A Practical AI Worker Pattern for Complex Insurance Claims
Use AI to organise claim evidence, identify gaps and prepare review without automating coverage or settlement decisions.
Intelliger Editorial Team•Jul 26, 2026Claims teams do not struggle because they lack documents. They struggle because the documents arrive in different formats, at different times and with different levels of reliability. A complex property claim may involve policy schedules, endorsements, photographs, adjuster notes, repair estimates, weather data and previous correspondence.
The strongest AI use case is not an automatic coverage decision. It is a worker that converts fragmented evidence into a reviewable claim file while keeping interpretation and customer outcome with the authorised claims professional.
Give the worker a case-preparation role
A claims-preparation worker can:
- classify incoming material and link it to the correct claim
- build a dated event chronology
- extract relevant facts with source references
- detect missing, duplicate or contradictory evidence
- retrieve the policy wording effective for the loss date
- prepare questions for the adjuster or policyholder
It may propose issues for review, but it should not present coverage, causation, liability or settlement as decided facts.
Build a claim evidence model
Before selecting a model, define the information objects in the process. At minimum, separate the insured event, policy and endorsements, insured items, claimed loss, observed damage, expert assessments, estimates, communications and decisions.
For each item, retain source, author, collection time, effective date and confidence in extraction. Photographic evidence should preserve the original file and context rather than reducing the image to a text description. Policy interpretation should always point to the exact wording used.
Use a visible chronology
Chronology is one of the highest-value outputs because it exposes gaps and contradictions quickly. The worker should distinguish the time an event occurred from the time it was reported or recorded. If two accounts disagree, show both instead of selecting the more fluent version.
A useful review screen lets the claims professional move from a timeline event to the supporting document or image in one action.
Separate checks from judgement
Some tasks can be deterministic. Dates can be compared, totals recalculated and required fields checked. Others require professional judgement, including whether evidence is persuasive, whether an exclusion applies and what a fair settlement should be.
Keep these categories visible. Deterministic checks should use controlled tools. Worker-generated observations should be labelled as recommendations. Authorised decisions should capture the person, rationale and evidence considered.
Define when the worker stops
Escalate when identity or policy matching is uncertain, the effective wording cannot be established, fraud indicators require specialist handling, vulnerability or complaints are present, expert reports conflict, reserves or settlement actions exceed limits, or the claim falls outside the pilot product.
Stopping is a capability. A worker that always produces an answer creates more review risk than one that explains what it cannot establish.
Evaluate the whole handoff
Measure evidence completeness, correct policy retrieval, chronology accuracy, contradiction detection and preparation time. Also measure the quality of escalation: did the reviewer receive the relevant documents, completed checks and a clear unresolved question?
For customer outcomes, monitor rework, reopened claims, complaints and correction rates. Do not claim improved fairness from speed alone.
Start with a contained claim type
Choose a claim type with a stable process, adequate historical cases and clear professional ownership. Run shadow cases first. Include routine files, complex files, missing evidence and out-of-scope cases. Review every error by type, not only by final outcome.
An OATI Receipt can retain a verifiable record of what the worker accessed, calculated and recommended. An OATI-ID gives the worker a stable identity across claims systems. Those records support accountability without pretending the worker owns the claim decision.