In Brief: A global h2c survey of hotel chains found that 91% already use artificial intelligence, but limited staff expertise, fragmented strategies and weak data governance are limiting expansion across their organizations; most reported benefits involve productivity and automation, while measurable financial returns remain uncommon.
AI Adoption Outpaces Strategic Readiness
A h2c industry study released Oct. 1 found that artificial intelligence has become common across the global hotel industry, although most hotel chains have not developed the organizational and technical foundations needed to use it at scale.
The study found that 91% of participating hotel chains already use AI. An additional 8% expect to adopt the technology within the next 12 to 24 months. Despite that level of adoption, only 28% of respondents said their company has an organization-wide AI strategy directed by senior leadership.
Most hotel groups instead use AI through pilot projects, departmental programs or individual tools.
The study was based on 122 responses representing 113 hotel chains across Europe, the Middle East and Africa, Asia-Pacific and the Americas. Participating groups collectively operate more than 8,200 properties with approximately 1.3 million rooms. Results were not weighted by hotel chain size.
Efficiency Is the Most Common Benefit
Operational improvements are the clearest result of current AI use. Nearly 70% of respondents reported efficiency and automation gains, while 59% said AI lets employees spend more time on higher-value work. About 32% identified improvements to the guest experience.
Financial returns are less evident. Only 13% of hotel chains reported measurable returns from AI. Respondents rated AI’s contribution to overall business performance an average of 5.6 out of 10.
The survey also collected 230 examples of implemented AI uses from 78 hotel chains. Applications included guest communications, reputation management, revenue forecasting, marketing, reservations, personalization, finance, internal productivity and technology automation.
Skills and System Integration Remain Obstacles
Limited internal expertise was the most frequently reported barrier. Hotel chains rated their AI knowledge an average of 3.4 out of 10, and 56% identified a lack of expertise, skills or training as a constraint.
Integration with existing systems was cited by 38% of respondents, followed by the absence of a clear AI strategy or roadmap at 32%. Data security and privacy concerns affected 29%, while 28% reported problems involving data governance and access management. Budget or cost constraints were cited by 22%.
Compared with the previous year, fewer respondents identified cost, uncertain returns, organizational resistance or insufficient staffing as primary concerns.
External Tools Lead Current AI Use
Hotel chains depend heavily on publicly available products and technology vendors. External tools such as ChatGPT accounted for 60% of reported day-to-day AI use, while AI functions in vendor systems accounted for 27%. Internally developed or hosted systems represented 12%.
About 31% of hotel chains said vendor-provided systems were their main implementation approach, up from 21% in 2025. Another 25% used a combination of internal and external technology. The share of companies still exploring how to approach AI declined from 29% in 2025 to 12% in 2026.
AI Agents Attract Growing Interest
AI agents and booking through AI platforms were each identified by 70% of respondents as likely areas of innovation during the next two years.
Among hotel chains using or planning to use AI agents, 70% reported staff-facing applications, compared with 55% considering guest-facing uses. Internal applications include reporting, operational analysis, finance, administrative work and employee coordination. Guest-facing applications include answering questions, processing booking requests and presenting additional products or services.
Hotels remain cautious about allowing AI to make decisions independently during guest interactions. 56% of respondents cited unclear liability for errors. Data privacy and security concerned 54%, while 53% questioned whether guests would provide the necessary personal information. Accuracy, reliability and potential bias concerned 52%.
Hotels Expect AI to Influence Direct Bookings
Seventy percent of respondents expect booking channels powered by systems such as ChatGPT and Gemini to increase direct reservations over the next one to two years. Of those surveyed, 47% predicted a moderate increase and 23% expected a significant increase.
Monitoring of AI-generated search and recommendation results remains limited. Only 22% of hotel chains systematically track how their brands or properties appear in those results. Another 48% monitor their presence occasionally, while 20% do not monitor it and 10% are unsure.
Some hotel groups are adopting structured data, real-time availability connections and methods intended to improve visibility in AI-generated answers. However, 33% have taken no specific action to make their properties easier to find or book through AI channels.