HEDNA and AI Hospitality Alliance Map 109 Hotel AI Uses

The AI Hospitality Alliance and HEDNA have released the Hospitality AI Use Case Catalogue, cataloguing 109 unique artificial intelligence use cases across 39 hotel systems [1]. Distilled from 198 industry submissions, the interactive framework organizes applications across five core operational functions and three cross-cutting infrastructure layers to guide operators on where automation is active today [1].

What is the Hospitality AI Use Case Catalogue?

The Hospitality AI Use Case Catalogue is a crowdsourced industry framework created by the AI Hospitality Alliance and HEDNA to document tangible artificial intelligence deployments across hospitality [1]. As Lodging Magazine reported, the project received 198 industry submissions, which underwent review and deduplication to produce 109 unique applications [1]. The resource groups these applications across 39 distinct hotel systems [1].

Technology vendors represented 39 percent of the initial 198 submissions, while consultants contributed 32 percent, according to Asian Hospitality [2]. Other contributors made up 21 percent, and hoteliers accounted for 8 percent of the submissions [2]. The catalogue provides metadata for each entry, detailing primary beneficiaries, adoption maturity, supporting evidence, and cross-functional reach [1].

Which hotel departments have the most active AI use cases?

Operations leads the industry in deployment volume, housing 35 identified AI use cases, 32 of which already possess live real-world examples [2]. Revenue management and business intelligence ranks second with 27 use cases, including 23 backed by active examples [2]. Guest experience features 16 use cases [2]. Marketing and sales, along with distribution and commerce, complete the five primary functional areas, with distribution accounting for 10 distinct applications [[1], [2]].

In terms of repeated submissions, different contributors submitted identical concepts independently across several departments [2]. Operations registered eight repeated submissions, guest experience saw seven, and distribution recorded five [2].

How are hoteliers prioritizing AI implementations?

Distribution and commerce recorded the highest average priority score among the core categories at 55.8, despite having fewer total use cases than operations [2]. Within distribution, the top-rated application is AI-search visibility and machine-readable hotel discovery, which targets how hotel inventory surfaces inside algorithmic search engines and automated booking services [2].

In operations, labor scheduling and labor-cost optimization achieved the highest category priority score, averaging 45.3 [2]. In guest experience, AI guest inquiries, concierge services, and automatic replies took top priority with an average score of 45.2 [2]. In revenue management and business intelligence, dynamic pricing and room-rate optimization secured the top priority ranking [2]. Asian Hospitality noted that the catalogue's evaluation-priority score reflects industry interest rather than verified return on investment, vendor software quality, or current market share [2].

What business problems are properties attempting to solve?

Properties target manual workload reduction more than any other issue, with manual work and staff capacity challenges cited in 36 percent of all 109 use cases [2]. Revenue leakage and conversion obstacles represent the second most frequent problem at 34 percent, while decision visibility and forecasting account for 25 percent [2].

When assessing reported business impacts, efficiency and time savings lead the catalogue, identified in 61 percent of use cases [2]. Guest experience and service impacts follow at 49 percent, while revenue and conversion gains appear in 47 percent of applications [2]. Despite this focus, productivity results remain uneven across the sector; Asian Hospitality cited the State of Distribution 2026 report by NYU’s Tisch Center, RateGain, and HEDNA, which found that while over half of hotels use or procure generative AI, fewer than one in 10 have cut manual work by more than 30 percent [2].

Where does hotel AI infrastructure lag behind?

Hotel development, asset intelligence, and transaction layers show minimal technological maturity compared to back-of-house operations [[1], [2]]. The catalogue tracks three structural layers: payments and transaction infrastructure; data, middleware, semantic and agent infrastructure; and hotel development, asset and investment intelligence [1].

Payments infrastructure currently features just one identified use case, which possesses zero live examples [2]. Hotel development and investment intelligence includes three use cases, also with zero live examples, while logging the lowest average priority score across the entire catalogue [2].