Very High AI Risk Slow Growth

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.

AI Exposure Score
69% Very High

Proportion of tasks susceptible to AI automation (O*NET analysis)

Projected Growth
-3.7%
2024–2034 (BLS)
-9,500 jobs
Median Annual Wage
$48,450
BLS May 2024
How wage figures are sourced →
The verdict

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.

69%
AI exposure
Top 3%
most exposed
-3.7%
Job growth 2024–34
$48,450
Median wage

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.

AI exposure distribution - Insurance claims and policy processing clerks marked 1 occupations at 0–10% 1 0 43 occupations at 10–20% 43 10 184 occupations at 20–30% 184 20 332 occupations at 30–40% 332 30 158 occupations at 40–50% 158 40 64 occupations at 50–60% 64 50 29 occupations at 60–70% 29 60 15 occupations at 70–80% 15 70 5 occupations at 80–90% 5 80 1 occupations at 90–100% 1 90 AI exposure (%) →
Top 3% by AI exposure Higher AI exposure than 97% of all 832 occupations.

Insurance claims and policy processing clerks has ai exposure of 69%. Distribution: 1 occupations at 0-10%; 43 occupations at 10-20%; 184 occupations at 20-30%; 332 occupations at 30-40%; 158 occupations at 40-50%; 64 occupations at 50-60%; 29 occupations at 60-70%; 15 occupations at 70-80%; 5 occupations at 80-90%; 1 occupations at 90-100%.

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.

Future-proofGrowing but exposedStable, lower-AIMost at risk34.1%50.1%66%82.0%97.9%-8.3%-5.0%-1.8%1.5%4.8%AI exposure (%) →Projected growth (%) →Insurance claimsCustomer service repOffice clerksSecretariesBookkeepingFirst-line supervisoReceptionistsShippingMedical secretariesExecutive secretarieBillingProduction

Source: BLS Employment Projections 2024–2034 (growth) and O*NET (AI-exposure analysis by PlainWorkforce).

Employment Projections

256,700
Employment 2024
247,200
Projected 2034
-3.7%
Change (%)
-9,500
Change (jobs)

Occupation Insight

Insurance claims and policy processing clerks (SOC 43-9041) carries an AI exposure score of 69%, placing it in the Very High automation-risk tier. This score is computed from O*NET Database 30.0 task-level analysis, where each task an 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 economic context matters alongside the risk score. BLS counted approximately 256,700 workers in this occupation in 2024, and projects a -3.7% change through 2034 - a decline that often compounds with high AI exposure to create displacement headwinds. Median annual compensation stands at $48,450, reflecting both skill scarcity and the value employers place on the tasks that remain difficult to automate. Entry typically requires High school diploma or equivalent, plus None of related experience.

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. Pair the AI exposure score with the BLS employment projection and wage percentiles above for a complete career assessment.

Education & Entry Requirements

Typical Education
High school diploma or equivalent
Work Experience
None
On-the-Job Training
Moderate-term on-the-job training

Top Tasks (O*NET)

  1. 1. Prepare insurance claim forms or related documents, and review them for completeness.
  2. 2. Pay small claims.
  3. 3. Calculate amount of claim.
  4. 4. Post or attach information to claim file.
  5. 5. Transmit claims for payment or further investigation.
  6. 6. Contact insured or other involved persons to obtain missing information.
  7. 7. Review insurance policy to determine coverage.
  8. 8. Process and record new insurance policies and claims.
  9. 9. Process, prepare, and submit business or government forms, such as submitting applications for coverage to insurance carriers.
  10. 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

3.5
out of 5.0

Very High automation risk based on 10 analyzed tasks. A majority of tasks in this occupation are susceptible to AI automation.

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).

Data sourced from official public datasets. See our methodology for details. Retrieved and formatted by PlainWorkforce Editorial

Every figure on PlainWorkforce is rendered directly from BLS/O*NET source data, no number is typed in by an editor. See our editorial standards & corrections policy, the methodology behind these figures, or report a data error. Data current as of BLS Employment Projections 2024-2034.