How Ready Is Europe’s Hotel Industry for AI? Insights from a Multi-Country Survey
Synopsis
Talk to any hotel executive today and artificial intelligence is almost guaranteed to be part of the conversation. From predictive analytics to personalised guest messaging, AI is widely seen as the next frontier in hospitality innovation. But how far have we really come, and where is the line between aspiration and implementation? To answer that, we surveyed over 1,000 hotels across Europe. What we found was a mixed picture, one that reveals both strong belief in AI’s potential and the practical barriers still holding many hotels back.
If you talk to any hotel executive today, the topic of artificial intelligence (AI) is almost guaranteed to come up. From predictive analytics to personalised guest messaging, AI is widely regarded as the next frontier in hospitality innovation. But how far along are we really? And what is the difference between aspiration and implementation?
To find out, we recently surveyed over 1,000 hotels in Austria, France, Germany, Italy and Switzerland. Results were insightful, not only because of the ways in which AI is already being used in hotels, but also because of the areas in which it is struggling to take root.
Strong Intentions, Uneven Reality
The majority of hotel managers recognise the value of AI. When asked in which areas AI will be most useful for hotels in the future, respondents cited reservations as the top area, followed closely by marketing, customer relationship management and data analysis/reporting. The industry clearly sees AI as a driver of performance and personalisation.
However, belief does not always translate into action. When we asked hotels which AI-based technologies they use, a much more cautious picture emerged. Only two solutions are widely implemented today: AI-generated content (e.g. ChatGPT or Gemini) for guest communication and online review analysis. Beyond that, adoption drops off quickly. Real-time revenue management, personalised emails or app recommendations, and predictive occupancy analytics are gaining traction, but more advanced applications such as chatbots, automated customer replies and virtual assistants remain on the fringes.
The contrast is even more striking when it comes to operational use cases. Fewer than 10% of hotels currently use AI for tasks such as guest check-in via facial recognition, robotic room automation or waste analysis. These figures suggest that the hospitality industry is still experimenting with basic use cases and is holding back from deeper operational transformation.
The Perceived Barriers Are Real
So what’s holding hotels back? Our respondents were clear: it's not a lack of interest, but a lack of clarity and capability.
The biggest barrier cited was 'poor knowledge of the available AI solutions on the market'. This was followed closely by integration challenges, a lack of technical skills and high setup costs. In short, AI is seen as both confusing and expensive, particularly by small to mid-sized operators who often lack dedicated tech teams.
Concerns about guest data privacy and staff acceptance were also widely reported. While these challenges are not new, they take on fresh urgency in the context of AI, where personalisation and automation require a degree of trust from both guests and employees that many hoteliers are still working to establish. While AI offers the promise of efficiency and optimisation, many respondents were simply not convinced that it would deliver a solid return on investment.
The Need for Operational Anchoring
To us, the message is clear: we have moved beyond the 'curiosity phase' of AI, but have not yet reached the 'confidence phase'. For AI to be adopted more widely in the hospitality industry, it needs to be firmly rooted in operational processes. This requires vendors to move away from generic sales pitches and help hoteliers develop AI roadmaps based on real workflows, staff capabilities and measurable performance goals. AI must help hoteliers solve their most urgent challenges, such as improving guest satisfaction, optimising rates in volatile markets and reducing staff workload, not just because it’s novel, but because it’s necessary.
The fact that 81% of respondents already use AI for content generation demonstrates how swiftly new tools can disseminate when the barriers are low and the value is evident. The challenge now is to apply that same clarity and usability to more complex areas, such as dynamic staffing and personalisation at scale.
A Shift in Mindset
The final piece is cultural. As one respondent told us: AI is not the problem – change is.
This sentiment reflects the fact that integrating AI is not just about choosing the right tool, but about preparing teams, rethinking processes, and fostering a learning mindset. That requires training – not only on how to use AI tools, but on how to lead AI projects, measure outcomes, and manage ethical questions.
Where Do We Go From Here?
If we had to summarize the state of AI in European hospitality today, We’d call it promising, but not yet aligned.
Hoteliers want AI that fits their needs, respects their limits, and empowers their people. They’re not looking for robots – they’re looking for relief, relevance, and results.