INTEGRATING AI IN DECISION MAKING IN EDUCATIONAL MANAGEMENT: CHALLENGES AND PROSPECTS

Abstract

Artificial Intelligence (AI) is increasingly transforming educational management by strengthening institutional planning, administrative efficiency, monitoring, forecasting and evidence-based decision-making. Contemporary educational institutions can employ AI tools such as machine-learning and predictive-analytics systems, natural-language processing applications, learning and institutional analytics platforms, AI-powered dashboards and generative AI assistants to analyse institutional information and support managerial decisions. However, the use of AI in educational decision-making also creates challenges relating to transparency, accountability, algorithmic bias, data privacy, explainability, infrastructure, technical capacity and stakeholder trust. These concerns are particularly important where AI informs high-stakes decisions involving admissions, staff recruitment and promotion, resource allocation, student support, quality assurance, accreditation and institutional planning. This paper examined the integration of AI in decision-making in educational management, with particular attention to its applications, benefits, challenges and prospects. The paper adopted a conceptual and narrative review approach, synthesising literature on AI in education, educational management, AI-supported decision-making, explainable AI, ethical governance and responsible AI. The discussion was guided by the Trust-Centred Explainable Governance Framework (TCEGF), which was proposed in the original version of the paper and is explicitly operationalised in the revised article. The framework links AI-enabled data and analytical tools to AI-generated recommendations, explainability and transparency, human oversight, ethical and algorithmic accountability, stakeholder participation, institutional learning and improved educational-management outcomes. The paper argued that AI should function as a decision-support capability rather than an autonomous substitute for educational managers. It concludes that responsible integration of AI can improve the timeliness, consistency, predictive capacity and evidence base of educational decisions when supported by appropriate governance, explainability, data protection, capacity building and human judgement.