AI-Driven Data Governance: A Framework for Real-Time Observability, Data Quality, and Compliance

As organizations accelerate digital transformation, data governance has become a critical enterprise capability to ensure trust, compliance, and operational efficiency. However, traditional governance models often fail to address the dynamic challenges of real-time data integrity, observability, and regulatory alignment in multi-domain, large-scale systems. This paper proposes a Data Governance Framework enhanced with Data Observability and AI/ML integration to deliver real-time monitoring, predictive quality assurance, and automated insights. Drawing on lessons from enterprise-scale finance and retail systems, the framework emphasizes modular governance, embedded observability, AI readiness, data certification, and ethical usage of data. The paper situates the framework within existing scholarly and industry literature, illustrates practical applications, and discusses its implications for future research and industry adoption.