Purpose This study aims to examine academic research conducted on artificial intelligence (AI) in the field of tourism within a comprehensive bibliometric framework, revealing the intellectual structure, thematic development and collaboration networks of the field. Design/methodology/approach The dataset was obtained from the Web of Science Core Collection database; descriptive bibliometric indicators were used in the analysis process, along with visualisations showing co-authorship networks at the author and institution levels, citation relationships, keyword co-occurrence networks and time-based thematic transformations using VOSviewer software. Findings The findings reveal that AI research in tourism has undergone a significant transformation over the years. In the early stages of the literature, robotic services, automation, big data and technological efficiency were at the forefront, whereas in recent years, social and psychological dimensions such as trust, privacy, technology acceptance, human–robot interaction and emotional responses have gained prominence. In particular, the rapid rise of themes related to generative artificial intelligence (e.g. ChatGPT) after 2022 signals a significant shift in the field's research paradigm. Co-authorship and co-citation analyses reveal that AI research in tourism is becoming increasingly internationalised and its theoretical foundations are diversifying. Originality/value This study provides a systematic and up-to-date overview of the development of AI research in tourism by integrating bibliometric mapping and thematic evolution analysis. By identifying key research clusters, emerging themes and collaboration patterns, the study contributes to a deeper understanding of the field and offers insights into potential future research directions.
Sağcan et al. (2026) studied this question.