Claims adjusters, appraisers, examiners, and investigators

Authorize and process claim payments

Payment authorization for approved claims is largely algorithmic: verify approval, check payment limits, process transaction. AI can handle end-to-end for standard claims with exception handling for anomalies, minimal human involvement needed beyond audit sampling.

BLS evidence: The duties list includes 'authorize payments' and examiners 'authorize appropriate payment, deny the claim, or refer the claim to an investigator.'

Review claims documentation to ensure compliance with proper guidelines and procedures

Document review for compliance is a pattern-matching task well-suited to AI. Systems can check completeness, flag missing signatures, verify policy numbers, and ensure procedural adherence faster than humans, with spot-checking sufficient for quality control.

BLS evidence: Claims examiners 'review claims after they are submitted to make sure claimants and adjusters followed proper guidelines.'

Prepare reports documenting claim findings with photographs and statements

AI can generate structured reports from templates, incorporate photos, transcribe statements, and organize findings logically. Most routine claim documentation can be auto-generated from collected data with human review for accuracy and completeness.

BLS evidence: Adjusters 'gather information—including photographs and statements, either written or recorded on audio or video—and put together a report for claims examiners to review.'

Determine appropriate claim settlement amounts based on policy coverage and damage assessment

AI excels at parsing policy terms, calculating depreciation, comparing repair estimates, and applying coverage formulas. Most straightforward claims can be settled algorithmically; human review needed primarily for disputed or high-value cases.

BLS evidence: Workers 'decide the appropriate amount the insurance company should pay' and appraisers 'estimate the cost of repairs.'

Investigate and evaluate insurance claims to determine coverage and validity

AI can analyze policy documents, compare against claim details, and flag coverage issues with high accuracy. However, complex edge cases and nuanced judgment calls about validity still benefit from human oversight, placing this in the 'AI does most autonomously with batch review' range.

BLS evidence: The page states that these workers 'investigate, evaluate, and settle insurance claims' and 'determine whether the insurance policy covers the loss claimed.'

Detect and investigate potentially fraudulent claims

AI can identify red flags (duplicate claims, suspicious patterns, metadata anomalies) and score fraud likelihood effectively. However, investigating requires synthesizing disparate evidence, conducting interviews, and making judgment calls that still need human investigators for complex cases.

BLS evidence: Workers must 'ensure that claims are not fraudulent' and 'insurance investigators handle claims in which the company suspects fraudulent or criminal activity.'

Consult with specialists such as doctors, lawyers, engineers, and accountants for expert evaluations

AI can schedule consultations, prepare briefing materials, and summarize expert reports. However, the actual consultation—explaining claim context, asking follow-up questions, and interpreting nuanced expert opinions—requires human judgment and domain knowledge.

BLS evidence: Adjusters 'may consult with other workers, such as accountants, architects, construction workers, engineers, lawyers, and physicians, who can offer a more expert evaluation of a claim.'

Interview claimants, witnesses, and other parties to gather claim information

AI can conduct structured interviews via chat or voice, extract key facts, and identify inconsistencies. However, reading body language, adapting questions based on evasiveness, and building trust in sensitive situations still require human presence, especially for contested claims.

BLS evidence: Adjusters 'interview the claimant and witnesses' and workers must 'get information from a range of people, including claimants, witnesses, and medical experts.'

Negotiate settlements with policyholders and claimants

Negotiation requires real-time reading of human emotional cues, building rapport, strategic concession-making, and handling confrontational dynamics. AI can suggest settlement ranges and talking points, but the interpersonal negotiation itself remains human-dependent.

BLS evidence: The duties list includes 'negotiate settlements' and the page states 'when the examiner approves the claim, the adjuster negotiates with the policyholder and settles the claim.'

Inspect damaged property or vehicles to assess extent of loss

Physical inspection requires on-site presence in varied, unpredictable environments (homes, accident scenes, commercial properties) with assessment of structural integrity, hidden damage, and safety hazards. AI-assisted photo analysis can support but cannot replace the physical inspection itself.

BLS evidence: Adjusters 'inspect property damage or personal injury claims' and 'might inspect a home, a business, or an automobile,' while appraisers 'inspect damaged vehicles after an accident.'

Conduct surveillance and field investigations on suspicious claims

Physical surveillance requires mobile presence in unpredictable environments, real-time decision-making about following subjects, operating vehicles, and adapting to evasive behavior. Field investigations involve door-knocking, reading situations for safety, and improvising—all beyond current AI+robotics capabilities.

BLS evidence: Investigators 'often do surveillance work' and 'may covertly watch the claimant to see if he or she does anything that would be suspicious based on injuries stated in the claim.'