The value of an AI agent lies in its ability to complete a meaningful unit of work. That requires more than a language model and a collection of integrations. It requires an explicit role, a defined scope of authority, and clear escalation points for people.
A practical starting point
A well-designed agent can retrieve approved knowledge, prepare a recommendation, coordinate permitted tools, and record what it did. It should not act beyond the controls, evidence, or approvals appropriate to the workflow it supports.
The strongest path to adoption is to begin with bounded, high-value work: case preparation, policy triage, document review, or operational coordination. Autonomy can expand only as teams gain evidence that quality, safety, and accountability are being maintained.