AI-mediated cultural tourism experiences: balancing utility and authenticity in shaping cultural attachment and tourist engagement

Artificial intelligence (AI) recommendation systems increasingly shape tourist decision-making on digital platforms, yet their influence on cultural attachment and engagement remains underexplored. Drawing on the Stimulus–Organism–Response framework integrated with appraisal and attribution perspectives, this study examines how perceived benefits and perceived concerns toward AI-generated cultural recommendations jointly influence tourists’ emotional attachment and engagement behavior. Data were collected through a scenario-based online survey of 358 experienced AI users in China. Structural equation modeling combined with response surface analysis reveals that perceived benefits strongly enhance cultural attachment and engagement, whereas perceived concerns primarily weaken attachment but have limited direct behavioral effects. Engagement is highest when both benefits and concerns are simultaneously high, suggesting that reflective evaluations of utility and authenticity foster deeper involvement with cultural experiences. The findings highlight how AI-mediated recommendations function as experiential interfaces shaping meaningful tourism engagement.