Objective: To analyze the indexed scientific productions related to the role of artificial intelligence in the evolution of information seeking behavior in the Web of Science citation database in this field.

Method: The present study is an applied study with a scientometric approach. Data were extracted using the advanced search strategy in the Web of Science database in the period from 1976 to 2025 records. The analyses were performed using Excel, R. Studio, and Bibliometrics software.

Findings: The field of “Artificial Intelligence in the Evolution of Information Seeking Behavior” has experienced rapid growth in recent years; so that more than 39 percent of the 1902 records extracted from the aforementioned database belong to the years 2024 and 2025. Harvard University (33 articles) and author Liu (9 articles) are in the top ranks of institutions and authors, respectively. Keyword cluster analysis revealed seven thematic axes, including digital health, machine learning algorithms, natural language processing, generative artificial intelligence, recommender systems, and specialized information retrieval.

Conclusion: The field of study is a dynamic interdisciplinary field. In recent years, the need to review concepts such as trust, ethics, and information justice has become more prominent. In this direction, the humanities have gradually found a more effective place in the discourse of this field; however, continuing this trend and preventing the trend towards purely technical systems requires the expansion of deeper interdisciplinary collaborations, attention to the cognitive consequences of users' interaction with artificial intelligence, and the development of ethical frameworks for intelligent information retrieval systems.