A practical AI governance framework covering policy, risk assessment, human oversight, data protection and monitoring.
AI adoption without governance creates risk: data leakage, biased or inaccurate outputs, regulatory exposure and loss of trust. A lightweight governance framework lets you move fast and stay safe.
Why governance matters
Regulations and standards are emerging worldwide, including the EU AI Act, the NIST AI Risk Management Framework and ISO/IEC 42001. Even where not mandatory, customers increasingly ask how you govern AI.
Six building blocks
- Ownership. Name an accountable owner and a cross-functional review group.
- AI usage policy. Approved tools, data that must never be entered, and review requirements.
- Inventory and risk classification. List AI use cases and classify them by impact on people, data and decisions.
- Data protection. Access controls, data minimization and vendor due diligence.
- Human oversight. Define where humans review or approve AI outputs.
- Monitoring and improvement. Track accuracy, incidents and drift, and review regularly.
NIST AI RMF at a glance
The framework organizes work into four functions: Govern, Map, Measure and Manage. It is a useful structure even for small teams.
Start small
Begin with one or two use cases, apply the framework, and expand as you learn. Governance should enable adoption, not block it.
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AI governanceAI risk managementEU AI ActISO 42001NIST AI RMFresponsible AI
