Governing AI Agent Sprawl Across the Enterprise

As AI agents proliferate, the governance challenge shifts from approving individual deployments to controlling a growing estate of non-human actors. The article proposes classifying agents by autonomy and access, maintaining a central system of record, assigning unique identities and owners, and monitoring actions rather than model performance alone. It also recommends review dates, rollback mechanisms, cost controls, and explicit retirement procedures. Technology leaders should scale controls with an agent’s ability to act and the potential consequence of that access rather than applying one governance policy to every use case.