From Technology Adoption to Organizational Governance: Mapping the Intellectual Structure and Shifting Paradigms of AI Governance in Educational Leadership

This study maps the intellectual structure and thematic evolution of the intersection between artificial intelligence (AI) and educational leadership in related literature. Employing a hybrid research design that integrates bibliometric analysis with Latent Dirichlet Allocation (LDA)-based topic modeling, we examined 757 unique records retrieved from the Web of Science and Scopus databases for the period 2017–2026. Through computational optimization, the corpus was delineated into six emerging research themes that dictate the field’s shifting paradigms: “Digital Leadership & Transformation,” “Teaching & Student Learning,” “AI Acceptance & Self-Efficacy,” “Data Management & Machine Learning,” “School Leadership & Principals,” and “Technical & Computational Fields.” While “Digital Leadership & Transformation” dominates over half of the literature, a sharp proportional decline in “School Leadership & Principals” uncovers a critical structural imbalance between abstract institutional transformation discourse and the actual human agents executing it. Furthermore, a severe underrepresentation of technical, governance, and transparency themes exposes a critical “opaque box” crisis of institutional agency. The study concludes that the field remains theoretically fragmented and calls for an integrated socio-technical framework reconciling leadership governance with the complex realities of AI systems.