Before an AI agent can take action, define its permitted actions, give it a controlled identity and least-privilege access, log every material action, require human approval for consequential steps, and provide a monitored way to stop or revoke it. Add testing, rate limits, exception handling and clear ownership appropriate to the risk of the process.
Scope the action surface
A tool that drafts an email has a different risk from one that sends it, changes a customer record or triggers payment.
Use real identity and access design
Do not let autonomous processes inherit broad human credentials. Give them explicit permissions and traceable identities.
Treat failure as normal
Design what happens when the model is uncertain, a tool fails, data is inconsistent or the requested action violates policy.
How soapplied approaches the question
I would not start by assuming the stated problem is the whole problem. The first step is to understand the people, purpose, constraints and interactions around it, then test what intervention would improve the system rather than merely optimise one component.