Purpose This study examines the key determinants of tourist satisfaction and behavioural intention regarding the use of artificial intelligence (AI) in the tourism sector. As AI technologies are increasingly integrated into travel experiences, understanding the tourist decision-making processes in using AI and key factors that drive positive behavioural outcomes is essential. Design/methodology/approach An online survey was administered to 449 tourists in Vietnam who had experience with AI-enabled tourism services. The proposed research model integrates the Artificially Intelligent Device Use Acceptance (AIDUA) model and Expectation Confirmation Theory (ECT). Structural equation modelling (SEM) was employed to test the hypothesised relationships between trust, satisfaction and behavioural outcomes. Findings The results reveal that outcome behaviours – such as consumer engagement, electronic word-of-mouth (eWOM) and continued use of AI-powered devices – are influenced through a multistage process, with satisfaction acting as a mediating variable. Trust emerged as a significant antecedent of satisfaction, shaped by both heuristic cues (i.e. social influences and hedonic motivation) and individual factors (i.e. technology dependence). Notably, the findings also reveal a negative relationship between performance expectancy and satisfaction. By integrating AIDUA and the ECT framework, this study provides a robust explanation of how tourists form attitudes and behavioural responses towards AI adoption in travel contexts. Practical implications The findings suggest that tourism stakeholders should leverage social influence, develop engaging and user-friendly AI applications, and enhance transparency to build trust. Emphasis on mobile-first strategies, adaptive AI interactions and strong governance frameworks is essential to support sustainable AI adoption in emerging markets like Vietnam. Originality/value This research contributes to the theoretical advancement of AI adoption in tourism by developing a comprehensive behavioural framework. It also offers practical implications for tourism providers and AI developers to implement strategies that foster trust, enhance satisfaction, and encourage favourable behavioural responses, ultimately improving the effectiveness and acceptance of AI-driven tourism innovations.
Ma et al. (2026) studied this question.