The use of Artificial Intelligence in decision-making in tourism companies: a bibliometric review

Abstract

In a global context characterized by accelerated digital transformation, artificial intelligence (AI) has emerged as a strategic lever for strengthening decision-making within organizations. The tourism sector, which relies heavily on data analysis, demand forecasting, and service personalization, represents a privileged field for the implementation of these emerging technologies. However, despite the growing body of research on AI across various management domains, an integrated understanding of its impact on decision-making processes in tourism remains fragmented, highlighting the need for a structured scientific examination. The objective of this study is to provide a consolidated overview of the evolution of research dedicated to AI-driven decision-making, with particular attention to contributions related to the tourism sector. A rigorous bibliometric methodology was employed to explore the dynamics, structure, and trends of the field. Data were extracted from the Web of Science database for the period 2020–2025, based on a query simultaneously targeting artificial intelligence, decision-making, and tourism. After applying strict methodological filters, a final corpus of 105 articles was retained. The analysis conducted via Biblioshiny highlights sustained growth in scientific production, structured around core concepts such as artificial intelligence, decision-making, big data, and innovation. The emergence of themes such as ethics, trust, and automation reflect a broadening of academic concerns. Geographically, contributions are dominated by Asia and English-speaking countries. This review reveals a rapidly maturing field, particularly relevant for tourism organizations facing increasingly complex decision-making environments. It provides a solid foundation for understanding current research directions and their managerial implications.