Refers to the policies, processes, roles, standards, and oversight mechanisms used to guide how artificial intelligence (AI) is developed, selected, deployed, used, and monitored within an organization or system.

AI governance establishes who is responsible for AI-related decisions, what uses are permitted or restricted, and how organizations manage risks related to accuracy, privacy, security, bias, transparency, accountability, and other potential impacts.

Effective AI governance may include approved-use policies, human oversight requirements, risk assessments, data protections, documentation and audit trails, procedures for reviewing AI-generated outputs, and rules governing when AI systems may act autonomously and when human approval is required.

As AI systems become more capable—including agentic AI systems that can plan and carry out multi-step tasks—governance increasingly extends beyond approving particular AI tools to governing the processes, decisions, data, and actions in which AI participates.

AI governance seeks to balance innovation and responsible use by creating clear boundaries and accountability while enabling individuals and organizations to benefit from AI.

See Topic Brief: Regulation/Policy in Artificial Intelligence (AI) | Learn & Work Ecosystem Library