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Mail Clerks and Mail Machine Operators, Except Postal Service

Occupation · SOC 43-9051.00

Prepare incoming and outgoing mail for distribution. Time-stamp, open, read, sort, and route incoming mail; and address, seal, stamp, fold, stuff, and affix postage to outgoing mail or packages. Duties may also include keeping necessary records and completed forms.

Also called: Mail Clerk · Mail Handler · Mail Machine Operator · Postal Clerk · Insert Operator · Inserter Operator · Mail Processor · Mail Reader · Mail Sorter · Addressing Machine Operator · Addressograph Operator · Advertising Inserter

Job family: Office and Administrative Support Occupations

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Download .md

A source-stamped Markdown brief of this occupation — paste it into an agent, or fetch /roles/role-43-9051-00/context.md directly.

AI work map

A fast read on where AI already shows up in this occupation, where it stays a copilot, where humans remain in the loop, and what the labor market is doing. Built from observed Claude.ai conversations mapped to O*NET tasks and from published research — measures of usage and exposure, not advice or predictions that the job is going away.

26th-percentile task overlap — yet about 6,900 openings a year (-6.6% projected, BLS) . What exposure means →

AI & job outlook

What today's research says about this occupation's exposure to AI, how AI is actually being used in it, and where employment is headed. These are positions within published studies — measures of exposure and usage, not predictions that this job will disappear.

Exposure to current AI

Each study uses its own scale, so the raw scores are not comparable across rows — the percentile (this job's rank among all U.S. occupations with data) is the comparable figure, and sizes the bars.

Measure Rank vs all occupations Percentile Score
Overall AI exposure (Felten et al.) Low 25th -0.8
LLM task exposure, γ (OpenAI / Eloundou) Moderate 34th 0.3
AI assistant applicability (Microsoft) Low 24th 0.1

OpenAI's exposure study scores tasks three ways: with a language model alone (α 0.1), with simple added tooling (β 0.2), and including AI-powered software (γ 0.3). Higher means more of the job's tasks could be done at least twice as fast — not that they will be automated away.

Most of this job's tasks can be done remotely (Dingel–Neiman), which tends to track with higher digital and AI exposure.

Mixed signals. Today's AI/LLM studies show relatively low exposure for this job, but the older (2013) Frey–Osborne work rated it higher for computerization and robotics. Different eras, different technologies — the AI measures above reflect the current state.

Historical automation estimate (2013)

A pre-LLM (2013) estimate of how automatable this job is by computerization and robotics. Shown for historical context only — it is not part of any current AI ranking.

Frey–Osborne probability 0.9 · 86th percentile among occupations · High

Job outlook

Independent U.S. Bureau of Labor Statistics employment projection for 2024–2034 — a labor-market forecast, not an AI-impact forecast.

Outlook Declining · -6.6% by 2034
Projected annual openings 6,900
Employment 2024 → 2034 67,400 → 62,900

“Annual openings” counts new jobs plus replacements for workers who leave the occupation, so it can be large even when growth is modest.

Where this work sits on the global GenAI gradient

The ILO's 2025 global study scores generative-AI exposure on the international ISCO-08 occupation system, not US SOC. Bridged through the published (and approximate, many-to-many) IBS O*NET-SOC ↔ ISCO-08 crosswalk, this US occupation corresponds to the international occupation below. Exposure here means how much of the work's tasks today's AI can attempt — task overlap, not automation, adoption, or jobs lost.

41% mean task exposure (2025)
78th percentile of 427 placed occupations
−7 pts shift 2023 → 2025
International occupation (ISCO-08) Task exposure (2025) Most tasks fall in
Mail Carriers and Sorting Clerks · 4412 41% Gradient 2

Read the whole six-band gradient on the GenAI exposure gradient page. The crosswalk is approximate: a US occupation can map to several international ones, and the ILO scores describe the international occupation, not this exact US role.

Tasks

All 29 tasks O*NET lists for this occupation, ordered by importance. Each links to its own page with AI-exposure and observed-use detail.

Work activities

Knowledge, skills & abilities

O*NET importance rating, from 1 (not important) to 5 (extremely important).

