High AI Risk Declining

Postal service mail sorters, processors, and processing machine operators

SOC Code: 43-5053

Postal service mail sorters, processors, and processing machine operators carries a 45% AI exposure score (High automation risk), with a median annual wage of $56,530 and -8.4% projected employment growth from 2024 to 2034 (BLS), affecting approximately 106,400 workers. Full task breakdown, skills, and employer data are below.

AI Exposure Score
45% High
Above-average exposure

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

Projected Growth
-8.4%
Bottom 10% growth
2024–2034 (BLS)
-8,900 jobs
Median Annual Wage
$56,530
Typical pay
BLS May 2024
How wage figures are sourced →
The verdict

At 45% AI exposure, Postal service mail sorters, processors, and processing machine operators sits 8 points above the 37.2% average across 832 U.S. occupations - more exposed than 81% of them. Most of its core tasks still require human judgment.

45%
AI exposure
Top 19%
most exposed
-8.4%
Job growth 2024–34
$56,530
Median wage
F

Career outlook score

25/100

Postal service mail sorters, processors, and processing machine operators, 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 D $56,530

    Annual median wage, percentile rank vs all tracked occupations

  • Projected growth F -8.4%

    Projected employment change, 2024-2034, BLS Employment Projections

  • AI exposure (inverted) F 45% exposure

    Lower O*NET task-automability scores lower risk; this dimension scores security, not exposure

Employment vs AI 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).

4.3M
Home health and personal care aides employment (#1)
#392
Home health and personal care aides AI rank
95%
Bookkeeping, accounting, and auditing clerks AI exposure (#1)
#17
Bookkeeping, accounting, and auditing clerks employment rank

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 Postal service mail sorters, processors, and processing machine operators in the High band.

Credential × growth standing

Open entry on a declining BLS line

Typical entry is No credential (109/832) while growth is Declining (111/832). This is the crowded high-risk corner of the map - automation and headcount pressure compound without a degree moat.

Where Postal service mail sorters, processors, and processing machine operators sits among all occupations

AI-exposure score distribution across 832 U.S. occupations (O*NET task analysis). This occupation is marked in rose.

Where Postal service mail sorters, processors, and processing machine operators sits by AI exposure

AI-exposure score distribution across U.S. occupations (O*NET task analysis)

45% Higher than most higher than 81% 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.

Postal service mail sorters, processors, and processing machine operators vs. its occupational neighbors

AI exposure (horizontal) vs projected 2024–2034 growth (vertical) for occupations in the same SOC group. Postal service mail sorters, processors, and processing machine operators 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%-9.0%-5.6%-2.1%1.4%4.8%AI exposure (%) →Projected growth (%) →Postal service mail , AI exposure (%) →: 45% · Projected growth (%) →: -8.4%Postal service mail Customer service rep, AI exposure (%) →: 56% · Projected growth (%) →: -5.5%Customer service repOffice clerks, AI exposure (%) →: 84% · Projected growth (%) →: -6.7%Office clerksSecretaries, AI exposure (%) →: 77% · Projected growth (%) →: -1.6%SecretariesBookkeeping, AI exposure (%) →: 95% · Projected growth (%) →: -5.8%BookkeepingFirst-line superviso, AI exposure (%) →: 55% · Projected growth (%) →: -0.3%First-line supervisoReceptionists, AI exposure (%) →: 76% · Projected growth (%) →: 0%ReceptionistsShipping, AI exposure (%) →: 60% · Projected growth (%) →: -7.7%ShippingMedical secretaries, AI exposure (%) →: 80% · Projected growth (%) →: 4.2%Medical secretariesExecutive secretarie, AI exposure (%) →: 83% · Projected growth (%) →: -1.6%Executive secretarieBilling, AI exposure (%) →: 88% · Projected growth (%) →: -0.4%BillingProduction, AI exposure (%) →: 69% · Projected growth (%) →: -1.8%Production

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

Employment Projections

106,400
Employment 2024
97,500
Projected 2034
-8.4%
Change (%)
-8,900
Change (jobs)

Where This Score Comes From

Postal service mail sorters, processors, and processing machine operators's 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 43-5053) 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 Postal service mail sorters, processors, and processing machine operators 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 Postal service mail sorters, processors, and processing machine operators. Adjacent occupations shown further down offer lateral moves that preserve industry knowledge while potentially reducing exposure.

