AI Governance

AI Governance
Organizational oversight and management of AI systems

AI governance refers to the rules, institutions, practices and responsibilities used to guide development, deployment and oversight of AI. Governance can address performance, legality, transparency, accountability, safety, fairness and security; the appropriate controls depend on the context and risks of a specific system.

Risk management

The NIST AI Risk Management Framework is voluntary guidance organized around the functions of govern, map, measure and manage. The functions support continuous consideration of risks across the AI lifecycle.

Physical-system considerations

For robotics, governance may involve hazard analysis, incident reporting, role-based approvals, maintenance, access permissions, documentation of operational limits and records of model or software changes.

Standards and implementation

Governance guidance should not be confused with a binding law in every jurisdiction. Organizations need to determine which legal or sector-specific requirements apply to a given use case, and standards can change over time.

Further reading

• AI Risk Management Framework Core — NIST AI Resource Center

See also

• AI Safety
• AI Security
• Robot Cybersecurity
• Autonomous Systems
• Physical AI Identity
• AI Governance