Knowledge

Customer and Personal Service 3.9
English Language 3.4
Mathematics 3.0
Law and Government 2.5
Education and Training 2.5

Abilities

Near Vision 3.4
Oral Comprehension 3.3
Written Comprehension 3.1
Information Ordering 3.1
Category Flexibility 3.1
Manual Dexterity 3.1
Finger Dexterity 3.1
Speech Recognition 3.1
Oral Expression 3.0
Problem Sensitivity 3.0
Deductive Reasoning 3.0
Arm-Hand Steadiness 3.0
Written Expression 2.9
Inductive Reasoning 2.9
Perceptual Speed 2.9
Selective Attention 2.9
Static Strength 2.9
Far Vision 2.9
Speech Clarity 2.9
Trunk Strength 2.8
Control Precision 2.6
Multilimb Coordination 2.6

Essential skills

Reading Comprehension 3.0
Speaking 3.0
Critical Thinking 3.0
Monitoring 3.0
Active Listening 2.9
Writing 2.9

Transferable skills

Time Management 3.0
Coordination 2.9
Operations Monitoring 2.9
Operation and Control 2.9
Judgment and Decision Making 2.9
Social Perceptiveness 2.8
Service Orientation 2.6

Skills in demand

Skills employers ask for in job postings for this occupation (Lightcast), with whether each is a common or specialized skill.

Showing the top 40 of 41.

Tools & technology

Example Category
Microsoft Excel Spreadsheet software Hot technology In demand
Microsoft Office software Office suite software Hot technology In demand
Microsoft Outlook Electronic mail software Hot technology In demand
Adobe Acrobat Document management software Hot technology
Microsoft Access Data base user interface and query software Hot technology
Microsoft PowerPoint Presentation software Hot technology
Microsoft Windows Operating system software Hot technology
Microsoft Word Word processing software Hot technology
Email software Electronic mail software
Financial accounting software Accounting software
Postal Explorer Mailing and shipping software
Recordkeeping software Data base user interface and query software
Web browser software Internet browser software

Work context

How characteristic each condition is of the job, on O*NET's 1–5 context scale (higher = more present in day-to-day work). Each condition links to how it varies across all occupations.

Indoors, Environmentally Controlled 5.0
Telephone Conversations 4.9
E-Mail 4.7
Frequency of Decision Making 4.7
Contact With Others 4.6
Face-to-Face Discussions with Individuals and Within Teams 4.5
Importance of Being Exact or Accurate 4.5
Determine Tasks, Priorities and Goals 4.4
Work With or Contribute to a Work Group or Team 4.3
Spend Time Using Your Hands to Handle, Control, or Feel Objects, Tools, or Controls 4.3
Importance of Repeating Same Tasks 4.3
Time Pressure 4.1
Impact of Decisions on Co-workers or Company Results 4.1
Freedom to Make Decisions 4.0
Spend Time Making Repetitive Motions 4.0
Physical Proximity 3.9
Spend Time Standing 3.8
Work Outcomes and Results of Other Workers 3.7
Written Letters and Memos 3.7
Deal With External Customers or the Public in General 3.6
Consequence of Error 3.5
Dealing With Unpleasant, Angry, or Discourteous People 3.4
Pace Determined by Speed of Equipment 3.4
Coordinate or Lead Others in Accomplishing Work Activities 3.4
Spend Time Sitting 3.3
Health and Safety of Other Workers 3.2
Spend Time Walking or Running 3.0
Spend Time Bending or Twisting Your Body 3.0
Degree of Automation 3.0
Level of Competition 3.0
Conflict Situations 2.8
Exposed to Sounds, Noise Levels that are Distracting or Uncomfortable 2.4
Exposed to Contaminants 2.1
Indoors, Not Environmentally Controlled 2.1
Public Speaking 2.0
Spend Time Kneeling, Crouching, Stooping, or Crawling 1.9
Exposed to Extremely Bright or Inadequate Lighting Conditions 1.8
Exposed to Hazardous Equipment 1.8
Exposed to Very Hot or Cold Temperatures 1.7
Spend Time Keeping or Regaining Balance 1.6

How to get in

Job zone
Zone 2 — Job Zone 1-2: Very Little to Some Preparation Needed
Education
Usually requires a high school diploma or GED, though some occupations may not.
Typical entry-level education
High school diploma or equivalent · BLS, the typical path — not a requirement
Related experience
Some occupations may need little or no previous experience; others require several months to a year of experience. For example, landscaping and groundskeeping workers might require very little training or previous experience, while agricultural equipment operators can benefit from on-the job training.
Preparation level
SVP (Below 6.0) — total schooling plus on-the-job experience.

