EvaluationAISimone Figueira3 min read
AI agents in insurance customer service: a practical evaluation framework
A good demo answers a question. A good AI agent finishes a piece of work, with your data, inside your rules.
AI assistants are everywhere in insurance software pitches. Some are genuinely useful; many are a chat window on top of a generic model. For an agency, the difference shows up in week two, when clients ask real questions about their policy and the AI either helps the team or creates more work for it.
The five criteria
| Criterion | Ask the vendor to show | Red flag |
|---|---|---|
| Context | The AI answering with this client's policy, history and open cases | Answers that ignore who is asking |
| Action | A task created, a form sent or a record updated from a conversation | It only talks, never does |
| Handoff | A transfer to a person with a summary, in the same thread | The client has to repeat everything |
| Governance | Rules for what it can't answer, and a full log of what it said | No way to limit or audit it |
| Results | Response time, resolved or scheduled conversations, handoff rate | Only "conversations handled" |
If an AI mistake could change a client's coverage, premium or tax bill, a licensed person should approve that step.
See the signal, context, ARIA, automation and team pipeline in detail. How ARIA works
Run a two-week pilot, not a demo
- 01Pick one flow: after-hours lead response or document reminders are good starting points.
- 02Write the rules: what the AI may answer, what it must hand off and in which languages.
- 03Measure a baseline for response time and handoffs before turning it on.
- 04Review ten conversations a day with the team, and adjust.
- 05Decide with numbers: keep, expand or stop.
“AI amplifies the operation it sits on, for better or worse. Structure first, then intelligence.”
Next step
Test it with your own workflows.
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