AI-Driven Data Governance: Advancing Security and Regulatory Compliance in Enterprise Systems

Abstract

Artificial intelligence is transforming data governance by enabling organizations to better protect data, address regulatory requirements, and manage enterprise information within unified environments. In recent years, data volumes have increased dramatically, while regulatory demands have become more stringent, complicating challenges related to data validation, security, and compliance with frameworks such as GDPR, HIPAA, and CCPA. This paper explores how organizations can integrate AI into data governance strategies as an automation mechanism for anomaly detection and enhanced security. AI-driven data management leverages machine learning, natural language processing, and predictive analytics to address critical organizational challenges. These technologies allow enterprises to automatically discover, classify, and index data, assess risks, and monitor usage patterns in real time. Furthermore, AI significantly strengthens data protection by employing anomaly detection models that can rapidly identify threats such as unauthorized access and malicious activities. The study also examines how AI supports regulatory compliance by improving audit processes, ensuring data accuracy, and enforcing compliance standards. AI-enabled policy automation restricts excessive data usage and prevents prohibited data sharing, thereby reducing the likelihood of violations, penalties, and breaches. Additionally, AI systems can anticipate future compliance risks by analyzing historical and current compliance trends. Through case studies and practical examples, the paper highlights key benefits of AI-based data governance, including improved data accuracy, reduced human intervention, and enhanced operational efficiency. At the same time, it addresses challenges such as ethical concerns, algorithmic bias, and the need for continuous system updates to remain effective in a rapidly evolving regulatory landscape. Overall, the study emphasizes the transformative role of AI in enterprise data governance, demonstrating its potential to enhance security, strengthen compliance, and unlock greater value from organizational data. Consequently, it recommends that enterprises adopt AI-driven governance frameworks while remaining mindful of the associated challenges in today’s dynamic data environment.