Education of current workers

Share of people in this occupation at each level of education.

Associate's Degree (or other 2-year degree) 6.2%

Interests & work styles

The interests and personal qualities O*NET associates with people who do this work.

Career interests (Holland / RIASEC)

Conventional 6.5
Realistic 4.0
Enterprising 2.1
Social 2.0

Interest areas

Office Work 6.3
Physical/Manual Labor 3.5
Transportation/Machine Operation 1.6
Personal Service 1.5
Mechanics/Electronics 1.3
Human Resources 1.3
Accounting 1.3
Management/Administration 1.3
Sales 1.1

Work styles

Dependability 2.2
Attention to Detail 2.1
Integrity 1.1

Wages & employment

U.S. · annual wages (BLS OEWS)

$29k10th$34k25th$38kMedian$45k75th$52k90th
Annual wages by percentile — U.S. (BLS OEWS). The light band spans the 10th–90th percentile; the darker band is the middle half (25th–75th); the line is the median.
67k202463k2034 (proj.)-6.6% · Declining
Projected U.S. employment, 2024–2034 (BLS Employment Projections). A labor-market forecast for the occupation, not an AI-impact forecast.
10th percentile $29,460
25th percentile $34,440
Median (50th) $38,150
75th percentile $44,940
90th percentile $52,150
People employed 62,730

Industries that employ this occupation

Where these workers are employed, by number of jobs (national, BLS OEWS). Pay shown is the occupation's national median, not industry-specific.

Industry Workers National median pay
Administrative and Support and Waste Management and Remediation Services · Sector 19,790 $36,680
Professional, Scientific, and Technical Services · Sector 8,440 $37,210
Finance and Insurance · Sector 6,160 $41,640
Educational Services · Sector 5,020 $39,700
Manufacturing · Sector 4,850 $40,990
Information · Sector 4,420 $35,370
Newspaper Publishers · National industry 3,080 $33,650
Temporary Help Services · National industry 3,070 $38,240
Transportation and Warehousing · Sector 2,410 $37,780
Health Care and Social Assistance · Sector 1,930 $39,430
Management of Companies and Enterprises · Sector 1,760 $44,990
Wholesale Trade · Sector 820 $39,570

Where this work is most concentrated

Industries where this occupation is far more common than in the economy as a whole. The location quotient is how many times more concentrated it is here (a value of 5 means five times its economy-wide share).

Industry Concentration Workers
Newspaper Publishers · National industry 83.53× 3,080
Administrative and Support and Waste Management and Remediation Services · Sector 5.39× 19,790
Direct Health and Medical Insurance Carriers · National industry 4.43× 810
Information · Sector 3.74× 4,420
Temporary Help Services · National industry 2.85× 3,070
Finance and Insurance · Sector 2.43× 6,160
Professional, Scientific, and Technical Services · Sector 1.93× 8,440
Management of Companies and Enterprises · Sector 1.54× 1,760

Part of the Management & Entrepreneurship career cluster.

Exposure quadrant: AI task-overlap percentile vs Median pay Mail Clerks and Mail Machine Operators, Except Postal Service sits at the 26th percentile of AI task-overlap and the 9th percentile of median pay, placed here against 12 adjacent occupations on the same two axes. Lower overlap · higher pay Higher overlap · higher pay Higher overlap · lower pay Lower overlap · lower pay Mail Clerks and Mail Machine Operators, Except Postal Service Postal Service Mail Sorters, Processors, and Processing Machine Operators Shipping, Receiving, and Inventory Clerks Postal Service Clerks Data Entry Keyers AI task-overlap percentile → ↑ Median pay
AI task-overlap percentile (horizontal) vs. median-pay percentile (vertical), across all scored occupations. This occupation is highlighted; related occupations are plotted alongside it. Overlap measures shared tasks with AI, not automation.

