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Bibliometric analysis reveals seven thematic clusters in AI-driven tourism personalization, highlighting emerging focuses on large language models and ethical concerns like algorithmic bias.
Purpose This study aims to examine the transformative role of artificial intelligence (AI) in enhancing personalization and efficiency in tourism. By analyzing current literature, it identifies key gaps and proposes actionable directions for advancing AI-driven innovation in the sector. Design/methodology/approach The research uses a bibliometric analysis of 185 peer-reviewed articles sourced from Web of Science and Scopus databases between 2014 and 2024. The study uses cooccurrence network analysis, supported by VOSviewer, to map thematic clusters and trends related to AI applications and personalization in tourism. Findings The keyword cooccurrence analysis revealed seven thematic clusters. Findings highlight growing scholarly interest in AI-driven personalization, chatbots, large language models and hybrid recommender systems, alongside increasing attention to ethical considerations such as algorithmic bias and data privacy. Originality/value This study contributes to the growing body of literature by presenting a research agenda focused on a critical perspective on AI adoption. It also contributes by explicitly linking ethical AI frameworks with user-centered innovation.
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Khaliliadl et al. (2026) studied this question.
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