AI assistants and agents need clear purpose, data boundaries, identity and access controls, approved tools/models, logging, evaluation, human oversight and defined accountability. The more an AI system can act rather than merely suggest, the stronger the controls must be. Governance should follow the risk of the action, not the novelty of the technology.
Start with allowed actions
Define what the system may read, generate, change, send or approve. Do not rely on a generic “use responsibly” policy.
Design oversight into the workflow
Human review should occur at meaningful decision points, especially where there is financial, legal, safety, customer or employee impact.
Operate it as a service
Monitor quality, drift, exceptions, access, incidents and model/vendor changes after launch.
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.