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Journals / European Journal of Technique (EJT) / 2026 / Cilt: 16 Sayı: 1

AI-Driven Digital Transformation in Higher Education: A Bibliometric Analysis of Research Trends

Nesip Yıldırım(BINGOL UNIVERSITY)0009-0004-1602-6253
Mehmet Yavuz(BINGOL UNIVERSITY)0000-0001-6218-232X
Pages
60–68
Publication Date
2026-07-01
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Overall, the findings provide a broad bibliometric overview of the evolving AI-driven digital transformation literature in higher education and may offer implications for future research and policy development.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Despite the rapid growth of academic literature at the intersection of artificial intelligence (AI), digital transformation, and higher education, comprehensive bibliometric syntheses that systematically map the intellectual structure and developmental trajectory of this domain remain limited.
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Key Findings & Data:This study addresses this gap through a bibliometric analysis of 614 publications indexed in the Web of Science database between 1997 and 2026.
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Conclusion & Impact:Overall, the findings provide a broad bibliometric overview of the evolving AI-driven digital transformation literature in higher education and may offer implications for future research and policy development.
🔬Design:Modeling & Simulation
📍Scope:2026 Verileri
⚙️Variables:Yapay zeka · Yükseköğretim · Dijital dönüşüm

Abstract

Despite the rapid growth of academic literature at the intersection of artificial intelligence (AI), digital transformation, and higher education, comprehensive bibliometric syntheses that systematically map the intellectual structure and developmental trajectory of this domain remain limited. This study addresses this gap through a bibliometric analysis of 614 publications indexed in the Web of Science database between 1997 and 2026. Using the bibliometrix R package, the study examined annual publication trends, geographic distribution, citation impact, co-authorship networks, journal concentration, thematic structures, and research life cycle patterns. The findings suggest that the field has experienced three broad developmental phases: an initial lag period (1997–2015), an acceleration phase (2016–2022), and a possible transition toward maturation after 2023. The logistic growth model estimated an inflection point around 2023.5, although this projection should be interpreted cautiously due to the evolving nature of the field. China emerged as the leading country in publication output, while the United Kingdom demonstrated comparatively higher citation impact. Thematic analysis indicates a gradual shift from technology-oriented discussions toward competency-oriented perspectives, with AI and innovation appearing as persistent motor themes. In contrast, ethics, equity, and governance-related topics remain relatively underrepresented. Overall, the findings provide a broad bibliometric overview of the evolving AI-driven digital transformation literature in higher education and may offer implications for future research and policy development.

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Cite This Article

Yıldırım, N., Yavuz, M. (2026). AI-Driven Digital Transformation in Higher Education: A Bibliometric Analysis of Research Trends. European Journal of Technique (EJT), Cilt: 16 Sayı: 1, 60–68. https://doi.org/10.36222/ejt.1932336

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