Discovery field guide / Industry
How to find AI opportunities in Insurance
Where should discovery start?
Trace a claim or policy-service case from first notice through evidence collection and review. Look for repeated document reading, missing information requests, and handoffs between brokers, handlers, and specialists. Keep evidence preparation distinct from coverage, pricing, settlement, and denial decisions. The useful opportunity is a demonstrable improvement in the case journey, not merely a faster summary of an incomplete or incorrectly interpreted file.
The shared framework
Fourteen stages, from objective to portfolio.
Every guide uses this sequence to connect a business problem to an accountable investment. Revisit earlier stages when new evidence changes the assessment.
Stage 1: Business Objective
Name the outcome the organization is trying to move, so every later idea has something to be measured against.
Stage 2: Department
Locate the team that owns the objective and the work that feeds it.
Stage 3: Process
Describe how the work actually runs today: steps, handoffs, systems, and exceptions.
Stage 4: People
Capture who performs and depends on the work, and what they know that no document records.
Stage 5: Problem
State the friction in plain terms: delay, rework, error, cost, or risk, with evidence.
Stage 6: Opportunity
Frame a specific improvement that addresses the problem, not yet tied to any technology.
Stage 7: AI/Automation Fit
Compare AI, RPA, IDP, workflow automation, process redesign, and no technology change.
Stage 8: Value
Estimate benefit in the objective's own terms, with assumptions written down.
Stage 9: Feasibility
Check data, systems, skills, and change capacity needed to deliver.
Stage 10: Risk
Surface compliance, quality, security, and adoption risks and the controls they need.
Stage 11: Scoring
Rate each opportunity on the same dimensions so comparisons are consistent and explainable.
Stage 12: Prioritization
Sequence opportunities by score, dependencies, and capacity, with reasons people can challenge.
Stage 13: Investment
Match approved effort to the sequence; people with budget authority decide what gets funded.
Stage 14: Portfolio
Track opportunities over time as a living set: delivered, in flight, waiting, and retired.
Start with one observable journey
Select one product, policy jurisdiction, and recurring case type. Compare a straightforward claim with a disputed or reopened one. Assemble approved, redacted records showing the policy version, endorsements, submitted evidence, reviewer notes, and customer communications.
Where to look across departments
Claims intake and evidence follow-up
Follow how handlers identify missing loss details, organize attachments, and request specialist reports. Record which gaps delay a defensible review. A checklist or portal change may solve repeated missing fields; interpretation of variable reports is a different candidate with different failure modes.
Underwriting support and policy service
Inspect submission preparation, broker correspondence, renewal changes, and policy-document comparisons. Check where staff reconcile schedules, exclusions, and endorsements. Do not merge an administrative completeness task with a recommendation about risk acceptance simply because both occur in the same file.
Who to interview and what each person knows
Handler, adjuster, and service staff
Ask a claims handler and adjuster to explain why one case needed more evidence. Include a policy-service employee and, where appropriate, the broker-facing team. Their perspectives reveal where an apparently complete submission fails to answer the reviewer's actual question.
Coverage, complaints, and governance owners
Interview the responsible underwriting or coverage specialist, compliance owner, and complaint handler. Include document-system and privacy owners. Clarify who can approve a communication, a reserve change, or a settlement and which evidence must remain available if the outcome is challenged.
What to ask: follow the evidence
Which policy wording actually applied?
Ask how the handler verified policy dates, endorsements, insured parties, and relevant limits. Which later document changed the interpretation? Request a case where a plausible summary omitted a material exclusion. Capture how the team detects a mismatch before it reaches a customer.
Why did the file return?
Ask what the reviewer needed that the first packet lacked. Did the customer supply it already through another channel? What communications deadlines or vulnerability considerations applied? Separate effort spent finding evidence from professional judgment about causation, coverage, or settlement.
Signals of opportunity, and reasons to look elsewhere
Repeated preparation with clear file boundaries
Document organization and completeness checking may be promising when the applicable policy can be verified and reviewers can inspect source references. Similar-looking policies with different endorsements are a warning against treating document similarity as equivalent coverage.
Avoidable customer evidence requests
Repeated requests for the same information can reveal a case-management or integration problem. An AI candidate should show why interpreting or organizing existing evidence helps beyond a simple duplicate check. Lower handling time is not useful if it increases reopened claims or misses customer communications.
