AI Hospitality Alliance
2026 Member Survey · Report

AIHA 2026 Member Survey Report

Themes, stakeholder priorities, engagement patterns, and implications for the future of AI in hospitality

Prepared: May 2026  ·  Source: 100 founding survey responses collected April 24, 2026 to May 6, 2026

100
total responses
78
want AI trend leadership
66
want to shape the industry
39
explore partnerships
Section 01

Executive Summary

The AI Hospitality Alliance (AIHA) member survey shows a market that is highly interested in AI, but hungry for practical guidance. Respondents are not asking for abstract AI commentary. They want a trusted convening body that can separate signal from noise, translate technology into hotel operations, and help the industry create shared standards before fragmentation hardens.

AIHA is being asked to become a de facto authority rather than another source of generic AI benefits; Hoteliers want help moving with the pace of innovation as smoothly as possible; and clarity plus broad automation remain important technology-vendor asks.

  • AI trend leadership is the clearest demand: 78 of 100 respondents selected staying ahead of AI trends as a reason to engage with AIHA.
  • The survey audience is broad but concentrated in four stakeholder groups: Technology Vendors, Hoteliers, Consultants, and Academics account for 90 of 100 responses.
  • The dominant frustration is the distance between AI promises and operational value, reinforced by concerns about fragmented systems, weak standards, and uneven readiness.
  • The strongest aspiration is for AIHA to become a practical, trusted knowledge hub: standards, case studies, education, benchmarking, and community are recurring asks.
  • Engagement appetite is active rather than passive. Workshops, research participation, content contributions, and partnerships all drew high interest.
Strategic readout

AIHA has permission from this respondent base to act as a translator and standard-setter: convene the ecosystem, identify credible use cases, publish practical guidance, and keep AI aligned with measurable hospitality outcomes.


Section 02

Survey Purpose and Respondent Base

The survey is designed to understand what hospitality AI stakeholders need from AIHA: what they hope to gain, how they prefer to participate, what frustrates them most about AI in hospitality today, and what they would change if they had a 'magic wand' for the future.

Respondents included technology vendors, hoteliers, consultants, academics, investors, media, and other industry participants. Email addresses were excluded from the analysis and report outputs; results are presented in aggregate.

Respondent stakeholder mix
100 total survey responses
27
26
23
14
5
4
Technology Vendor
27 respondents (27%)
Hotelier
26 respondents (26%)
Consultant
23 respondents (23%)
Academic
14 respondents (14%)
Other
5 respondents (5%)
Investment Company
4 respondents (4%)
Media
1 respondents (1%)
Stakeholder typeResponsesShare
Technology Vendor2727%
Hotelier2626%
Consultant2323%
Academic1414%
Other55%
Investment Company44%
Media11%

Section 03

What Respondents Want From AIHA

The highest-priority needs are intellectual leadership and practical translation. Respondents want AIHA to track fast-moving AI trends, provide applicable use cases, publish high-quality research, and create venues where stakeholders can shape the industry's direction together.

What respondents hope to get from AIHA
Multi-select question; counts show number of respondents choosing each option.
Stay ahead of AI trends shaping hospitality
78
Contribute to shaping the future of the industry
66
Learn practical AI use cases I can apply today
65
Access high-quality research, insights, and data
60
Connect with industry peers and leaders
59
Participate in events, workshops, or discussions
50
Discover relevant technologies, vendors, and solutions
46
Find business, investment, or partnership opportunities
38
Other (please specify)
5
Survey choiceSelectionsShare of respondents
Stay ahead of AI trends shaping hospitality7878%
Contribute to shaping the future of the industry6666%
Learn practical AI use cases I can apply today6565%
Access high-quality research, insights, and data6060%
Connect with industry peers and leaders5959%
Participate in events, workshops, or discussions5050%
Discover relevant technologies, vendors, and solutions4646%
Find business, investment, or partnership opportunities3838%
Other (please specify)55%

Section 04

Preferred Engagement Model

Engagement preferences reinforce that the audience wants a working alliance, not only a newsletter. Workshops, research participation, content contributions, and partnerships all drew high interest. Partnership and sponsorship interest is smaller but still meaningful, with 39 respondents selecting it.

Preferred engagement modes
Multi-select question; respondents could choose more than one.
Attend events or workshops
71
Participate in research or surveys
66
Contribute content or insights
61
Just stay informed
58
Explore partnerships or sponsorship
39

Section 05

Biggest Frustrations: What Is Holding the Field Back

The frustration responses are not anti-AI. They are anti-confusion. Across stakeholder groups, respondents describe a market crowded with AI claims, immature integrations, uncertain governance, and limited evidence of measurable hotel outcomes.

