Enterprise AI governance is the set of rules, policies, and technical controls that define what data an AI system may access, what actions it may take, and what outputs it is allowed to produce inside a business. It turns AI from a flexible tool into a managed part of the enterprise environment, with limits for privacy, compliance, safety, and accountability.
This matters because business AI can leak sensitive data, generate harmful advice, or trigger actions through connected tools and agents. In attacks, weak governance can let prompt injection, unauthorized data retrieval, or overprivileged automation turn a model into a path to internal systems. In defense, governance is enforced with access controls, content filtering, audit logs, approval workflows, and policy checks at inference time so teams can see, restrict, and review what the AI is doing.