The rapid diffusion of generative artificial intelligence, exemplified by ChatGPT, is reshaping how travelers search for information and plan trips. Based on a questionnaire survey of individuals with prior experience using conversational AI for travel planning or information search, this study examines the adoption of AI-generated travel information in authentic tourism contexts. Drawing on the Information Adoption Model and the Elaboration Likelihood Model, we investigate how Information Quality (IQ) and Prompt Engineering Characteristics (PEC) influence trust, how trust drives recommended travel information adoption, and how Faith in Technology and Novelty Seeking moderate these relationships. The results show that both IQ and PEC significantly enhance trust, which in turn strongly promotes the adoption of AI-generated travel information. Among the PEC dimensions, promptness does not exert a significant effect, suggesting that in high-involvement travel planning, users value contextual relevance, controllability more than response speed alone. The findings extend information adoption research by highlighting that trust in generative AI is shaped not only by output quality but also by the co-constructed nature of iterative human-AI interaction. Practically, the study suggests that the value of generative AI in tourism lies less in speed than in context-sensitive and decision-relevant support.
Wang et al. (2026) studied this question.