AI governance defines the principles, roles, decision rights, policies, controls, evidence, monitoring, and accountability used across the AI lifecycle.

Create an AI governance framework with clear scope, an inventory, risk tiers, decision rights, lifecycle controls, monitoring, incidents, reporting, and review.

AI governance responsibility should be shared across the board, executives, business owners, technology, data, privacy, legal, security, risk, HR, and users.

The importance of AI governance lies in protecting people and the organization while creating clear ownership, faster decisions, safer innovation, and evidence.

An AI governance policy should cover scope, approved use, accountability, risk tiers, data, privacy, security, oversight, vendors, incidents, and enforcement.