Education & Entry Requirements

Typical Education
No formal educational credential
Work Experience
None
On-the-Job Training
Short-term on-the-job training

Top Tasks (O*NET)

  1. 1. Direct items according to established routing schemes, using computer-controlled keyboards or voice-recognition equipment.
  2. 2. Check items to ensure that addresses are legible and correct, that sufficient postage has been paid or the appropriate documentation is attached, and that items are in a suitable condition for processing.
  3. 3. Clear jams in sorting equipment.
  4. 4. Bundle, label, and route sorted mail to designated areas, depending on destinations and according to established procedures and deadlines.
  5. 5. Operate various types of equipment, such as computer scanning equipment, addressographs, mimeographs, optical character readers, and bar-code sorters.
  6. 6. Move containers of mail, using equipment, such as forklifts and automated "trains".
  7. 7. Open and label mail containers.
  8. 8. Load and unload mail trucks, sometimes lifting containers of mail onto equipment that transports items to sorting stations.
  9. 9. Sort odd-sized mail by hand, sort mail that other workers have been unable to sort, and segregate items requiring special handling.
  10. 10. Distribute incoming mail into the correct boxes or pigeonholes.

Key Skills Required

  • Monitoring
  • Reading Comprehension
  • Speaking
  • Critical Thinking
  • Coordination
  • Active Listening
  • Operations Monitoring
  • Judgment and Decision Making
  • Time Management
  • Social Perceptiveness

Knowledge Areas

  • English Language
  • Production and Processing
  • Customer and Personal Service
  • Administrative
  • Administration and Management
  • Public Safety and Security
  • Transportation
  • Computers and Electronics
  • Education and Training
  • Mathematics

Frequently Asked Questions

Will AI replace Postal service mail sorters, processors, and processing machine operators?

Postal service mail sorters, processors, and processing machine operators has an AI exposure score of 45%, indicating a 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 Postal service mail sorters, processors, and processing machine operators?

According to BLS Employment Projections 2024-2034, Postal service mail sorters, processors, and processing machine operators is projected to decline by 8.4% over the decade. Current employment stands at approximately 106,400 workers.

What skills are needed for Postal service mail sorters, processors, and processing machine operators?

Key skills for Postal service mail sorters, processors, and processing machine operators include Monitoring, Reading Comprehension, Speaking, and others. Typical entry-level education is No formal educational credential.

How much do Postal service mail sorters, processors, and processing machine operators earn?

The median annual wage for Postal service mail sorters, processors, and processing machine operators is $56,530, 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 Postal service mail sorters, processors, and processing machine operators?

The typical entry-level education for Postal service mail sorters, processors, and processing machine operators is No formal educational credential. Employers generally expect None of related work experience. On-the-job training typically involves Short-term on-the-job training. Requirements can vary by employer and specialization.

Which companies employ Postal service mail sorters, processors, and processing machine operators?

Postal service mail sorters, processors, and processing machine operators 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

2.3
out of 5.0

High automation risk based on 10 analyzed tasks. A moderate share of tasks may be augmented by AI tools.

Nationwide occupations with similar workforce profiles

Two data-derived peer sets for Postal service mail sorters, processors, and processing machine operators: AI-exposure neighbors and BLS 2034 growth neighbors (distinct comparison neighborhoods, cross-occupation).

Similar AI exposure score

Nearest O*NET task-automability scores nationwide (45% here).

Similar projected growth (2024–2034)

Nearest BLS employment change rates nationwide (-8.4% here).

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.

What to do with this

Use Postal service mail sorters, processors, and processing machine operators' numbers above to compare, not just read in isolation.

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).

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.

Sources: BLS Employment Projections 2024-2034, O*NET Database 30.0.