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Human-AI decision-making
When managers should accept, modify, pause, investigate, override, or escalate an AI-supported hotel decision.
Founder | Hotel Decision Lab
Drew Potter
Drew Potter is a former hotel operator and hospitality technology leader focused on how artificial intelligence changes managerial decision-making in hotel operations. He founded Hotel Decision Lab to study a narrower question: how should decision authority be divided between hotel managers and intelligent systems?
His work draws on experience in hotel operations, property leadership, and hospitality technology, alongside graduate study in business analytics and digital marketing. His current research program focuses on AI-supported hotel labor decisions, managerial judgment, calibrated reliance, human oversight, and decision rights.
Background
Hotel operations, hospitality technology, and decision research.
Drew’s background spans hotel operations, property leadership, and hospitality technology. That combination informs which operating problems Hotel Decision Lab studies, which conditions deserve attention, and how findings are translated for hotel settings.
Drew is an MBA candidate at Gies College of Business at the University of Illinois Urbana-Champaign, with academic focus areas in business analytics and digital marketing.
Professional experience helps identify operating problems, build realistic examples, and interpret how academic findings may apply to hotels. It is not treated as empirical research evidence. Hotel Decision Lab distinguishes professional interpretation from direct findings, author interpretation, propositions, and open questions.
Research interests
The decision-making layer of AI in hotels.
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Labor decisions
How forecasting, staffing, scheduling, and real-time personnel actions interact with local information and operating pressure.
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Decision rights
How organizations allocate authority, review, intervention, accountability, and monitoring between managers and intelligent systems.
Research and disclosure
How Hotel Decision Lab handles evidence.
Hotel Decision Lab uses a structured integrative review process and distinguishes direct findings, author interpretations, Hotel Decision Lab inferences, propositions, and open questions. Hotel-specific evidence is separated from evidence transferred from adjacent domains.
The current work is not presented as peer-reviewed research, original empirical research, a systematic review, or a validated framework. Read the full methodology and publication boundaries.
Drew works in hospitality technology. Hotel Decision Lab does not use proprietary employer, customer, prospect, or hotel information as research evidence. Relevant conflicts are disclosed when they bear on a publication.
Contact
Read the work or get in touch.
Start with the AI in Hotels research gateway, review the current research agenda, or browse published essays.