Will AI replace Insurance Claims and Policy Processing Clerks?
Work in Insurance Claims and Policy Processing Clerks sits in the in-between: AI reaches some of it (~83% in theory) but is only measured doing about 15% today — part human, part machine.
O*NET-SOC 43-9041
How your 15 core tasks split
Top = what GPT-4 judged AI could speed up. Bottom = how much AI was actually used for these tasks (Anthropic's March 2026 report, usage from Aug & Nov 2025). The gap is the real story.
Back in 2023, GPT-4 judged AI could, in theory, assist with a high share of this job's tasks (~83%). By late 2025, real-world AI use had reached about 15% of its task activity (growing but still limited). The gap between that 2023 forecast and today is the real story.
Where this job sits among 738 jobs
Each dot is one of 738 U.S. jobs. Right = AI can do more of it. Up = AI is actually used more.
Read this as a range, not a verdict
The signals here partly disagree — AI's theoretical reach (~83%) and its real-world use (~15%) tell different stories. AI-risk scores also shift a lot by which model does the rating (2.7%–51.5% in one 2026 study), so this is a direction of travel, not a fixed answer.
See all 15 tasks, ratedBased on real task-level AI scores — click to collapse
- Prepare insurance claim forms or related documents, and review them for completeness.
- Post or attach information to claim file.
- Transmit claims for payment or further investigation.
- Review insurance policy to determine coverage.
- Organize or work with detailed office or warehouse records, using computers to enter, access, search or retrieve data.
- Correspond with insured or agent to obtain information or to inform them of account status or changes.
- Review and verify data, such as age, name, address, and principal sum and value of property, on insurance applications and policies.
- Compare information from application to criteria for policy reinstatement, and approve reinstatement when criteria are met.
- Transcribe data to worksheets, and enter data into computer for use in preparing documents and adjusting accounts.
- Notify insurance agent and accounting department of policy cancellation.
- Calculate amount of claim.
- Contact insured or other involved persons to obtain missing information.
- Process and record new insurance policies and claims.
- Provide customer service, such as limited instructions on proceeding with claims or referrals to auto repair facilities or local contractors.
- Examine letters from policyholders or agents, original insurance applications, and other company documents to determine if changes are needed and effects of changes.
- ⚠️ None — every core task is at least partly within AI's reach. The job won't vanish, but almost all of it changes.
How we measured this — and how fresh it is
AI's theoretical reach data: 2023
From GPTs-are-GPTs (Eloundou et al.), where GPT-4 rated how much of each task an AI tool could meaningfully speed up. This is the most recent open, commercially-usable occupation-level potential dataset — it dates to 2023. Newer multi-model re-runs exist but swing wildly (one 2026 study saw "high-risk" jobs range 2.7%–51.5% by model) and aren't openly licensed, so we show the stable 2023 baseline and pair it with newer real-world data.
Real-world AI use 2026 report
From the Anthropic Economic Index, which observes how real Claude conversations map onto each occupation's tasks. Published in Anthropic's March 2026 labor-market report, based on usage measured in Aug & Nov 2025 (Sonnet 4 / 4.5).
Task list & ratings O*NET 30.3
Tasks come from O*NET 30.3. Each task's "AI can do / speeds up / still on you" tier uses the real task-level exposure scores from GPTs-are-GPTs (E1 / E2 / E0) — not a guess from keywords.
Sources: O*NET 30.3 (CC BY 4.0) · GPTs-are-GPTs (MIT, 2023) · Anthropic Economic Index (CC BY, Aug & Nov 2025). Page compiled June 2026. "O*NET" is a trademark of the U.S. Department of Labor.
This page is for general informational purposes only and is not career, financial, or employment advice. AI exposure reflects research estimates of task overlap, not predictions about any individual's job, employer, or future employment.