Frustration themeMentionsAvg. sentiment
Hype vs. real value26−0.08
Keeping pace & education24−0.07
Fragmentation & integration20−0.08
Adoption readiness & investment18−0.09
Human and guest impact18−0.05
Trust, governance & risk13−0.11
Distribution & platform power8−0.11
Talent, training and workforce7−0.15
Environmental and social impact3−0.15
Biggest frustrations by stakeholder type
Cell color reflects share of coded responses within each stakeholder group.
Technology Vendor
Hotelier
Consultant
Academic
Hype vs. real value
727%
819%
922%
00%
Keeping pace & education
415%
717%
717%
630%
Fragmentation & integration
623%
819%
410%
210%
Adoption readiness & investment
14%
410%
1127%
210%
Human and guest impact
28%
717%
410%
420%
Trust, governance & risk
312%
12%
410%
315%
Distribution & platform power
14%
25%
25%
210%
Talent, training and workforce
14%
410%
00%
15%
Environmental and social impact
14%
12%
00%
00%

The heatmap shows that each stakeholder type is worried about a slightly different version of the same problem. Vendors emphasize standards, distribution power, and practical credibility. Hoteliers emphasize operating reality and the gap between vendor promises and guest/employee usefulness. Consultants concentrate on value clarity, readiness, and implementation. Academics most often frame the challenge as education, guidelines, and responsible use.


Section 06

Magic Wand Aspirations: The Future Respondents Want

The magic wand question shifts the tone from frustration to constructive ambition. Respondents repeatedly imagine AIHA as an industry platform that sets standards, teaches practical use, convenes stakeholders, and anchors AI adoption in measurable hospitality value.

Aspirational themeMentionsAvg. sentiment
Trusted knowledge hub & education41+0.14
Guest experience and operations31+0.16
Collaboration and community29+0.17
Data, analytics and distribution28+0.13
Common standards & interoperability24+0.17
Practical use cases & measurable ROI24+0.23
Responsible AI and trust15+0.14
Talent, training and workforce8+0.18
Sustainable AI infrastructure2+0.01
Magic wand aspirations: full dataset
Bubble size reflects theme mentions; color reflects average sentiment tone.
41
Trusted knowledge hub & education
31
Guest experience and operations
29
Collaboration and community
28
Data, analytics and distribution
24
Common standards & interoperability
24
Practical use cases & measurable ROI
15
Responsible AI and trust
8
Talent, training and workforce
2
Sustainable AI infrastructure

The overall bubble diagram shows the center of gravity: standards and interoperability, practical use cases, trusted education, and collaboration. The survey base wants AIHA to make AI less abstract and more operationally usable.


Section 07

Stakeholder-Specific Implications

StakeholderWhat the survey suggestsAIHA opportunity
Technology VendorWants credible standards, clearer market rules, and better visibility into AI search/distribution dynamics.Create interoperability working groups and publish vendor-neutral implementation guidance.
HotelierWants solutions that work in real operations, not another disconnected layer.Prioritize operational case studies, buyer checklists, and measurable implementation playbooks.
ConsultantWants a stronger bridge between strategy and hotel execution, plus better agreement on the problem before AI solutions are adopted.Build benchmark libraries, maturity models, practitioner forums, and cross-stakeholder alignment sessions.
AcademicWants applied learning, classroom-ready examples, responsible-use guidance, and research collaboration.Create teaching cases, research agendas, and industry-academic project pathways.

Bottom line

The survey points to a clear founding mandate: AIHA should help hospitality move from fragmented AI excitement to practical, trusted, measurable adoption.


Appendix

Methodology

The analysis is based on 100 founding-member survey responses collected April 24–May 6, 2026. Email addresses were removed before analysis, and all results are reported in aggregate.

Multi-select fields (member goals and engagement preferences) were split on semicolons and each selected option was counted once per respondent, so reported percentages reflect the share of respondents choosing an option rather than a share of total selections. The two open-ended questions were analyzed on the responses actually provided: 82 of 100 respondents answered the “biggest frustration” question and all 100 answered the “magic wand” question. Responses were coded with keyword-based theme dictionaries built from the survey’s own language, and a single response could contribute to multiple themes when it clearly referenced multiple topics.

Sentiment scoring used a transparent positive/negative lexicon rather than a trained machine-learning model, and should be interpreted directionally — as a relative signal of tone across groups and themes — rather than as a statistically validated emotion measure.

The four analyzed stakeholder groups — Technology Vendor, Hotelier, Consultant, and Academic — account for 90 of the 100 responses. The remaining 10 responses (Other, Investment Company, and Media) are included in whole-dataset counts and visuals where appropriate, but the dedicated comparison diagrams focus on the four requested groups.