Definition
AI governance is the set of policies, roles, and controls that keep your business’s AI systems legal, safe, and accountable.
At a glance
- Oversight, not coding: it sets who is accountable, what AI may be used for, and how its risks get checked.[3]
- Three frameworks dominate: voluntary NIST AI RMF (US), certifiable ISO/IEC 42001, and the binding EU AI Act.
- The EU AI Act sorts AI into four risk tiers, with obligations rising as risk rises.[2]
- Fines reach 35 million euros or 7 percent of global turnover for the worst violations.
How it works
Governance answers practical questions for any AI you build or buy: Who owns the decisions? What is off-limits? How is it checked for bias, errors, or data leaks before and after launch? NIST organizes this into four functions, Govern, Map, Measure, and Manage.[1] ISO/IEC 42001 lets you certify the same diligence to clients, while the EU AI Act sets the legal floor.[4]
Why it matters
If your AI denies a loan, screens a job applicant, or leaks customer data, the liability lands on you, not the vendor. Banned uses (like social scoring) are off the table; high-risk uses like credit scoring and hiring need documentation, human oversight, and audits.[2] Even outside the EU, governance cuts your odds of lawsuits, breaches, and brand damage, and customers increasingly demand it in contracts.
Bottom line
Pick a framework, name an owner, and write down what your AI may and may not do, before a regulator or lawsuit does it for you.