Sarcouncil Journal of Multidisciplinary

Abstract: This article presents an AI-augmented Master Data Governance framework for healthcare enterprises in regulated environments. Merging smart algorithms with established data governance practices elevates information quality, accelerates verification processes, and upholds regulatory standards. Current healthcare systems struggle with mushrooming data stores, tangled attribute relationships, ever-changing compliance rules, and workforce constraints. By employing smart algorithms for finding duplicates, spotting inconsistencies, and anticipating quality issues within enterprise systems, this framework elevates data governance while satisfying strict healthcare mandates. The architecture combines core MDG components with specialized algorithms implemented through a phased approach. Performance tracking shows clear improvements in data precision, worker efficiency, regulatory alignment, and technical reliability. Implementation revealed vital success elements, significant hurdles, and valuable future possibilities. Hospitals and clinics secure meaningful benefits through this approach, applying sophisticated calculation methods to strengthen expert decisions, reduce compliance risks, and maintain operational unity across connected business frameworks.