Data Governance as the Foundation: Preparing Legacy Infrastructure for AI-Powered DevSecOps

The document argues that organizations deploying AI-powered governance tools on legacy data infrastructure create an invisible failure mode: AI systems that function correctly but operate on untrustworthy data, producing authoritative-looking outputs that cannot be verified.

This paper presents a detailed examination of the challenges and solutions addressed by Data Governance, providing actionable frameworks for organizations navigating the intersection of AI adoption and regulatory compliance.

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• Establishes a structured approach to data governance that aligns technical implementation with federal compliance requirements.
• Demonstrates how Data Governance concepts translate directly into measurable engineering controls and audit artifacts.
• Provides implementation patterns validated against real-world deployment constraints in regulated environments.
• Identifies critical gaps in current approaches and proposes concrete architectural solutions backed by operational evidence.