Impact of Artificial Intelligence (AI) on Educational Leadership: A Systematic Literature Review

Abstract

This systematic literature review (SLR) examined how artificial intelligence (AI) influences educational leadership practices and what outcomes, risks, and governance challenges are reported in recent empirical research. Guided by the PRISMA-2020 framework, a comprehensive search was conducted across six major academic research databases, namely Web of Science, Scopus, PubMed, ERIC, DOAJ, and EBSCO. Eighteen peer-reviewed empirical studies published between 2024 and 2025 met the inclusion criteria and were synthesised using thematic analysis. Findings show that AI primarily affects instructional and administrative leadership by supporting data-informed decision-making, automating routine managerial tasks, and enabling more structured feedback and professional development. Leaders reported improved efficiency and faster access to organisational data; however, direct evidence of improved student outcomes remains limited. Ethical leadership emerged as a critical dimension of AI adoption, with persistent concerns regarding algorithmic bias, transparency, data privacy, and professional trust. Governance frameworks were found to be uneven, with many institutions lacking formal policies to regulate AI-supported leadership practices. Overall, the review portrays AI as a supportive rather than autonomous actor in leadership work, with its impact shaped by leaders’ professional judgement, institutional capacity, and regulatory context. The findings highlight the need for stronger governance mechanisms, leadership preparation in AI literacy and ethics, and longitudinal research across diverse educational settings.

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