the finding that should worry travel marketing teams the most, because it's not a content strategy problem. It's a broken pipe.

Several major brands in this dataset, spanning hotel chains, cruise lines, and OTAs, returned an HTTP 403 (forbidden) or 429 (rate-limited) status when their pages were crawled for this analysis, meaning the crawler was actively denied access rather than served a page that was merely thin or poorly structured. One of the review platforms that dominates citations elsewhere in this dataset returned a 403 on its own analyzed page. When a page returns an access-denied response to the crawler infrastructure behind AI search, no amount of content strategy fixes the citation gap. The model literally cannot see the page.

JavaScript dependency is the second major technical failure mode, and it's severe in places. One car rental brand's analyzed page was 100% dependent on JavaScript rendering, meaning zero content was visible to a crawler that doesn't execute JS. A major vacation rental marketplace came in at 97%. A cruise line came in at 80%. AI crawlers generally behave like old-school web crawlers rather than full browsers, so a page that needs JavaScript to render its value proposition looks blank to them.

Missing or invalid JSON-LD structured data and missing canonical URLs were flagged as high-priority fixes in the large majority of reports we reviewed. The travel-specific wrinkle is how often these technical failures compound with genuinely severe access issues (403s, 429s, noindex directives), rather than just the more common “the schema is missing” problem.

The recurring recommendation themes across all 55 reports:

1. Build intent-specific, high-fidelity landing pages instead of broad category pages. “Best hotels with high-speed Wi-Fi for business travel.” “Accessible car rentals with hand controls.” “Overwater bungalows in the Maldives.” This was the single most common recommendation across the dataset, appearing in some form in nearly every report. Broad brand pages earn mentions. Specific, structured answers earn citations.
2. Fix crawler access before anything else. If your page is returning a 403 or 429 to the bots behind AI search, every other GEO investment is wasted. Audit your bot access rules and CDN/WAF configuration before you touch content strategy.
3. Move critical content out of client-side JavaScript. Server-render or statically generate the specific claims, pricing details, and program specifics you want AI models to cite. If it only appears after JS executes, it's invisible to most AI crawlers.
4. Deploy JSON-LD structured data and fix canonical URLs. This is the same universal fix we've flagged in prior industry studies. Hotel, Product, FAQ, and Review schema give AI models a machine-readable answer instead of forcing them to guess from prose, and a correct canonical URL makes sure the citation credit lands on the right page.
5. Go deep on one or two owned niches instead of broad category claims. The strongest citation performers in this dataset all won by dominating something specific: a premium fleet niche, a heritage-site niche, a sustainability niche, a comparison-shopping use case. None of them won by trying to be the best answer to “best travel brand.”

One pattern worth flagging for hotel and car rental marketers specifically: loyalty program content in this dataset actually converts to citations in several reports, unlike what we found in the airline industry, where not a single loyalty program page earned a citation across 20+ carriers. If you run a hotel or rental loyalty program, this dataset suggests you're closer to winning that particular battle than airlines are. It's worth doubling down rather than assuming it's a lost cause.

To see where your brand specifically stands, request a free GEO report.

This analysis is based on Gradial GEO reports for 55 travel and hospitality brands, spanning hotel chains, luxury hospitality groups, online travel agencies and metasearch engines, car rental companies, cruise lines, theme parks and attractions, tour operators, vacation rental platforms, and all-inclusive resorts. Each report tracked 20 to 25 queries across 7 AI providers (OpenAI, Anthropic, Perplexity, Google Gemini, Grok, Microsoft Copilot, and Google AI Mode), producing 140 searches per brand and over 7,700 total data points. Queries were designed to reflect real traveler research intent across categories including luxury travel, business travel, family vacations, extended stay, loyalty and rewards, destination discovery, and booking logistics.

Headline mention and citation rate figures throughout this piece use each report's top-line scorecard metric as the authoritative figure. A small number of underlying reports showed minor internal inconsistencies between scorecard figures and narrative text elsewhere in the same report; scorecard figures were treated as the source of truth in every case.

This is part of Gradial's ongoing research into AI search visibility across industries. To see how your brand shows up in AI-generated answers, request a GEO report.