Occupation · SOC 43-9061.00
Perform duties too varied and diverse to be classified in any specific office clerical occupation, requiring knowledge of office systems and procedures. Clerical duties may be assigned in accordance with the office procedures of individual establishments and may include a combination of answering telephones, bookkeeping, typing or word processing, office machine operation, and filing.
Also called: Clerk · Office Assistant · Office Clerk · Office Services Specialist · Administrative Clerk (Admin Clerk) · Clerical Aide · Clerical Assistant · General Clerk · Office Support Assistant · Administration Clerk · Administrative Support Specialist · Administrative Technician (Admin Tech)
Job family: Office and Administrative Support Occupations
A source-stamped Markdown brief of this occupation — paste it into an agent, or fetch
/roles/role-43-9061-00/context.md directly.
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.
Task areas most often handled directively in observed AI conversations — candidates to delegate with light review.
Task areas where people work with AI — iterating, learning, or checking — staying in the loop rather than handing the task off.
Task areas where a human was still judged necessary in a large share of observed conversations — not a safety ruling, an observed-need signal.
The capabilities O*NET rates most important for this occupation — the human ground the work is built on.
See all skills →Independent published positions, read together — not a forecast.
73rd-percentile task overlap — yet about 282,400 openings a year (-6.7% projected, BLS), and observed AI use leans 3653% copilot, not hand-off (AEI) . What exposure means →
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.
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.) High | 73rd | 1.0 | |
| LLM task exposure, γ (OpenAI / Eloundou) Moderate | 64th | 0.8 | |
| AI assistant applicability (Microsoft) High | 78th | 0.2 |
OpenAI's exposure study scores tasks three ways: with a language model alone (α 0.4), with simple added tooling (β 0.6), and including AI-powered software (γ 0.8). 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.
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 1.0 · 91st percentile among occupations · High
Among measured AI assistant conversations mapped to this occupation (Anthropic Economic Index, 2026-01-15), these task types came up most. These are shares of observed AI conversations — not shares of the job, of worker time, or of what could be automated.
| Troubleshoot problems involving office equipment, such as computer hardware and software. | 65.5% | |
| Communicate with customers, employees, and other individuals to answer questions, disseminate or explain information, take orders, and address complaints. | 4.7% | |
| Process and prepare documents, such as business or government forms and expense reports. | 3.8% | |
| Answer telephones, direct calls, and take messages. | 2.6% | |
| Operate office machines, such as photocopiers and scanners, facsimile machines, voice mail systems, and personal computers. | 2.3% | |
| Review files, records, and other documents to obtain information to respond to requests. | 2.1% |
Independent U.S. Bureau of Labor Statistics employment projection for 2024–2034 — a labor-market forecast, not an AI-impact forecast.
| Outlook | Declining · -6.7% by 2034 |
| Projected annual openings | 282,400 |
| Employment 2024 → 2034 | 2,646,000 → 2,468,200 |
“Annual openings” counts new jobs plus replacements for workers who leave the occupation, so it can be large even when growth is modest.
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.
| International occupation (ISCO-08) | Task exposure (2025) | Most tasks fall in |
|---|---|---|
| General Office Clerks · 4110 | 60% | Gradient 4 |
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.
How people actually apply AI to this occupation's tasks, from Claude.ai (Free and Pro) conversations in the Anthropic Economic Index, 2026-01-15. This is one AI assistant's consumer sample — not all AI, not the whole workforce. Autonomy and the collaboration mix are model-rated estimates; figures below the sample floor are hidden.
| Augmentation vs. automation | 36.5% working with AI · 58.8% handed to AI |
| Most common way people use AI here | Feedback loop · AI does it, then adjusts from your feedback |
| Typical AI autonomy | 3.0 / 5 · higher = AI acts more independently |
| Used for work (vs. personal / coursework) | 37.3% |
The role's most common tasks in AI conversations, each tagged with how people work with the AI on it. “Usage” is the share of observed conversations, not of the job.
