AI-Enhanced Decision Support Systems for Strategic Higher Education Management: A Framework for Improving Decision-Making Efficiency and Stakeholder Trust

This study investigates the role of Artificial Intelligence (AI) in enhancing decision-making effectiveness within higher education institutions.It specifically examines how AI integration levels, data quality, administrator training, and ethical governance practices contribute to the performance of AI-enhanced Decision Support Systems (DSS).Descriptive statistics were used to analyze central tendencies, while correlation, regression, and ANOVA tests were conducted to assess relationships and predictive impacts among variables.The results demonstrate that higher levels of AI integration are significantly associated with improved decision-making effectiveness.Institutions with robust AI training programs for administrators and highquality, accessible data reported greater confidence and success in implementing AI-driven decisions.Transparency and ethical governance emerged as critical factors, positively influencing stakeholder trust in AI outcomes.Among the tested algorithms-ROA, BMA, and SSPA-the SSPA algorithm outperformed others across all performance metrics, including prediction accuracy, operational efficiency, bias mitigation, and fairness enhancement.These findings highlight the importance of a balanced AI strategy that prioritizes both technological capabilities and institutional readiness.This research contributes to the growing literature on AI in education by identifying the key enablers of successful AI-driven governance.It provides actionable recommendations for institutional leaders seeking to improve administrative outcomes through AI, emphasizing training, ethical compliance, and high-quality data infrastructure.