How to onboard a new claims handler to an AI agent workspace

Start a new claims handler on the agent's output, not a blank claim. In week one they learn how the agent takes first notice of loss, checks cover and drafts reserves and offers, and shadow a certified handler. In week two they decide held claims with every decision checked. Settlement authority is granted in stages, lowest values first, after sign-off.

What does the claims agent already do?

In an insurer or claims administrator that runs agents, the claims agent typically records the first notice of loss from a call, form or email, checks the policy for cover and excesses, requests documents, flags fraud indicators, suggests an initial reserve and drafts settlement offers for simple claims. Intake and document requests run at depth 2 or 3 within set rules. Coverage decisions, reserves and offers are drafted at depth 2 for a handler to decide. Paying a claim moves money and is depth 4, earned only on evidence, and in most teams stays with a person above small amounts.

A new handler therefore spends less time typing claim details and more time on the decisions: is this covered, is the reserve right, does this need investigation, is the customer vulnerable? The change is described in what changes in a claims handler's day when AI agents arrive. The claims team leader owns onboarding.

What is the plan, day by day?

1. Day 1. Person (team leader): shows the agent's bounds for this book of business: what it may do alone, what it holds, what it refuses.
2. Day 1 to 2. Person (new handler): learns to read cover checks. The policy wording is sealed from the policy system. The customer's account of the loss is declared. A repairer's estimate is signed. A photo emailed by a third party is external.
3. Day 2 to 4. Agent, depth 2: drafts coverage views, reserves and offers on live claims, decided by a certified handler while the new handler watches and asks.
4. Day 5. Person (new handler): works closed claims in a sandbox workspace, deciding from the agent's drafts with the outcome hidden.
5. Week 2. Person (new handler): decides live held claims, each checked before it takes effect.
6. Week 2. Person (new handler): records reasons on every change to the agent's draft.
7. End of week 2. Person (team leader): grants authority up to a low settlement value if accuracy is high and no red line was missed.

Which judgements does a new handler need most?

Reading a policy wording against facts. The agent quotes the relevant clause. The handler must decide whether the facts fit it, especially exclusions and conditions. New handlers often defer to the agent's quote; teach them to read the clause themselves every time in the first fortnight.

Treating fraud flags as questions. An indicator is not an accusation. The handler decides whether to refer, and must not let a flag shape how they speak to the customer.

Spotting vulnerability. Bereavement, serious injury and financial hardship often appear in a single line of a claim form. The agent should hold such claims for a person; the handler must notice if it did not, and adjust how the claim is handled.

Knowing what the customer has already been told. The agent may have acknowledged the claim, requested documents and given a timescale. A new handler who calls the customer without reading those messages may contradict them. Reading the claim's message history first is a habit worth testing in the sandbox week.

How should corrections be recorded?

Every time the handler changes a coverage view, reserve or offer, they pick a reason: wording misread, fact missing, reserve basis wrong, vulnerability missed, or handler judgement. Reasons let the agent owner bank genuine errors into the agent's brief, sources or bounds. "Handler judgement" marks a legitimate choice so it is not mistaken for an error. The AI agent training plan template for claims handlers includes this as a module.

Which controls and evidence should onboarding leave?

• Checked decisions in week two. Evidence: both handlers named on each decision.
• Authority by value. Evidence: the dated authority level, raised in steps.
• Sandbox outcomes. Evidence: closed claims attempted and compared.
• Reasons on changes. Evidence: reason codes by handler.

What should the team leader measure?

Coverage decisions changed by the checking handler. Reserve accuracy on claims as they develop. Fraud referrals that the new handler made or missed. Vulnerability cases caught. Complaints and reopened claims in the first quarter after sign-off.

Where does it usually go wrong?

Settling at the agent's figure. A new handler sees a drafted offer, the customer is waiting, and the offer goes out unchanged. The checked week exists to break this habit.

Authority granted in one step. Handlers who move straight from supervised to full authority miss the gradual exposure to larger and stranger claims.

No exposure to complaints. A handler who has never read a complaint about an agent-drafted letter does not know what customers notice. Include a few in week one.

Collections and support teams face the same staged-authority pattern, as the plans for a new collections agent and a new customer support agent show. The wider approach is in training teams for AI agents.