AI GOVERNANCE: THE BILLION-DOLLAR WAKE-UP CALL

Meta paid Texas $1.4 billion. Google paid $1.375 billion. Insurance companies face lawsuits for AI systems that rejected 300,000 claims in two months—spending 1.2 seconds per decision—with patients dying after early discharge.

This isn't theoretical risk. It's happening now, across every industry.

Most organizations think they have AI governance because they have policies. They don't. Their data governance frameworks weren't built for AI-specific risks: model drift, algorithmic bias, consent violations, lack of transparency. Every legacy risk gets supersized—then new ones get added.

In this episode, we break down:

- Why the SEC is charging individual executives personally for AI governance failures
- What "I delegated it to IT" no longer works as a legal defense
- The four core functions of the NIST AI Risk Management Framework
- How poor governance turns AI from competitive advantage into career-ending liability
- Your 7-day action plan to inventory systems, map accountability, and close compliance gaps

Key insight: AI governance isn't overhead that slows innovation—it's what makes your AI investments actually work while protecting you from becoming the next billion-dollar settlement.

If you're a C-suite executive, board member, or governance professional who can't answer basic questions about what AI systems operate in your environment—what data they access, what decisions they make autonomously, who approved those capabilities—this is your wake-up call.

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LinkedIn:https://www.linkedin.com/in/sheltonkhill/