Side-by-side comparisons place two occupations’ pay, preparation, skills, and AI exposure on the same page — same data, same scale, no forecast.

What you can do with this

Options the data surfaces for Mail Clerks and Mail Machine Operators, Except Postal Service — not advice or a forecast. Each is a real cross-link you can follow into the evidence.

Skills that travel

Capabilities this work builds that are used across many other occupations.

Paths in

How people typically prepare for this work.

Zoom out

On the global GenAI exposure gradient this work sits around the 78th percentile of 427 international occupations.

Write a report on thisheadline · factoids · citation

Mail Clerks and Mail Machine Operators, Except Postal Service show 26th-percentile AI task overlap — and about 6,900 annual U.S. openings

  • Mail Clerks and Mail Machine Operators, Except Postal Service rank in the 26th percentile (Low band) for AI task overlap across U.S. occupations — a measure of how much of the work today's AI can attempt, not how much is automated.Eloundou et al. (GPTs are GPTs) + Felten AIOE
  • The occupation is projected to see about 6,900 U.S. job openings per year (2024–34), counting growth and replacement — a labor-demand projection made independently of AI.BLS Employment Projections 2024–34
  • BLS projects employment to be declining (-6.6%) from 2024 to 2034.BLS Employment Projections 2024–34
  • Median annual pay is $38,150, across about 62,730 U.S. workers.BLS OEWS (May 2024)
Copy the whole kit
Mail Clerks and Mail Machine Operators, Except Postal Service show 26th-percentile AI task overlap — and about 6,900 annual U.S. openings

• Mail Clerks and Mail Machine Operators, Except Postal Service rank in the 26th percentile (Low band) for AI task overlap across U.S. occupations — a measure of how much of the work today's AI can attempt, not how much is automated. (Eloundou et al. (GPTs are GPTs) + Felten AIOE)
• The occupation is projected to see about 6,900 U.S. job openings per year (2024–34), counting growth and replacement — a labor-demand projection made independently of AI. (BLS Employment Projections 2024–34)
• BLS projects employment to be declining (-6.6%) from 2024 to 2034. (BLS Employment Projections 2024–34)
• Median annual pay is $38,150, across about 62,730 U.S. workers. (BLS OEWS (May 2024))

Source: Singulariki — "Mail Clerks and Mail Machine Operators, Except Postal Service". https://singulariki.com/roles/role-43-9051-00
Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.

AssetsShare imageMethodology & sourcesPress & newsroomThe newsroom

Every line is built only from figures this page already shows and cites. AI task overlap means what today's AI can attempt — not automation, job loss, or a forecast.

Sources for this page

Every figure above traces to a named public dataset and the exact release below — not hand-written opinion. See the full methodology for what each measure does and does not mean.

Data compiled June 2, 2026. Figures are estimates, not advice.

Cite this page
Plain

Singulariki. "Mail Clerks and Mail Machine Operators, Except Postal Service." Singulariki: a source-backed encyclopedia of work. Built from O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Microsoft “Working with AI” working-with-ai; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans; ILO / Gmyrek et al. GenAI exposure gradient 2025; IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022; Frey & Osborne (2013) frey-osborne-automation; Dingel & Neiman (2020) dingel-neiman-workathome. Accessed June 7, 2026. https://singulariki.com/roles/role-43-9051-00

APA

Singulariki. (2026). Mail Clerks and Mail Machine Operators, Except Postal Service. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-43-9051-00

BibTeX
@misc{singulariki-role-43-9051-00,
  title  = {Mail Clerks and Mail Machine Operators, Except Postal Service},
  author = {{Singulariki}},
  year   = {2026},
  note   = {O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Microsoft “Working with AI” working-with-ai; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans; ILO / Gmyrek et al. GenAI exposure gradient 2025; IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022; Frey & Osborne (2013) frey-osborne-automation; Dingel & Neiman (2020) dingel-neiman-workathome. Accessed June 7, 2026},
  url    = {https://singulariki.com/roles/role-43-9051-00}
}

Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.

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