AI Visibility in Hospitality 2026

What determines whether AI recommends your property — and is your website ready for the answer? Two original studies across five European markets, the four leading AI models, and 1,337 audited accommodation websites.

AI Visibility in Hospitality 2026 is a Nokumo Research report combining two original studies: 450 hospitality prompts across four AI models yielding 3,600 responses and 20,370 URL citations, plus an audit of 1,337 accommodation websites in five European markets. Its headline finding: OTAs take 22.9% of AI citations, and Booking.com appears in 95.3% of queries.

3,600

AI responses analyzed

20,370

URL citations extracted

1,337

Websites audited

Markets (DACH + Adria)

Nokumo Research · 2026-03-01 · 15 min read

The new reality: AI is replacing search

For two decades, finding a hotel meant a keyword, a list of blue links, and a booking. AI-powered discovery has no blue links — the assistant either recommends your property or it does not. To map this new landscape, Nokumo Research ran two studies between August 2025 and February 2026: 450 hospitality prompts tested across four AI models (GPT-5, Gemini 2.5, Perplexity and Mistral), yielding 3,600 responses, 20,370 URL citations and 13,859 brand mentions; and a technical audit of 1,337 accommodation websites across 30,935 pages in five markets — Germany, Austria, Switzerland, Slovenia and Croatia.

Who gets cited? URL citation share by provider type

Online Travel Agencies (OTA): 22.9%
Independent hotels (direct): 11.8%
STR platforms (Airbnb, Vrbo): 7.4%
Review / UGC platforms: 5.8%
Hotel chains (direct): 4.3%
DMO / tourism boards: 3.9%
Metasearch: 3.2%
Travel media / blogs: 2%
Other / unclassified: 24.1%

Booking.com — the undisputed champion

One domain towers over all others. Booking.com appears in 95.3% of every query tested and takes 14.5% of all citations — one in seven. The top three domains (Booking.com, TripAdvisor, Airbnb) account for 19.5% of citations, and only 86 of 4,043 domains are cited across all five countries. For every independent-hotel URL an AI cites, it cites roughly two OTA URLs.

OTA dependency by market

Croatia: 30.7%
Slovenia: 27.1%
Switzerland: 25.1%
Germany: 24.1%
Austria: 22.3%

Four AI models, four personalities

The models differ enough to be statistically distinct (χ² = 494.63, p < 0.001). GPT-5 is the most generous citer at 10.6 URLs per response and gives the best direct-booking outcomes. Perplexity is the most predictable and leans on review and UGC sources. Gemini 2.5 is the most OTA-heavy — significant given its place inside Google Search. Mistral returns zero URL citations yet still names 2.5 brands per answer.

Citations and brand mentions per response, by model

Gemini 2.5: Avg URLs / response 7.2, Avg brand mentions 3.8
GPT-5: Avg URLs / response 10.6, Avg brand mentions 6.4
Perplexity: Avg URLs / response 5, Avg brand mentions 3.1
Mistral: Avg URLs / response 0, Avg brand mentions 2.5

What travelers ask, who AI recommends

Intent is destiny. Luxury, wellness and business queries surface direct hotel sites most often; budget-city, family and event queries are captured by OTAs. Event and festival queries are the OTA trap — 39.4% OTA dependency, the highest of any intent — so hotels near a venue should publish event-specific pages with direct booking CTAs.

Share of citations by provider type for each travel intent (450 queries).
Intent	OTA %	Direct hotel %	Indep. hotel %	STR / VR %	DMO %
Luxury / Romantic	16.6	39.2	20.4	1.5	3.4
Wellness	21.3	36.5	27.6	0.2	5.4
Business	19.8	37.3	19.0	1.0	4.5
Unique Stays	24.1	31.2	22.9	12.4	2.1
Cultural / Sightseeing	28.7	22.4	10.3	6.8	8.9
Budget City	34.2	18.6	9.2	8.4	3.2
Family Vacation	32.4	20.1	5.9	14.7	5.3
Adventure / Nature	22.8	16.4	11.3	30.2	15.3
STR / Rental	18.4	9.2	7.1	36.0	6.8
Event / Festival	39.4	14.8	3.6	7.4	5.8

Direct booking score by segment

Business: 28.8%
Luxury / Romantic: 22.8%
Wellness: 22.3%
Unique Stays: 19.4%
Cultural / Sightseeing: 14.2%
Family Vacation: 12.8%
Budget City: 9.4%
STR / Rental: 7.2%
Event / Festival: 6.1%

The language effect

Every query was asked in English, German and Croatian. Language changes the answer. Croatian-language queries produce the highest OTA dependency in almost every market — up to ten percentage points higher — likely because Croatian-language training data is thinner on local providers, so models fall back to globally indexed OTAs. For DACH properties, German-language queries deliver the best direct-booking outcomes.

