Despite the growing adoption of artificial intelligence (AI) in the hospitality industry, manual tasks persist as a burden for hotel staff. A recent H2c report reveals that 69% of hotels rely on employees to manually input guest preferences, while only 19% utilize AI to extract this data from guest interactions.
The State of Distribution 2026 report from New York University, RateGain and HEDNA found that more than 80% of commercial teams still spend one to two days a week producing and analyzing reports manually.
AI Adoption and Manual Work
The distribution report also revealed more than half of hotels are using or procuring generative AI, but fewer than one in 10 report reductions in manual work greater than 30%. According to Amanda Moore, VP of digital experience at Preferred Travel Group, much of initial adoption has been task-based, and the sector’s longstanding fragmentation issues stand in the way of true transformation.
Moore noted that applying AI over fragmented data does not remove underlying complexity. Ksenia Tarasova, CRM and brand loyalty manager at Penta Hotels, added that ‘AI’s utility relies entirely on the data and processes supporting it.’
Tarasova explained that AI cannot fix issues like duplicate guest profiles, inconsistent preferences, improper consent structuring, or data spread across multiple systems; in fact, it might worsen these problems. Connectivity is the primary issue, she said, rather than legacy systems.
Midsize Hotel Chains and AI Adoption
Moore and Tarasova highlighted AI’s impact on midsize hotel groups—defined as chains with less than 100 properties and a presence in a few countries—with the State of Distribution report identifying these chains as a “potential commercial ‘sweet spot.'” Midsize hotel chains had the highest adoption of preset automation when compared with large chains and independent hotels.
These midsize chains also saw the biggest labor cuts, with about 14% reporting a drop of over 30%. Furthermore, their AI search contributed to 6% of total reservations, the highest figure among the three hotel-size categories.
Tarasova observed that organizations must reach a certain size to invest in technology and specialists while remaining small enough to dodge the complexity and silos typical of massive tech ecosystems. Moore suggested success is not determined by budget alone.
In the middle of this AI adoption trend, it is clear that hotels are still figuring out how to effectively use AI to reduce manual work and improve efficiency.
Moore noted that hotels have improved infrastructure with strong websites and booking engines, but demand remains the major challenge. She stated, ‘OTAs are still very effective at capturing travelers during discovery and consideration, and independent hotels cannot simply outspend them.’
Hotels must provide travelers with reasons to book directly, which requires distinct content and storytelling, attractive member or direct-booking benefits, strong search and metasearch visibility, smooth booking processes, personalization, and better CRM usage after a guest enters the ecosystem.
Moore emphasized that differentiation is key for independent hotels. AI search, accounting for 4% of reservations in 2026, adds another element to this environment, according to the State of Distribution report.
Legacy systems are a component of the issue, but connectivity is the larger problem, according to Tarasova.
Tarasova noted that the industry is not yet ready for AI, as it is currently adding AI to individual tools rather than using it across the full guest journey.
AI’s Role in Hotel Operations
The State of Distribution report identified midsize hotel chains as a potential commercial “sweet spot” due to their balanced model, which supports specialized talent and automation while remaining agile.
Midsize chains have enough scale to invest in technology and specialist teams, but are still small enough to avoid the complexity and silos that hinder global brands, according to the report.