AI-Driven Decision Support Systems for School Leaders: A SystematicLiterature Review of School Improvement Practices in Malaysian UrbanPublic Secondary Schools

Abstrak

This systematic literature review examined how artificial intelligence (AI)-driven decision support systems (DSS) are represented in existing literature as tools to support school leaders’ decision-making for school improvement in Malaysian urban public secondary school contexts. Guided by Digital Leadership Theory, the Data-Driven Decision-Making Framework, Organisational Learning Theory and Sensemaking Theory, the review adopted a qualitative systematic literature review methodology. ERIC was used as the main structured database search, while Google Scholar and DOAJ were used as supplementary sources. A total of 363 records were screened at the title and abstract stage, 52 full-text articles were assessed for eligibility, 27 studies were appraised for quality, and 16 studies met the quality threshold for final thematic synthesis. Across these studies, 131 extracted data segments were coded and synthesised. Five themes were generated: AI-augmented leadership practices and decision-support functions; data-informed and predictive school improvement planning; leadership readiness, organisational learning and human-centred change; ethical governance, accountability and trust in AI-supported decision-making; and resource availability, equity and contextual fit for sustainable AI implementation. The findings indicate that AI-driven DSS can support school leaders by strengthening data interpretation, predictive planning, administrative efficiency, instructional leadership and targeted intervention. However, AI does not directly produce school improvement. Its value depends on leadership judgement, professional capacity, ethical governance, stakeholder trust, digital infrastructure and contextual adaptation. The study concludes that AI-supported decision-making should be understood as augmented school leadership, where AI supports but does not replace human interpretation, ethical responsibility and context-sensitive decision-making.