A practical guide to routing and ranking incoming claims with AI while keeping every decision human.
Key takeaways
Adjudicating a claim, deciding whether and how much to pay, is a judgment call insurers rightly keep tightly controlled. Triage, deciding which claim an adjuster looks at first and flagging what's missing, is a much lower-risk task and one where AI can add real speed.
The distinction matters for how you scope a pilot and how you explain it internally: triage support is unlikely to raise the same governance questions that automated adjudication would.
A well-built triage layer reviews an incoming claim, checks it against a completeness checklist, estimates complexity based on claim type and documentation, and routes it to the right queue or adjuster, all before a human opens the file.
This means adjusters spend their time on files that are ready to be worked, rather than discovering halfway through that a document is missing or the claim belongs to a different line of business.
Write the boundary into policy: the AI ranks and routes; it does not approve, deny, or estimate a payout. This isn't just good governance, it also makes the tool easier to explain to policyholders, regulators, and your own staff.
Some insurers add a simple rule that any claim the AI can't confidently classify gets routed to a senior adjuster by default, rather than guessed at. That keeps the system honest about its own limits.
Start with your highest-volume, most standardised claim type, often auto glass or simple property claims, where the completeness rules are well understood and the stakes per claim are lower.
Track how much adjuster time is freed up and whether cycle times improve, then use that evidence, not enthusiasm, to decide whether to extend triage support to more complex claim types.
A 30-minute call is enough to tell you whether AI pays for itself here.
