Localizing matters: The effect of AI accent on tourist travel intention

This research delves into enhancing AI utilization in the tourism sector by focusing on AI-based destination ambassadors and optimizing their performance. Through introducing schema incongruity theory and meaning transfer theory, this research examines how AI ambassadors speaking in local accents, a form of AI localization, impact tourists’ travel intentions. Three experiments, utilizing varied AI forms and local accents for accent manipulation, demonstrate a positive impact on travel intentions (Studies 1–3). This effect stems from increased positive surprise and competence trust (Studies 2–3). Moreover, individuals with higher subjective knowledge of the local accent respond more positively (Study 3). Theoretically, this study urges a reevaluation of AI’s role given the specialty of tourism consumption and contributes to distinguishing between human and AI. Practically, it provides a valuable tool for AI localization in tourism and underscores the performance-enhancing benefits thereof.