Enterprise AI Governance Framework for Data Teams

This post details an enterprise AI governance framework for data teams, focusing on accountability, transparency, fairness, privacy, security, and proportionality. It outlines seven pillars for building this framework: organizational structure, strategic principles, policies and standards, lifecycle management, identity and access controls, testing and validation, and monitoring and auditing. It also discusses the regulatory landscape (EU AI Act, NIST AI RMF, ISO/IEC 42001:2023) and provides a roadmap for implementation, emphasizing enabling AI adoption rather than blocking it. It specifically addresses governing agentic and autonomous AI by highlighting the need for scoped permissions and kill switches.