An AI-Enabled Multi-Level Governance Framework for Consulting and Research Institutes in Saudi Public Universities

This study examines the governance of institutes of studies and consulting services in Saudi public universities, which operate as hybrid entities combining academic and contract-based consulting functions. Despite their strategic role, these institutes face governance challenges, including overlapping authorities, unclear roles, and inconsistent levels of transparency and accountability. The study adopts a qualitative analytical approach based on reviewing relevant literature and governance frameworks, including the Three Lines Model, the Committee of Sponsoring Organizations of the Treadway Commission (COSO) Internal Control Framework, and Organisation for Economic Cooperation and Development (OECD) principles, to develop an integrated multi-level governance framework aligned with the Saudi regulatory context. The proposed framework organises governance across defined levels and classifies entities into core, supporting, and oversight bodies to enhance role clarity, strengthen control mechanisms, and improve institutional coordination. It also incorporates artificial intelligence as an enabling component to support data analysis, performance monitoring, anomaly detection, and risk prediction. The findings suggest that adopting this framework can improve institutional performance, enhance transparency and accountability, and support financial sustainability. The study provides practical policy implications for standardising governance practices and enabling data-driven decision-making in Saudi public universities, in line with Vision 2030. The study contributes by providing a structured and scalable governance model that bridges the gap between academic governance and contract-based institutional operations.