RPA works well when the world is deterministic: fields are stable, rules are explicit, and exceptions are rare. Broker workflows are less orderly. They combine documents, client intent, underwriting constraints, compliance checks, and time pressure. Adding AI can help, but it also changes the risk profile.
The design issue is control. An AI-assisted RPA workflow should know when to extract, when to ask, when to escalate, and when to stop. It should leave a trace of the evidence used and the operation performed. In financial and insurance contexts, automation without auditability is deferred risk.
The stronger architecture is layered: deterministic RPA for stable operations, models for interpretation, rules for authority boundaries, and human review where financial or regulatory consequences are material.