New for 2027
AI Best Practices Showcase
A session where academics share the best real-world use cases of AI in hospitality and tourism business. Each case shows a business problem, the AI solution that addressed it, and the results it produced. The goal is simple: give operators ideas they can use on Monday.
What qualifies
Real deployments, real numbers.
Any hospitality or tourism business: hotels, restaurants, resorts, airlines, cruise, attractions, events, destinations or the technology firms that serve them.
AI that is in use or in a documented pilot. Concept-only ideas belong in the research tracks.
Measured outcomes, such as revenue, cost, time saved, guest satisfaction, waste reduced or error rates, with a before and after.
Case brief
What to submit
A 500 to 800 word case brief with these six parts. Organizations may be named or anonymized.
- 1 · ContextThe organization, its size and segment, and who led the work.
- 2 · ProblemThe business problem and why it mattered.
- 3 · AI solutionThe tools, models or platforms used, and how they fit into existing systems.
- 4 · ImplementationTimeline, cost range, staff training and what went wrong along the way.
- 5 · ResultsMeasured outcomes against a baseline.
- 6 · LessonsWhat others can copy, what they should avoid, and any responsible AI safeguards.
Format
How the session runs
Seven-minute talks, three minutes of questions. Short enough to keep a mixed audience engaged, long enough to show the numbers.
Co-presenting is encouraged. Academics may present alongside the hotel, restaurant or vendor partner behind the case.
Industry and academic review. A joint panel scores each case on business impact, strength of evidence, transferability and responsible use of AI.
Best AI Practice Award. Judged on site by industry leaders attending the Summit.
Published casebook. Accepted cases appear in the GLOTECH 2027 AI Best Practices Casebook, a citable collection for teaching and practice.
Example topics
The kinds of cases we hope to see.
These are illustrations of scope, not accepted cases.
AI pricing or forecasting at an independent or small-brand hotel, with RevPAR before and after.
A guest messaging or voice agent that changed front desk workload and response times.
Demand forecasting that reduced food waste or improved labor scheduling in a restaurant group.
An AI trip planner or chatbot deployed by a destination marketing organization.
Housekeeping, maintenance or energy optimization using AI and sensor data.
AI tools for hiring, onboarding or training frontline staff, and how staff responded.