Educational institutions worldwide face an increasing challenge in effectively integrating artificial intelligence technologies into their managerial and educational structures. The absence of coherent conceptual and operational frameworks has resulted in the adoption of these technologies often occurring in fragmented, uncoordinated, and sometimes high‑risk ways. This situation not only limits opportunities for innovation but also raises concerns regarding educational equity, privacy, and professional ethics. Addressing this theoretical and practical gap, the present study proposes a comprehensive ten‑domain classification of artificial intelligence applications in educational leadership.

The framework is derived from a systematic review of research literature published between 2017 and 2025. The identified domains include administrative productivity, personalized learning, enhancement of teaching practices, decision‑making and policy development, student support services, organizational leadership and strategic planning, data governance and adaptability, social interaction, ethical AI leadership, and diversity, equity, and inclusion initiatives.

The findings suggest that this framework can serve as both an analytical and practical tool for educational leaders, facilitating the alignment of technological advancement with human‑centered principles, the mitigation of algorithmic bias, and the promotion of educational equity. Furthermore, the results demonstrate notable alignment with policy guidelines developed by international organizations such as UNESCO.