Agentic AI Meets Data Governance: The Unseen Battle for Control in Customer Data Platforms - Sumbaraju, Aditya Chakravarthy (International Journal of Computing and Engineering, 2025)
Integrating Agentic Artificial Intelligence into Customer Data Platforms represents a critical inflection point in enterprise data management, creating tension between technological advancement and governance imperatives. This article examines how autonomous AI systems, capable of independent learning and decision-making, fundamentally transform how organizations process customer data while simultaneously challenging traditional governance frameworks. As these self-directed systems increasingly collect, modify, and act upon sensitive customer information with minimal human oversight, enterprises face complex ethical, legal, and operational dilemmas spanning data provenance, explainability, and consent management. The article investigates this governance paradox by examining regulatory landscapes, emerging compliance challenges, and innovative governance approaches. By analyzing the conflict between AI autonomy and data governance requirements, this article proposes balanced frameworks that enable organizations to harness AI's transformative potential while maintaining appropriate control over their data ecosystems, ensuring both innovation and compliance in an increasingly AI-driven environment.