AI ethics in hospitality and tourism: theoretical perspectives, ethical beliefs, and actionable outcomes.

INTRODUCTION: As AI becomes embedded across hospitality and tourism, its ethical implications remain fragmented and largely undertheorized; this scoping review synthesizes the evidence on AI ethics in the sector. METHODS: Following a PRISMA-guided search and screening of Web of Science, Scopus, and Emerald, we reviewed 32 studies and organized findings into nine cross-cutting themes, with associated research gaps and future questions. To extend prior descriptive work, we interpret the literature through epistemology and the ethics of belief, examining how AI systems in service contexts form, justify, and act upon "beliefs" (e.g., inferred preferences, risk scores, and recommendations) and how unjustified beliefs can generate ethical harms. RESULTS: We map ethical concerns across key hospitality and tourism sub-sectors (e.g., accommodation, transportation, entertainment) and translate them into actionable guidance. Specifically, we propose (1) a sectoral risk framework that classifies common AI applications from unacceptable to minimal risk, and (2) a structured AI life-cycle approach identifying ethical safeguards at problem definition, data collection, model development, deployment, and feedback. CONCLUSION: The review advances a theory-based understanding of AI ethics in human-centric service industries, offering practical implications for managers, policymakers, and researchers seeking responsible AI adoption.