Industry-specific risks and constraints
Coverage and customer fairness
Incorrect interpretation can delay payment or wrongly influence a claim outcome. Relevant requirements vary by product and jurisdiction. Keep accountable professional review, explanations, and challenge routes in scope. Do not infer that an administrative trial supports autonomous denial, pricing, or fraud accusations.
Sensitive and adversarial evidence
Claims can contain medical, financial, and third-party information, as well as contradictory or misleading documents. Confirm lawful use, access, retention, and provider arrangements with responsible owners. Assess whether source instructions or document artifacts could manipulate an evidence-processing tool.
How to evaluate what you find
Test material omissions and policy mismatch
Use permissioned cases with amendments, multiple policy years, missing pages, and disputed facts. Measure correct source selection, material omissions, abstention, and handler corrections. A draft that reads well but loses an endorsement or uncertainty should fail even if its broad summary resembles the final file.
Measure the full case cost
Compare preparation, specialist review, follow-up, and reopened-file effort. Include quality checks and ongoing changes to policy forms. Establish which outcomes the pilot can demonstrate and which, such as improved loss results, require a separate, longer and carefully designed evaluation.
How to compare, prioritize, and invest
Start with a reviewable file task
Prefer a bounded claims-packet or submission-preparation trial in one product line. Fix policy-version identification and document access first if they are unreliable. Do not give a candidate settlement or coverage authority as an incidental extension of a successful administrative task.
Compare service and defensibility
Rank opportunities by less duplicated evidence collection, clearer review packets, customer service quality, and usable handler capacity. Include compliance and correction costs. Stop on material source omissions or harmful communications; accountable insurance leaders decide when the evidence supports expansion.
Turn observations into a comparable opportunity record
Describe the current process before naming a solution. Record the trigger, owner, input, steps, handoffs, systems, output, and exception path. Separate what you observed from what someone recalled and what you still need to verify. A vivid interview story is a useful lead, not proof that every case behaves the same way. Validate it against a sample of ordinary work and difficult exceptions, with the limits of that sample made explicit.
Measure active work separately from waiting. Note the observation period, case mix, frequency, and source of each estimate. Include the receiving team's effort, checking, correction, and escalation so a local improvement does not merely transfer work. Describe the outcome in operational terms before attaching a monetary value. Capacity released is not automatically a budget saving; explain what can actually change and which manager has authority to make that change.
Compare interventions before selecting a tool
If a rule is explicit and the input is structured, test ordinary workflow automation first. If the task repeats a stable interface action, examine RPA and an integration alternative. If the difficulty is reading documents, consider IDP with source checks. AI may help where language or variable evidence requires interpretation, but its output still needs a task-specific acceptance standard. Process redesign or no technology change may be the right answer when policy, ownership, or an unnecessary step causes the problem.
Write down why each alternative would or would not address the observed cause. Do not compare a carefully controlled AI proposal with an artificially weak version of the current process. Include data repair, access approval, integration, training, review, and upkeep in each feasible option. An unavailable prerequisite is a reason to sequence work or pause, not a detail to hide inside a feasibility score.
Agree on a decision, not just a demonstration
Before a trial, name the business owner, evaluator, permitted data, review boundary, and person who can stop it. Define acceptable outputs and failures that must trigger escalation. Use examples held out from development, including missing information and uncommon cases. Compare the complete task with the baseline, including human verification and downstream consequences. Preserve the evidence behind the result so another owner can challenge the conclusion.
Keep value, feasibility, risk, and evidence confidence visible separately. A candidate with an attractive benefit estimate is not ready if its owner cannot obtain the data or operate the controls. Record the decision to investigate, pilot, wait, reject, or retire, with a reason and a condition for revisiting it. After delivery, compare observed results with assumptions rather than leaving the original estimate in the portfolio as fact.
Use the evaluation guide for the evidence standard and the prioritization guide to compare qualified candidates. Your leaders make funding decisions; a score or a discovery tool supplies structured evidence, not investment authority.
Continue through the discovery framework
Browse all departments and industriesRelated practice notes
For focused interview techniques, examples, and scoring detail alongside this field guide:
Map an insurance case in IntakeOS
Bring a sanitized claim or policy-service path, the evidence gaps, and the approval boundary. Use IntakeOS qualification to compare the opportunity with process and system repairs before choosing a tool.
IntakeOS supports structured interviews, qualification, and comparison; it does not make funding decisions or replace professional review. Learn about VARA, review the trust page, or explore the platform before sharing sensitive information.
Explore discovery in an IntakeOS demo