OTA dependency by query language

Austria: English 11.4%, German 10.5%, Croatian 20.6%
Germany: English 13.2%, German 10.5%, Croatian 19.6%
Switzerland: English 12.7%, German 11.9%, Croatian 21.3%
Slovenia: English 14.1%, German 13.8%, Croatian 22.4%
Croatia: English 17%, German 17.2%, Croatian 17.3%

1,337 websites under the microscope

The technical audit found an industry operating at under 40% of its digital potential, with an average score of 38.1 / 100. 77.1% of properties have no booking engine, only 39.2% use any schema markup, and just 7% implement Hotel/LodgingBusiness schema. Most decisively, only 5.7% of audited properties were detected in any AI model response at all.

Digital maturity vs. schema completeness, by market

Austria: Overall score (/100) 40.1/100, Schema completeness % 3.5%
Switzerland: Overall score (/100) 37.7/100, Schema completeness % 2.1%
Germany: Overall score (/100) 39.1/100, Schema completeness % 1.8%
Croatia: Overall score (/100) 34.8/100, Schema completeness % 0.9%
Slovenia: Overall score (/100) 35.8/100, Schema completeness % 0.6%

Digital maturity sub-scores by market (/100)

Austria: Content quality 55.5, Booking funnel 53.8, Trust signals 53.7, Technical SEO 56.6
Switzerland: Content quality 54, Booking funnel 50, Trust signals 48.2, Technical SEO 55.3
Germany: Content quality 53.8, Booking funnel 57.6, Trust signals 49.7, Technical SEO 52.8
Croatia: Content quality 51.7, Booking funnel 42.9, Trust signals 42.1, Technical SEO 47.7
Slovenia: Content quality 55.4, Booking funnel 43.2, Trust signals 41.2, Technical SEO 50.5

What AI-cited properties do differently

Of 1,337 properties, only 76 (5.7%) were cited by any model — and they are not the flashiest sites, they are the clearest. URL quality is the single biggest differentiator (Cohen's d = 0.60), followed by trust signals (0.50) and content quality (0.36). Schema, while worth doing, shows the smallest measured effect. A well-written 10-page site beats a flashy 50-page one.

What separates AI-cited properties (effect size, Cohen's d)

URL quality: 0.6
Trust signals: 0.5
Overall score: 0.4
Content quality: 0.36
Technical SEO: 0.29
Booking funnel: 0.26
Schema completeness: 0.23
Content completeness: 0.18

Content strategy: what AI wants vs. what exists

The corpus is dominated by basic property information (61.1% of pages) while the categories AI actually queries on are missing. Zero percent of audited sites had a dedicated room-listing, dining or amenities page. The biggest content gap is budget and value — 74.8% of properties have none — followed by luxury positioning and events. Even a basic five-page site with entity-rich content outperforms 60% of the corpus.

Content gap by topic (share of properties with no coverage)

Budget / value: 74.8%
Luxury positioning: 61.6%
Events / conferences: 56.4%
Business travel: 35.6%
Family travel: 23.7%
Activities: 23.1%
Wellness: 16.7%
Dining: 15.6%

13,859 brand mentions across 5,946 distinct companies. The independents that break through share distinctive concepts and strong third-party authority.
Rank	Company	Mentions	Category
1	Booking.com	628	Platform
2	Airbnb	417	Platform
3	Motel One	99	Chain
4	Hotel Cubo Ljubljana	67	Independent
5	Hostel Celica Ljubljana	46	Independent
6	City Hotel Ljubljana	44	Independent
7	Expedia	41	Platform
8	TripAdvisor	38	Review / UGC
9	Hilton	36	Chain
10	Marriott	34	Chain

The playbook: what to do now

The actions that move the needle, in order. Today: complete and maintain your Booking.com and TripAdvisor listings, and list on your national and regional DMO. This week: sharpen a specific, factual positioning and build intent-specific pages for luxury, wellness or business travel. This month: add Hotel/LodgingBusiness schema and make sure robots.txt allows GPTBot, Google-Extended, ClaudeBot and PerplexityBot. Ongoing: build external authority through editorial coverage, and re-test 10–20 representative prompts every quarter.

Methodology & AI disclosure

Two studies, August 2025 to February 2026: 450 prompts across four models and three languages in five markets (3,600 responses, 20,370 citations, 13,859 brand mentions), plus a technical audit of 1,337 websites and 30,935 pages. Research design, analysis and conclusions are human-generated and independently verified; AI tools were used only for editorial assistance and source retrieval. © 2026 Nokumo Services d.o.o. (Infranet Group). Free to share with attribution (CC BY 4.0, with logo).

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