# AI Governance The frameworks, policies, and institutions that guide the development and deployment of AI systems. Broader than regulation (which is one tool); governance includes industry standards, ethical guidelines, technical safety measures, international coordination, and organizational policies. Key dimensions: safety, fairness, transparency, accountability, privacy. Distinct from [[AI Safety]] (technical research on making AI systems behave as intended), [[AI Alignment]] (ensuring AI objectives match human values), and AI Ethics (philosophical inquiry into right and wrong). Governance is the operational and institutional layer that translates these concerns into enforceable rules, standards, and organizational practices. Examples: the [[EU AI Act]] (risk-based regulatory framework), NIST AI Risk Management Framework, ISO/IEC 42001, corporate AI review boards, and model evaluation standards. The challenge is keeping governance adaptive. AI capabilities evolve faster than policy cycles, creating a persistent gap between what systems can do and what rules cover. ## References - ## Related - [[Microsoft AI Agent Governance Toolkit]] — operational stack for policy, identity, sandboxing, and compliance for AI agents - [[AI Safety]] - [[AI Alignment]] - [[Responsible AI]] - [[EU AI Act]]