| Sumario: | Artificial intelligence, which for many years was considered a subfield of computer science, has recently gained significant importance in the social sciences--particularly within the disciplines of business and management. In these fields, artificial intelligence has become a key driver of transformation in areas such as decision-making, strategic planning, process optimization, and innovation management. Its contributions have shifted traditional management approaches toward data-driven structures and have played a mediating role in enhancing organizational performance. Consequently, previous studies in this field serve as an essential reference point and guide for researchers. Building on this motivation, the present study aims to systematically examine the academic reflections of artificial intelligence within the social sciences using bibliometric analysis and to evaluate its position in the international literature, current research trends, and future scientific potential. The analysis is based on 16,410 articles published in the Scopus database between 1970 and 2023. The findings reveal that research on artificial intelligence has increased markedly since 2017 and that the United States leads the field in terms of publication volume and citation impact. Co-authorship analyses indicate that scholars such as Dwivedi, Kraus, and Dung hold central positions in the literature, while institutions such as the Institute of Research and Development and Fuy Tan University emerge as key nodes in collaboration networks. At the country/region level, the United States, China, and the United Kingdom stand out, occupying central positions in global scientific interaction through strong collaboration linkages. Overall, the bibliometric analysis demonstrates that scientific production, collaboration, and impact networks in the domain of artificial intelligence form complex yet meaningful patterns across individual, institutional and country/region levels.
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