AI Governance

AI governance connects purpose, roles, decision rights, policies, controls and evidence so that AI systems are used throughout their lifecycle in line with strategy, risk tolerance, values and applicable requirements. It links technical choices to organisational accountability and defines how systems are selected, developed, acquired, evaluated, operated, monitored, changed and retired. It is not a single committee or one-off approval.

Use the term when an organisation needs repeatable rules and accountabilities across several AI use cases or throughout a system lifecycle.

Governance stops at principles or an ethics policy without owners, risk criteria, evidence, escalation and operational processes. Conversely, disproportionate centralisation can obstruct low-risk use without improving control.