Enterprise AI Governance: Frameworks + Implementation Guide

AI governance is crucial for companies implementing artificial intelligence systems, as it ensures these technologies are safe, fair, and aligned with organizational values. Effective governance involves understanding and managing data used by AI models, including training, tuning, and inference data, to prevent issues like bias, data leaks, and inaccuracies. As AI adoption grows, regulations like the EU's AI Act and state-level laws in the U.S. emphasize the need for compliance, transparency, accountability, and fairness. Companies should create clear governance frameworks, possibly drawing from established models like the NIST AI Risk Management Framework, and employ tools to enforce these rules across data, models, and workflows. Successful governance requires appointing clear ownership, crafting comprehensive policies, and treating governance as an evolving practice to adapt to technological and regulatory changes.