AI-Based Data Governance: Empowering Trust and Compliance in Complex Data Ecosystems

Abstract

In today’s interconnected digital environment, data governance is critical for ensuring regulatory compliance, data quality, and user trust. Traditional rule-based systems are often rigid, unable to cope with the dynamic and heterogeneous nature of modern data ecosystems. This paper presents an AI-driven data governance framework designed to automate policy enforcement, detect anomalies, and ensure continuous compliance across complex infrastructures. Leveraging machine learning and natural language processing, the system can 
adapt to evolving regulatory requirements, perform real-time data classification, and recommend corrective actions. Our proposed solution demonstrates significant improvements in compliance assurance, data quality scores, and governance efficiency. Experimental results across multi-cloud datasets reveal a 92% accuracy in detecting policy violations and a 38% reduction in manual auditing tasks, illustrating the transformative potential of AI in governance landscapes.