AI governance refers to the set of legal, institutional, and organizational mechanisms used to shape the development, deployment, and use of artificial intelligence systems. These mechanisms include formal regulation, private law rules, standards-setting, market design, and internal governance practices within firms and public institutions.
In legal scholarship, AI governance is often contrasted with purely technical approaches to safety or alignment. Rather than focusing on how systems behave internally, governance frameworks emphasize how incentives, constraints, and accountability structures influence behavior externally.
AI governance is not limited to public regulation. It also encompasses private ordering through contracts, liability regimes, industry standards, and market institutions that condition access to data, compute, and deployment environments.