AI Adoption and Operational Benefits
The research includes 122 responses from 113 unique hotel chains. It covers Europe, the Middle East and Africa, Asia Pacific, and the Americas. The participating groups represent more than 8,200 properties and approximately 1.3 million rooms. On average, each participating chain operates 73 properties. In addition, 78 hotel chains provided 230 examples of implemented AI use cases. These applications cover guest communication, reputation management, revenue management and forecasting. Other areas include internal productivity, marketing, reservations, personalization, operations, finance and technology automation.
- Nearly seven in ten respondents report improved operational efficiency and automation.
- Meanwhile, 59% say AI enables staff to focus on higher-value tasks.
- Improved guest experience represents another reported outcome, cited by 32% of organizations.
- Financial results remain less established across participating hotel chains.
- Only 13% report measurable return on investment from AI so far.
- Hotel chains rate AI’s contribution to overall business performance at an average of 5.6 out of 10.
Skills, Integration and Strategy Remain Key Barriers
Internal AI knowledge receives an average rating of only 3.4 out of 10.
Lack of AI expertise, training or skills represents the leading adoption barrier, cited by 56% of respondents.
Integration challenges with existing systems affect 38% of respondents.
Another 32% cite the absence of a clear AI strategy or roadmap.
Corporate data security and privacy concerns affect 29% of participating organizations.
Data governance and access-management issues account for 28% of responses.
High costs or budget constraints are cited by 22%.
Compared with the previous year, concerns about costs and uncertain ROI have declined. Organizational resistance and staffing concerns have also decreased. Hotel chains increasingly rely on external technology providers and publicly available AI tools.
External AI tools, including ChatGPT, account for 60% of reported day-to-day usage.
AI embedded within vendor systems represents a further 27% of usage.
Internally developed or hosted AI tools account for 12%.
Overall, 31% of hotel chains primarily rely on vendor-provided AI solutions.
The corresponding figure stood at 21% in 2025.
A further 25% use a hybrid approach combining internal and vendor solutions.
The proportion still exploring their AI approach fell from 29% in 2025 to 12% in 2026.
AI Agents and AI-Driven Booking Channels
AI agents and bookings through AI platforms represent the two most frequently cited innovation areas for the next two years.
- Each category was selected by 70% of respondents.
- Among organizations using or planning to use AI agents, 70% target staff-facing applications.
- Guest-facing applications account for 55% of planned or existing AI agent use.
- Staff-facing opportunities include reporting, operational insights, finance and administrative automation. They also include internal communication and coordination. For guests, respondents identify upselling and cross-selling, booking requests and guest inquiries as key applications. Hotel chains also report concerns about autonomous decision-making in guest interactions.
- Unclear liability following AI errors represents the main concern, cited by 56%.
- Data privacy and security concerns account for 54% of responses.
- Another 53% cite guests’ willingness to provide the required personal data.
- Concerns about accuracy, reliability and potential bias affect 52% of respondents.
- AI-driven discovery and booking channels are also becoming part of hotel chains’ technology planning.
- Seventy percent expect AI-driven booking channels to increase direct booking volumes within one to two years.
- Among them, 47% anticipate a moderate increase and 23% expect a significant increase.
- Only 22% systematically monitor their brands or properties in AI-generated search and recommendation results.
- Another 48% monitor these results occasionally.
- Meanwhile, 20% do not monitor them, while 10% remain unsure.
Hotel chains are beginning to use answer-engine optimization, generative-engine optimization and structured data. They are also developing real-time availability and booking capabilities for AI-driven channels. However, 33% have not yet implemented specific measures to improve visibility and bookability through these channels.
