Glossary · AI engineering and governance
AI governance
German: KI-Governance
In organizations, AI governance is the system of roles, policies, processes and controls by which the development, procurement, use and monitoring of AI systems is directed and overseen, so that AI is used effectively, responsibly and in line with legal requirements. ISO/IEC 38507 addresses the governance implications of AI for governing bodies.
- Industrial AI
- AI
- Standards
In one sentence
AI governance is the system of roles, policies and controls that directs and oversees how an organization develops and uses AI.
Example
A machine builder's AI board approves each AI feature, checks whether it may fall under the EU AI Act and assigns an owner responsible for monitoring.
How it applies
- Engineering: AI governance defines how AI functions are proposed, assessed, approved, validated and changed. For machines and plants, this links to existing processes such as risk assessment and Change control.
- Compliance: It includes classifying AI systems under applicable rules such as the EU AI Act, assigning roles such as provider and deployer, and keeping the required records.
- Documentation: Governance produces documents: policies, inventories of AI systems, risk assessments, model records and instructions for users. Documentation teams should know which of these reach the customer.
AI governance vs. AI management system
AI governance is the overall direction and oversight. An AI management system (AIMS) according to ISO/IEC 42001 is a structured way of implementing it with defined processes, objectives and continual improvement. Having governance or a certified management system does not by itself make an AI system compliant.