Review Article

Bibliometric analysis of scientific publications on artificial intelligence in educational management and leadership: Web of Science and Scopus sources between 1986-2026

Adem Yurdunkulu 1 *
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1 Ibn Haldun University, Istanbul, TURKEY* Corresponding Author
Contemporary Educational Technology, 18(2), April 2026, ep658, https://doi.org/10.30935/cedtech/18577
Published: 20 May 2026
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ABSTRACT

This study aims to map the academic literature at the intersection of artificial intelligence (AI) and educational management/leadership through bibliometric methods, using a dataset of 1,072 articles retrieved from the Web of Science and Scopus databases. Analyses conducted with R software and the Biblioshiny package reveal that the field is exceptionally young and dynamic, with an average document age of only 2.7 years, and that scientific output has increased substantially in the post-2020 period. This dynamic structure can be attributed to the COVID-19 pandemic and the widespread diffusion of generative AI tools. The geographical distribution of publication output indicates orientation towards new geographical directions with a growing concentration along a Eurasian axis. At the institutional level, Kazan Federal University (99 publications) and RUDN University (62 publications) emerge as dominant contributors, while China holds a global leadership position in citation impact (1,885 citations). This result should be cautiously handled as the database bias and publication concentration effects might have influenced the search outputs. In terms of conceptual structure, “artificial intelligence” and “machine learning” appear as dominant terms, and the thematic map identifies these concepts—together with “education management”—as motor themes. This finding suggests that the field has moved beyond purely theoretical debates and is transitioning into the mainstream of data-driven educational management. Considering this transformation, it is recommended that policymakers and leadership-development programs urgently integrate modules on data literacy and AI ethics. Overall, the study concludes that the discipline is undergoing a transition period, where future leaders will be responsible for governing algorithmic resources alongside human resources.
 
Keywords: artificial intelligence, bibliometric, education, leadership, management

CITATION (APA)

Yurdunkulu, A. (2026). Bibliometric analysis of scientific publications on artificial intelligence in educational management and leadership: Web of Science and Scopus sources between 1986-2026. Contemporary Educational Technology, 18(2), ep658. https://doi.org/10.30935/cedtech/18577

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