Artificial Intelligence in School Management. A Systematic Review

Abstract

This article addresses a significant gap in the literature by synthesizing peer-reviewed evidence on artificial intelligence (AI) applications in school management, focusing on administrative decision-making, resource allocation, operational support, and educational leadership. The review follows PRISMA guidelines and draws on approximately forty peer-reviewed studies published between 2018 and 2026, retrieved from SpringerLink, Sage Journals, ScienceDirect, ERIC, and Google Scholar. To contextualize AI-enabled administrative functions, the analysis also incorporates research from organizational studies, management information systems, business process management, and cybersecurity. Particular attention is given to explainable AI and stewardship, including formal modeling approaches for administrative processes and techniques that enhance the transparency and accountability of algorithmic decision-making. The review further examines financial management, student data protection, cybersecurity, interoperability, federated learning, and the integration of large language models into school information and ERP systems. Three key themes emerge. First, AI can improve administrative efficiency, reduce workload, strengthen data-informed decision-making, and optimize organizational processes. Second, successful implementation depends on robust governance frameworks, ethical guidelines, AI literacy among staff and leaders, effective data protection and cybersecurity measures, interoperability planning, and adequate digital infrastructure. Third, core dimensions of educational leadership— including professional judgment, relational trust, contextual understanding, creativity, and ethical accountability—remain indispensable and should be preserved as AI adoption expands. Based on these findings, the article proposes three research hypotheses concerning the relationship between AI-driven automation and administrative workload, the role of AI governance frameworks in shaping stakeholder outcomes, and the moderating effect of organizational support on the relationship between AI integration and institutional performance. The review also identifies methodological limitations in the existing evidence base, which remains dominated by conceptual and qualitative studies. Overall, AI offers substantial potential to transform school management, but its effectiveness depends on sustained investment in governance, technical safeguards, AI literacy, transparency, and equity-oriented implementation practices.