High-risk AI agents need more than a single manager's approval. They can access sensitive data, call tools, influence customers, affect regulated workflows, or take actions that are hard to reverse. The approval process should reflect that shared risk.
The right approvers depend on the system, but the approval record should always answer who reviewed the agent, what they reviewed, what conditions they set, and when the decision expires.
Business approval
The business owner should confirm purpose, expected benefit, user population, launch scope, and acceptable operating boundaries. This approval matters because AI systems often expand beyond the original experiment. The owner should be accountable for the workflow, not just the idea.
Business approval should also confirm whether the agent is necessary, whether a less autonomous design would work, and what success and failure look like.
Technical approval
Engineering or technical owners should review architecture, model provider, prompts, retrieval sources, tools, permissions, evaluation results, logging, rollback, and change management. For agents, the tool list deserves special attention.
Technical approval should confirm that the system can be operated, monitored, and changed without relying on undocumented knowledge.
Security and privacy approval
Security should review access controls, least privilege, secrets handling, prompt injection defenses, data exfiltration risk, logging, and incident response. Privacy should review personal data, purpose limitation, retention, user notice, data subject rights, and vendor processing terms where relevant.
These reviews should be conditions of launch, not paperwork after launch.
Legal, compliance, and risk approval
Legal and compliance teams should review applicable obligations, regulated use cases, customer commitments, disclosures, records, and prohibited or restricted uses. Risk leaders may need to approve residual risk for systems with meaningful business or user impact.
Human oversight approval
For high-risk agents, someone should approve the human oversight model. Which actions need review? Who reviews them? What information does the reviewer see? Can the reviewer override the agent? Are reviewers trained?
The approval package should end with clear launch conditions, required controls, monitoring expectations, review date, and evidence location. A high-risk agent should not leave approval as a conversation. It should leave a durable decision record.