Field brief

Claims exception handling / evidence packet assembly

Start here because exception claims already expose visible friction: fragmented claim evidence, repeated follow-up, delayed routing, and weak communication traceability. AI can assemble and compare context, but coverage, settlement, denial, and escalation decisions remain human-owned.

IndustryInsurance

Decision ownerClaims adjuster

AI boundaryAssist only

Governancehigh

Why this workflow is viable first

Exception claims concentrate visible pain without requiring automation of the entire claims lifecycle.

The workflow depends on assembling evidence from known sources: claim file, policy, communications, vendor reports, and handling guidelines.

AI can prepare summaries, missing-evidence checks, and follow-up drafts while the adjuster owns coverage, settlement, denial, and escalation decisions.

Success can be measured through exception cycle time, touch count, missing-evidence rate, communication quality, and evidence completeness.

Value leakage to inspect

Fragmented claim file evidence
Manual exception triage
Repeated claimant, broker, vendor, or provider follow-up
Slow coverage or liability routing
Inconsistent handling guideline comparison

Bounded AI role

Summarize claim file
Detect missing evidence
Compare to handling guidelines
Draft claimant, broker, or vendor follow-up

Human-owned controls

AI does not decide coverage, liability, settlement, denial, SIU referral, or regulatory response.
Claims adjuster verifies summaries, evidence gaps, guideline comparisons, and communication drafts.
Authority rules determine which human owns escalation, approval, settlement, or denial.
The workflow should retain source evidence, drafts, approvals, communications, and decision rationale for audit or market conduct review.

Do not automate

Recommend settlement amount
Coverage denial or SIU referral decision

Pilot KPIs — establish baselines before the pilot starts

Measure these before the first case runs. The pilot result is the delta, not the absolute value.

daysException cycle timeAverage days from exception flag to resolution, last 30 exceptions

touchesTouch countAverage number of adjuster actions per exception case

%Missing evidence ratePercentage of exceptions with incomplete claim file on intake

%Claim file completenessPercentage of closed exceptions with required evidence on file

Governance profile

Data sensitivityconfidential

AI is permitted to

Summarize claim file and exception context into a structured packet
Detect missing evidence items against the required claim file list
Compare claim details to handling guidelines and flag exceptions
Draft claimant, broker, or vendor follow-up for adjuster review and approval
Prepare exception escalation packet for authority review

Retain for audit

Claim file evidence referenced in each AI summary
Communication drafts and adjuster approval record
Handling guideline comparison output and exceptions noted
Coverage and authority escalation decisions
Final decision and communication evidence for market conduct review

30/60/90 adoption path

Move from evidence inspection to one-team pilot before expanding the pattern.

30 daysSelect one exception type + Inspect recent exception claim files

60 daysPilot with one claims team + Add missing evidence detection

90 daysExpand to adjacent exception types + Integrate with claims workflow system

After 90 days

After claims exception is proven, the pattern extends to the full claims lifecycle, complaint handling, subrogation review, and regulatory correspondence — each shares the evidence-assembly and communication-drafting core.