The Impact of AI-Enhanced Pedagogy on Tourism Education

The integration of artificial intelligence (AI) in higher education is reshaping pedagogical practices across all disciplines; however, its role in tourism education remains underexplored. To bridge the gap, therefore, this study examines the factors influencing tourism students’ acceptance of AI-enhanced learning tools by drawing on an extended unified theory of acceptance and use of technology (UTAUT) framework. This research incorporates perceived trust, perceived risk, and attitude as additional constructs to conduct a quantitative survey of graduate, postgraduate students, research scholars, and tourism educators from multiple institutions and regions across India. The study’s findings established that performance expectancy, effort expectancy, and social influence positively predicted students’ attitudes. Facilitating conditions, perceived trust, and attitude positively predicted behavioral intentions; perceived risk did not. Gender significantly moderated the links from performance expectancy → attitude, effort expectancy → attitude, and perceived risk → intention, but not the other paths. The study’s findings extend UTAUT by incorporating context-specific constructs. Furthermore, it offers practical insights for implementing AI-driven pedagogy in tourism education.