| Task | How | Usage |
|---|---|---|
| Troubleshoot problems involving office equipment, such as computer hardware and software. | Feedback loop | 113.6% |
| Process and prepare documents, such as business or government forms and expense reports. | Directive | 4.5% |
| Complete work schedules, manage calendars, and arrange appointments. | Directive | 2.7% |
| Operate office machines, such as photocopiers and scanners, facsimile machines, voice mail systems, and personal computers. | Learning | 2.0% |
| Prepare meeting agendas, attend meetings, and record and transcribe minutes. | Iteration | 1.1% |
| Answer telephones, direct calls, and take messages. | none | 1.0% |
| Review files, records, and other documents to obtain information to respond to requests. | Directive | 0.9% |
| Communicate with customers, employees, and other individuals to answer questions, disseminate or explain information, take orders, and address complaints. | Iteration | 0.7% |
Tasks where the model most often judged that a person remained necessary — a useful read on the current boundary, not a guarantee.
| Complete work schedules, manage calendars, and arrange appointments. | 100.0% | |
| Operate office machines, such as photocopiers and scanners, facsimile machines, voice mail systems, and personal computers. | 99.5% | |
| Prepare meeting agendas, attend meetings, and record and transcribe minutes. | 99.1% | |
| Answer telephones, direct calls, and take messages. | 99.0% | |
| Communicate with customers, employees, and other individuals to answer questions, disseminate or explain information, take orders, and address complaints. | 98.6% | |
| Process and prepare documents, such as business or government forms and expense reports. | 98.0% |
Example prompts phrased from the tasks people most often delegate to AI in this occupation (Anthropic Economic Index). Each shows the underlying measured task and its share of observed AI use. They are suggested phrasings of real tasks — starting points, not endorsed instructions.
Help me troubleshoot problems involving office equipment, such as computer hardware and software. From: Troubleshoot problems involving office equipment, such as computer hardware and software. · 113.6% of measured AI use · feedback loop
Help me process and prepare documents, such as business or government forms and expense reports. From: Process and prepare documents, such as business or government forms and expense reports. · 4.5% of measured AI use · directive
Help me complete work schedules, manage calendars, and arrange appointments. From: Complete work schedules, manage calendars, and arrange appointments. · 2.7% of measured AI use · directive
Help me operate office machines, such as photocopiers and scanners, facsimile machines, voice mail systems, and personal computers. From: Operate office machines, such as photocopiers and scanners, facsimile machines, voice mail systems, and personal computers. · 2.0% of measured AI use · learning
All 21 tasks O*NET lists for this occupation, ordered by importance. Each links to its own page with AI-exposure and observed-use detail.
O*NET importance rating, from 1 (not important) to 5 (extremely important).
| Administrative | 4.2 | |
| English Language | 3.8 | |
| Customer and Personal Service | 3.4 | |
| Administration and Management | 3.0 | |
| Computers and Electronics | 2.9 | |
| Mathematics | 2.7 |
| Oral Expression | 3.9 | |
| Oral Comprehension | 3.8 | |
| Written Comprehension | 3.8 | |
| Written Expression | 3.6 | |
| Near Vision | 3.4 | |
| Speech Recognition | 3.4 | |
| Speech Clarity | 3.4 | |
| Problem Sensitivity | 3.1 | |
| Information Ordering | 3.1 | |
| Deductive Reasoning | 3.0 | |
| Inductive Reasoning | 3.0 | |
| Category Flexibility | 3.0 | |
| Selective Attention | 3.0 | |
| Time Sharing | 2.9 | |
| Fluency of Ideas | 2.8 | |
| Mathematical Reasoning | 2.8 | |
| Far Vision | 2.8 | |
| Number Facility | 2.6 |
| Reading Comprehension | 3.8 | |
| Active Listening | 3.8 | |
| Speaking | 3.6 | |
| Writing | 3.1 | |
| Critical Thinking | 3.0 | |
| Monitoring | 2.9 | |
| Active Learning | 2.8 |
| Social Perceptiveness | 3.0 | |
| Coordination | 3.0 | |
| Service Orientation | 3.0 | |
| Time Management | 3.0 | |
| Instructing | 2.8 | |
| Judgment and Decision Making | 2.8 | |
| Persuasion | 2.6 | |
| Negotiation | 2.6 | |
| Complex Problem Solving | 2.6 |
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 57.
Showing the top 40 of 59.
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.
What to study: Business, Management, Marketing, and Related Support Services . Fields of study crosswalked to this occupation (NCES CIP–SOC), not a requirement.
