How to Govern AI Agents

The governance of AI agents has evolved from managing single agents to overseeing entire fleets due to a phenomenon called "agent sprawl." This uncontrolled growth of agents within an organization creates new risks, including unforeseen costs and increased pathways for data leakage. The original four pillars of governance—lifecycle management, risk management, security, and observability—are still valid but must now be applied at scale across all agents. A fifth pillar, cost management, has become critical to control wasteful token usage. Modern solutions address this by implementing a centralized control plane to enforce policies, manage configurations, route tasks efficiently, set budgets, and provide unified tracing for the entire fleet.