Insurance claims and policy processing clerks
SOC Code: 43-9041
Insurance claims and policy processing clerks carries a 69% AI exposure score (Very High automation risk), with a median annual wage of $48,450 and -3.7% projected employment growth from 2024 to 2034 (BLS), affecting approximately 256,700 workers. Full task breakdown, skills, and employer data are below.
Proportion of tasks susceptible to AI automation (O*NET analysis)
At 69% AI exposure, Insurance claims and policy processing clerks sits 32 points above the 37.2% average across 832 U.S. occupations - more exposed than 97% of them. Most of its core tasks still require human judgment.
Career outlook score
18/100
Insurance claims and policy processing clerks, weighted across 3 of 3 tracked dimensions
A weighted composite of median wage, projected growth, and AI-automation security (inverted exposure), each benchmarked against every other tracked occupation. It describes this occupation's standing across those three dimensions, not a guarantee of future outcomes.
- Median wage F $48,450
Annual median wage, percentile rank vs all tracked occupations
- Projected growth F -3.7%
Projected employment change, 2024-2034, BLS Employment Projections
- AI exposure (inverted) F 69% exposure
Lower O*NET task-automability scores lower risk; this dimension scores security, not exposure
Home health and personal care aides is #1 of 832 occupations by employment (4.3M, AI exposure rank #392 at 35%) vs. Bookkeeping, accounting, and auditing clerks #1 by AI task exposure (95%, employment rank #17 at 1.6M).
Automation-risk inventory
Exclusive cut of 832 occupations by PlainWorkforce automation-risk band. Orthogonal to the continuous AI-exposure distribution chart below and to this occupation's single risk badge, this is the corpus band mix, with Insurance claims and policy processing clerks in the Very High band.
Credential × growth standing
Open entry with non-declining BLS pace
Insurance claims and policy processing clerks keeps an HS / some college bar (333 of 832) and sits in Slow growth (245 of 832). Lower formal gates with a non-shrinking employment line - skill and AI desks matter more than credentials here.
Where Insurance claims and policy processing clerks sits among all occupations
AI-exposure score distribution across 832 U.S. occupations (O*NET task analysis). This occupation is marked in rose.
Where Insurance claims and policy processing clerks sits by AI exposure
AI-exposure score distribution across U.S. occupations (O*NET task analysis)
69% Higher than most higher than 97% of 832 occupations
Occupations, banded by AI-exposure score
Each bar is a band; taller bars hold more occupations. The dashed line + filled bar mark this entry. Hover or tap any bar for its full count and share, and where it sits relative to this entry.
Source O*NET task data (U.S. Department of Labor) · BLS 2024–2034
Source: O*NET task data (U.S. Department of Labor); AI-exposure scores are PlainWorkforce's analysis. As of BLS 2024–2034.
Insurance claims and policy processing clerks vs. its occupational neighbors
AI exposure (horizontal) vs projected 2024–2034 growth (vertical) for occupations in the same SOC group. Insurance claims and policy processing clerks is marked in rose; the top-left corner is the most future-proof.
Source: BLS Employment Projections 2024–2034 (growth) and O*NET (AI-exposure analysis by PlainWorkforce).
Employment Projections
Where This Score Comes From
Insurance claims and policy processing clerks's Very High automation-risk tier is computed from O*NET Database 30.0 task-level analysis, where each documented task the occupation performs is evaluated against current generative AI, robotic process automation, and machine-learning capabilities. A score in the 40–70% range indicates meaningful automation pressure on specific task categories, but the role as a whole still requires human judgment for coordination, exception handling, or client interaction.
The employment, wage, and education figures above come from a second, separate federal source: BLS Employment Projections 2024–2034, matched to the O*NET task data by Standard Occupational Classification (SOC 43-9041) code, with the wage figure cross-validated against the BLS Occupational Employment and Wage Statistics (OEWS) May 2024 survey. BLS figures are presented exactly as published, with no adjustment on our part; the SOC-code match is what lets Insurance claims and policy processing clerks be compared directly against every other tracked occupation on the same basis, not just roles that happen to share a job title.
For career planners, this profile should be read alongside the task, skill, and knowledge breakdowns below and the list of employers whose workforce composition includes Insurance claims and policy processing clerks. Adjacent occupations shown further down offer lateral moves that preserve industry knowledge while potentially reducing exposure.
Education & Entry Requirements
Top Tasks (O*NET)
- 1. Prepare insurance claim forms or related documents, and review them for completeness.
