Academic ResearchJuly 9, 2025Research report HES-SO Valais/Wallis

Artificial Intelligence in European Hotels: Adoption, Applications, and Barriers. Results of an Online Survey among Hotels in Austria, France, Germany, Greece, Italy and Switzerland

In today's hospitality sector, discussions among hoteliers invariably lead to artificial intelligence (AI). Announced as a transformative force, AI is poised to redefine everything from guest services and dynamic pricing to predictive analytics and content creation. However, a significant gap exists between this potential and its current implementation. This raises critical questions: what is the true state of AI adoption in the industry and what primary obstacles are impeding its progress? To find out, we surveyed over 1,500 hotels across six European countries between January and April 2025 in collaboration with hotel associations from Austria, France, Germany, Greece, Italy, and Switzerland as part of a follow-up to a 2023 baseline study. The results are clear: AI adoption is advancing, but gaps remain between intention and execution.

Authors

Roland Schegg

Article content

What the paper studied

This article summarizes a follow-up survey on AI adoption in European hotels. More than 1,500 hotels in Austria, France, Germany, Greece, Italy, and Switzerland were surveyed between January and April 2025 with national hotel associations, building on a 2023 baseline study.

Key findings

AI is now a regular topic for hoteliers, especially around guest services, dynamic pricing, predictive analytics, and content creation.
The survey points to a clear gap between AI's perceived potential and its day-to-day implementation.
Adoption is advancing, but many hotels remain stuck between intention and execution.

Why it matters for hospitality

The research gives operators a practical reality check: AI interest is high, but operational maturity is uneven. That gap matters because hotels that turn interest into working systems will move faster on service quality, productivity, and commercial decision-making.

Practical takeaways

Benchmark AI readiness against peers, not against vendor promises.
Focus first on high-value use cases where adoption barriers are lower.
Treat the 2025 findings as evidence that implementation capability is becoming a competitive issue.

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