AI Claim Report Review Checklist for Insurance Adjusters

Before submitting an AI-drafted claim report, verify its facts against original evidence, preserve uncertainty, check calculations and policy references, and identify missing information. This checklist is for insurance adjusters reviewing a draft—not for automating coverage, liability or settlement decisions.

The draft reads well. Dates line up. The conclusion sounds confident.

Then you open the inspection notes. They say “possible ingress.” The draft says “water entered through the roof.” Two words of uncertainty have disappeared—and the meaning has changed.

This is an illustrative failure mode, not a reported customer incident. It explains why proofreading is not enough. Before submitting an AI-assisted claim report, check whether the draft preserves the evidence, uncertainty and limits of your assignment.

Download the pre-signing review checklist — use it with any drafting tool.

Start with the assignment, not the AI output

For US claims work, check the carrier or adjusting firm's reporting instructions, your authorized role and applicable state requirements. A drafting checklist does not expand your authority. Keep the inspection narrative, repair estimate and coverage analysis distinct; reconcile shared quantities and photo references instead of assuming one document validates another.

Five checks that go beyond proofreading

1. Trace factual assertions. Pick out dates, names, measurements and quantities. Compare them with the underlying document, note or photograph—not another AI-generated summary. Flag anything without a source.
2. Check changes in certainty. Search for “caused,” “confirmed,” “all,” “no evidence” and similar decisive wording. Did the source actually justify it? Restore qualifications such as “reported,” “not inspected” or “not yet established” where needed.
3. Recalculate consequential numbers. Check units, quantities, subtotals and any depreciation, deductible or other adjustment against the applicable basis. A neatly formatted table can still contain a wrong formula or unsupported input.
4. Verify policy and regulatory references. Open the actual wording and cited source. Check the edition, jurisdiction and applicability. A plausible clause number is not evidence that the clause exists or applies.
5. Look for omissions. Compare the draft against the assignment and unresolved-issues list. Missing limitations, conflicting accounts and inaccessible areas can matter as much as incorrect sentences.

Prioritize statements that influence cause, extent, valuation or recommendations. Spot checks alone may be insufficient for a high-consequence conclusion. Decide the depth of review based on the assignment and your applicable obligations, not on how polished the prose appears.

Keep a short review record

A useful internal record identifies the report and version, the drafting system, the reviewer and date, the evidence checked, substantive corrections, unresolved items and the release decision. Keep it with the working file under your firm’s retention rules.

For the opening example, that might read: “Cause statement compared with inspection note N07. Definitive roof-ingress wording removed. Cause remains unconfirmed pending access and contractor record.” This says more than a tick beside “AI output reviewed.”

The downloadable checklist is an editorial working aid—not an official RICS form or certification. Completing it does not, by itself, establish compliance.

The decision starts before uploading

Check whether the tool is approved for the data involved. Establish what the supplier retains, who can access it, whether inputs may be used for training and how deletion works. Do not assume a paid subscription answers those questions.

A final-document check cannot replace these earlier decisions. Where your agreement or applicable requirements call for disclosure or consent, handle it before using the tool.

If you also work under RICS standards

RICS’ responsible AI standard took effect on March 9, 2026. Its key elements address governance, supplier checks, client information and recorded judgments on material AI outputs. This applies to RICS members and regulated firms within its scope—not every US insurance adjuster, and not as an IRDAI rule for India.

For concrete wording examples, read how to separate observation from cause. For the wider document structure, see our survey-report guide.

Evaluate the draft, not the promise

Review a FieldScribe AI sample report against this checklist. If you want to test your own workflow, start a 14-day trial. No credit card is required, and a first-report setup call is included. Use only authorised data; the professional review and signing decision remain yours.