Generative AI in Tourism and Hospitality: A Systematic Review

Generative artificial intelligence (GenAI) is rapidly transforming tourism and hospitality, yet reviews have largely focused on bibliometric mapping, conceptual discussions, or specific applications, leaving limited integration of research methods, theories, benefits, risks, and tourism experience personalization. This study systematically reviews GenAI research in tourism and hospitality to identify its methodological and theoretical foundations, major applications and constraints, personalization mechanisms, and future research directions. Following PRISMA 2020 guidelines, the Web of Science and Scopus were searched for studies published from 2022 to June 2026, yielding 125 eligible peer-reviewed journal articles. Through qualitative content analysis and systematic coding, the studies were classified by methodology, theoretical foundation, application context, benefits, constraints, and personalization mechanisms. The findings show that quantitative approaches, particularly SEM/PLS-SEM and scenario-based experiments, dominate the field, while S-O-R, TAM, trust-related theories, social exchange theory, and UTAUT/UTAUT2 are the most frequently adopted theoretical foundations. Four major benefit categories and four constraint categories are identified, while personalization occurs mainly through situational adaptation, role-based interaction, and cognitive activation. The study contributes an integrated analysis of the field and proposes a Technology–Psychology–Organization framework linking GenAI characteristics, tourist responses, and organizational implementation. Practically, it highlights the need for transparent, risk-sensitive, and human-centered GenAI deployment.