Share of people in this occupation at each level of education.
| High School Diploma | 40.6% | |
| Associate's Degree (or other 2-year degree) | 36.4% | |
| Some College Courses | 14.7% | |
| Post-Secondary Certificate | 6.5% | |
| Less than a High School Diploma | 1.5% | |
| Bachelor's Degree | 0.2% |
The interests and personal qualities O*NET associates with people who do this work.
| Conventional | 6.8 | |
| Enterprising | 3.2 | |
| Social | 3.1 | |
| Realistic | 2.9 | |
| Investigative | 1.9 |
| Office Work | 6.8 | |
| Accounting | 3.4 | |
| Personal Service | 2.2 | |
| Human Resources | 2.1 | |
| Management/Administration | 1.9 | |
| Health Care Service | 1.7 | |
| Finance | 1.6 | |
| Information Technology | 1.6 |
| Dependability | 2.4 | |
| Attention to Detail | 2.1 | |
| Cooperation | 1.6 |
U.S. · annual wages (BLS OEWS)
| 10th percentile | $29,120 |
| 25th percentile | $35,350 |
| Median (50th) | $43,630 |
| 75th percentile | $52,560 |
| 90th percentile | $63,840 |
| People employed | 2,510,550 |
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 |
|---|---|---|
| Educational Services · Sector | 304,860 | $39,330 |
| Health Care and Social Assistance · Sector | 289,710 | $42,680 |
| Construction · Sector | 259,930 | $45,840 |
| Administrative and Support and Waste Management and Remediation Services · Sector | 206,480 | $41,300 |
| Professional, Scientific, and Technical Services · Sector | 197,040 | $44,300 |
| Retail Trade · Sector | 156,950 | $38,240 |
| Wholesale Trade · Sector | 132,290 | $44,610 |
| Manufacturing · Sector | 130,140 | $46,000 |
| Other Services (except Public Administration) · Sector | 121,170 | $40,070 |
| Finance and Insurance · Sector | 112,260 | $45,560 |
| Real Estate and Rental and Leasing · Sector | 100,870 | $42,490 |
| Transportation and Warehousing · Sector | 85,930 | $44,250 |
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 |
|---|---|---|
| Offices of Chiropractors · National industry | 4.63× | 11,000 |
| Exterminating and Pest Control Services · National industry | 4.48× | 10,800 |
| Research and Development in the Social Sciences and Humanities · National industry | 3.39× | 3,360 |
| Roofing Contractors · National industry | 2.66× | 10,750 |
| Real Estate and Rental and Leasing · Sector | 2.62× | 100,870 |
| Plumbing, Heating, and Air-Conditioning Contractors · National industry | 2.6× | 53,720 |
| Labor Unions and Similar Labor Organizations · National industry | 2.22× | 3,830 |
| Painting and Wall Covering Contractors · National industry | 2.04× | 6,860 |
Part of the Management & Entrepreneurship career cluster.
Side-by-side comparisons place two occupations’ pay, preparation, skills, and AI exposure on the same page — same data, same scale, no forecast.
Options the data surfaces for Office Clerks, General — not advice or a forecast. Each is a real cross-link you can follow into the evidence.
Capabilities this work builds that are used across many other occupations.
Occupations O*NET rates as related — the nearby moves on the map.
How people typically prepare for this work.
On the global GenAI exposure gradient this work sits around the 97th percentile of 427 international occupations.
Office Clerks, General show 73rd-percentile AI task overlap — and about 282,400 annual U.S. openings
Office Clerks, General show 73rd-percentile AI task overlap — and about 282,400 annual U.S. openings • Office Clerks, General rank in the 73rd percentile (High 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 282,400 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 (-6.7%) from 2024 to 2034. (BLS Employment Projections 2024–34) • Median annual pay is $43,630, across about 2,510,550 U.S. workers. (BLS OEWS (May 2024)) • Of the AI use actually observed for this work, 37% looks like augmentation (drafting, iterating, checking) rather than hands-off automation — from a Claude.ai usage sample, not a census. (2026-01-15-v4-plus-2025-03-27-v2) Source: Singulariki — "Office Clerks, General". https://singulariki.com/roles/role-43-9061-00 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.
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.
Singulariki. "Office Clerks, General." 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; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); 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-43-9061-00
Singulariki. (2026). Office Clerks, General. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-43-9061-00
@misc{singulariki-role-43-9061-00,
title = {Office Clerks, General},
author = {{Singulariki}},
year = {2026},
note = {O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); 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-43-9061-00}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.