Artificial Intelligence and Educational Leadership_ A Bibliometric Analysis (2004–2024) and Global Policy Review

The rapid evolution of Generative Artificial Intelligence (GenAI) and the transition to Society 5.0 have catalyzed a profound socio-technical metamorphosis in global education systems, shifting the role of education leaders from administrative managers to techno-pedagogical strategists. This study investigates the intersection of Artificial Intelligence (AI), leadership, and educational leadership through a dual-method research design, combining a bibliometric analysis of 188 core academic documents (2004–2024) from the Web of Science database with a qualitative thematic analysis of 30 influential global reports on AI from organizations such as UNESCO, the OECD, and the Washington OSPI. The findings reveal a significant “theory-practice divide,” where current literature remains largely normative, lacking empirical evidence of real-world principal-AI interaction. Central to the emerging theoretical framework is the human-AI-human (H-AI-H) model, which positions AI as a “co-pilot” rather than a final arbiter, emphasizing that educational processes must begin and end with human insight. Bibliometric trends highlight a shift toward “hybrid distributed leadership,” where technical tasks are delegated to AI while adaptive leadership, grounded in empathy and ethics, remains a human prerogative. Despite the potential for AI to reduce administrative workload and facilitate scalable personalized learning, the study identifies critical risks regarding algorithmic bias, the “intelligence divide,” and data privacy. Results indicate that while approximately 50% of educational leaders are already engaging with AI, there is a substantial competency gap in algorithmic governance. This paper concludes with a call for updated leadership competency frameworks and localized “AI use and ethics policies” to ensure that the integration of technology enhances human agency rather than undermining pedagogical autonomy.