- 2. Pay small claims.
- 3. Calculate amount of claim.
- 4. Post or attach information to claim file.
- 5. Transmit claims for payment or further investigation.
- 6. Contact insured or other involved persons to obtain missing information.
- 7. Review insurance policy to determine coverage.
- 8. Process and record new insurance policies and claims.
- 9. Process, prepare, and submit business or government forms, such as submitting applications for coverage to insurance carriers.
- 10. Organize or work with detailed office or warehouse records, using computers to enter, access, search or retrieve data.
Key Skills Required
- Reading Comprehension
- Time Management
- Speaking
- Active Listening
- Critical Thinking
- Writing
- Social Perceptiveness
- Coordination
- Service Orientation
- Monitoring
Knowledge Areas
- Customer and Personal Service
- Administrative
- English Language
- Computers and Electronics
- Mathematics
- Administration and Management
- Communications and Media
- Production and Processing
- Law and Government
- Economics and Accounting
Frequently Asked Questions
Will AI replace Insurance claims and policy processing clerks?
Insurance claims and policy processing clerks has an AI exposure score of 69%, indicating a very high level of automation risk. Some tasks in this role can be augmented or partially automated by AI, but core responsibilities require human judgment.
What is the job outlook for Insurance claims and policy processing clerks?
According to BLS Employment Projections 2024-2034, Insurance claims and policy processing clerks is projected to decline by 3.7% over the decade. Current employment stands at approximately 256,700 workers.
What skills are needed for Insurance claims and policy processing clerks?
Key skills for Insurance claims and policy processing clerks include Reading Comprehension, Time Management, Speaking, and others. Typical entry-level education is High school diploma or equivalent.
How much do Insurance claims and policy processing clerks earn?
The median annual wage for Insurance claims and policy processing clerks is $48,450, according to BLS Occupational Employment and Wage Statistics (May 2024). Actual earnings vary by location, experience, industry, and employer. The BLS publishes detailed wage percentiles by region in its Occupational Employment and Wage Statistics program.
What education is required for Insurance claims and policy processing clerks?
The typical entry-level education for Insurance claims and policy processing clerks is High school diploma or equivalent. Employers generally expect None of related work experience. On-the-job training typically involves Moderate-term on-the-job training. Requirements can vary by employer and specialization.
Which companies employ Insurance claims and policy processing clerks?
Insurance claims and policy processing clerks roles exist across many industries and employers. Workforce composition is estimated from BLS industry-occupation employment distributions matched to SEC-registered public companies.
AI Exposure Rating
Very High automation risk based on 10 analyzed tasks. A majority of tasks in this occupation are susceptible to AI automation.
Nationwide occupations with similar workforce profiles
Two data-derived peer sets for Insurance claims and policy processing clerks: AI-exposure neighbors and BLS 2034 growth neighbors (distinct comparison neighborhoods, cross-occupation).
Similar AI exposure score
Nearest O*NET task-automability scores nationwide (69% here).
- Compliance officers · AI exposure 69%
- Life, physical, and social science technicians, all other · AI exposure 69%
- Loan officers · AI exposure 69%
- Production, planning, and expediting clerks · AI exposure 69%
Similar projected growth (2024–2034)
Nearest BLS employment change rates nationwide (-3.7% here).
- Computer user support specialists · growth -3.7%
- Molding, coremaking, and casting machine setters, operators, and tenders, metal and plastic · growth -3.8%
- News analysts, reporters, and journalists · growth -3.9%
- Postal service clerks · growth -3.5%
Peers are nearest-neighbor matches on published BLS + O*NET metrics among occupations with ≥10,000 workers in 2024; corpus ranks above sort the full tracked set.
Related Occupations
Showing 6 of 24 occupations with a comparable automation-risk profile.
What to do with this
Use Insurance claims and policy processing clerks' numbers above to compare, not just read in isolation.
- Compare Insurance claims and policy processing clerks side by side against another occupation on wage, growth, and AI exposure. Workforce comparison tool
- Understand how the AI exposure score above is actually calculated before treating it as a verdict. Reading AI exposure scores
- See the full ranked list of occupations with the lowest automation exposure nationwide. Safest occupations from AI
AI exposure scores estimate task automatability from O*NET data; they are not a certainty of job loss, and BLS growth projections are estimates, not guarantees.
Data sources: Bureau of Labor Statistics Employment Projections 2024–2034 and O*NET Database 30.0. Employment figures are rounded. Wage data from BLS Occupational Employment Statistics (OES).