AI-Driven Data Governance: Intelligent Metadata, Lineage, and Compliance Automation in Cloud Data Platforms

Abstract

This research examines how artificial intelligence and machine learning can automate and improve data governance across cloud data platforms. It focuses on intelligent metadata management, automated data lineage tracking, and continuous regulatory compliance monitoring. The proposed framework integrates machine learning for metadata inference and data classification, graph-based techniques for lineage tracking, and automated compliance rules for detecting potential violations. It also explores natural language processing, data discovery, impact analysis, explainable AI, and human-in-the-loop review. The paper discusses implementation strategies, integration challenges, model accuracy, data drift, and the importance of human oversight for sensitive governance decisions. It provides practical guidance for organizations seeking to scale data governance while improving visibility, consistency, and compliance across cloud and hybrid environments. Keywords: AI-Driven Governance, Data Lineage, Metadata Management, Compliance Automation, Cloud Data Platforms, Machine Learning.