AI Governance in Practice — From Principles to Implementation

“We do AI responsibly,” says every company. But how many have a real governance framework? An AI governance board? Bias testing? From our experience: a fraction.

Framework Pillars¶

• AI systems inventory
• Risk classification — high/medium/low
• Model documentation — model cards
• Bias testing — automated tests
• Human oversight
• Monitoring and audit

Roles¶

AI Governance Board: a cross-functional team (tech, legal, business). Approves projects, defines policy.

Tooling¶

• Bias detection: Fairlearn, AI Fairness 360
• Explainability: SHAP, LIME
• Monitoring: WhyLabs, Arize

Governance Is a Competitive Advantage¶

Start simple: inventory, risk classification, model cards. You don’t need everything on day one.