91% of the 113 hotel chains surveyed by h2c are already using artificial intelligence, yet only 28% operate under a company-wide strategy led by senior leadership, according to the German hospitality consultancy's 2026 AI Opportunity Study.

The gap points to a sector that has moved from experimentation to dependency without yet building the governance and architecture to scale. h2c's research, released October 1 from Ratingen, draws on 122 responses from 113 unique hotel chains — 101 online surveys and 21 executive interviews — covering EMEA, Asia Pacific, and the Americas. Participating groups collectively operate more than 8,200 properties and roughly 1.3 million rooms, averaging 73 properties per chain.

"The industry has moved beyond asking whether to use AI," said Michaela Papenhoff, Founder and Managing Director at h2c. "The more pressing question is how hotel chains turn widespread experimentation into connected, governed, and scalable capabilities."

What does the gap between adoption and ROI look like?

Operational efficiency is the clearest payoff so far. Nearly seven in ten respondents (69%) cite improved efficiency and automation, and 59% say AI frees staff for higher-value tasks. Improved guest experience ranks as a leading outcome for 32%.

Financial returns remain thin. Just 13% report measurable ROI from AI so far. Chains rate AI's contribution to overall business performance at 5.6 out of 10 — moderate impact, well short of broadly scalable.

Why are operators struggling to scale?

Skills, not cost, now lead the constraint list:

• Lack of AI expertise, training, or skills: 56%
• Integration challenges with existing systems: 38%
• No clear AI strategy or roadmap: 32%
• Corporate data-security and privacy concerns: 29%
• Data governance and access-management issues: 28%
• High costs or budget constraints: 22%

Compared with 2025, cost concerns, ROI uncertainty, organizational resistance, and staffing shortfalls have all declined. Chains now rate their internal AI knowledge at just 3.4 out of 10.

Who actually delivers the AI?

External tools dominate daily work. Public AI products such as ChatGPT account for 60% of reported usage. AI embedded inside vendor systems accounts for 27%. Internally developed or hosted tools represent only 12%.

When asked about implementation strategy, 31% of chains say they rely primarily on vendor-provided AI, up from 21% in 2025. A further 25% use a hybrid approach. The share still "exploring" their AI approach fell from 29% to 12% year over year.

"The findings underline the strategic role of hotel-technology vendors," said Christin Haensel, Director at h2c. "Hotels do not simply need more AI features. They need connected systems, accessible and well-governed data, and interoperable platforms."

Will AI agents and AI-driven bookings reshape distribution?

Two areas dominate expectations for the next two years: AI agents and bookings via AI platforms, each cited by 70% of respondents.

Among chains using or planning AI agents, 70% target staff-facing applications versus 55% for guest-facing ones. Top staff-facing opportunities include reporting and operational insights, finance automation, and internal coordination. On the guest side, chains see the most value in upselling, handling booking requests, and responding to inquiries.

Cautious operators flag liability for AI errors (56%), data privacy (54%), guest willingness to share personal data (53%), and accuracy or bias (52%) as the top concerns.

On distribution, 70% expect AI-driven booking channels — including ChatGPT and Gemini — to lift direct booking volume over the next one to two years. Yet only 22% systematically monitor how their brand appears in AI-generated search and recommendation results. Another 48% monitor occasionally; 20% do not monitor at all.

The full study is available to sponsors only; a public extract, the Hotel Chain Tech Report, is downloadable at h2c.de. Sponsors include Apaleo, Aven Hospitality, Busy Rooms, Cendyn, dailypoint, D-EDGE, Shiji, and Sirma Travel & Hospitality.

Whether 2026 produces a wave of measurable direct-booking lift from generative engines — or another year of fragmented pilots — will test whether chains can convert AI curiosity into audited P&L impact.