Who Controls AI Agents in an Organization?

Your organization should assign a named owner to each AI agent and agree who approves its work, manages its access and reviews its activity. Control becomes practical when you can show who authorized the agent, what it was allowed to do and what it actually did.

Put ownership in writing and keep a register of agents, their approved tasks and the people responsible for them. A job title alone does not explain what an agent may access. Agree on who approves use, manages permissions and reviews activity. Kiteworks’s discussion of unclear ownership is a reason to check your own arrangements, not evidence that every organization lacks an owner. Its role examples are guidance, not universal legal assignments.

Make that responsibility practical by checking identity and permissions whenever the agent requests sensitive data, then linking its activity to the authorization. Kiteworks describes Compliant AI as applying identity checks, access policy, encryption and audit logging to data governed through its platform. These controls support review at that boundary; wider agent behavior and other systems still need oversight. Confirm coverage and configuration, since published product descriptions do not establish deployment compliance.

Put this into practice

Register each agent with a named owner and approved task.
Assign approval, access management and review responsibilities.
Keep access records linked to the agent’s authorization.

Who controls AI agents in an organization?

Put this into practice

Sources

See the controls in your workflow.