Occupation · SOC 43-1011.00
Directly supervise and coordinate the activities of clerical and administrative support workers.
Also called: Accounting Manager · Customer Service Manager · Customer Service Supervisor · Office Manager · Accounts Payable Supervisor · Accounts Receivable Manager · Administrative Supervisor · Office Coordinator · Office Supervisor · Staff Services Manager · Accounting Administrator · Accounting Clerks Supervisor
Job family: Office and Administrative Support Occupations
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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.
80th-percentile task overlap — yet about 144,500 openings a year (-0.3% projected, BLS), and observed AI use leans 6265% 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 | 77th | 1.0 | |
| LLM task exposure, γ (OpenAI / Eloundou) High | 77th | 0.9 | |
| AI assistant applicability (Microsoft) High | 79th | 0.2 |
OpenAI's exposure study scores tasks three ways: with a language model alone (α 0.1), with simple added tooling (β 0.5), and including AI-powered software (γ 0.9). 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 0.0 · 9th percentile among occupations · Low
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.
| Participate in the work of subordinates to facilitate productivity or to overcome difficult aspects of work. | 4.4% | |
| Compute figures such as balances, totals, or commissions. | 2.4% | |
| Resolve customer complaints or answer customers' questions regarding policies and procedures. | 2.3% | |
| Analyze financial activities of establishments or departments and provide input into budget planning and preparation processes. | 2.3% | |
| Research, compile, and prepare reports, manuals, correspondence, or other information required by management or governmental agencies. | 1.7% | |
| Prepare and issue work schedules, deadlines, and duty assignments for office or administrative staff. | 0.4% |
Independent U.S. Bureau of Labor Statistics employment projection for 2024–2034 — a labor-market forecast, not an AI-impact forecast.
| Outlook | Declining · -0.3% by 2034 |
| Projected annual openings | 144,500 |
| Employment 2024 → 2034 | 1,558,400 → 1,554,400 |
“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 |
|---|---|---|
| Office Supervisors · 3341 | 43% | 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.
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 | 62.6% working with AI · 31.1% handed to AI |
| Most common way people use AI here | Iteration · you and AI go back and forth |
| Typical AI autonomy | 3.0 / 5 · higher = AI acts more independently |
| Used for work (vs. personal / coursework) | 75.0% |
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 |
|---|---|---|
| Participate in the work of subordinates to facilitate productivity or to overcome difficult aspects of work. | Iteration | 18.2% |
| Provide employees with guidance in handling difficult or complex problems or in resolving escalated complaints or disputes. | Iteration | 3.7% |
| Resolve customer complaints or answer customers' questions regarding policies and procedures. | Directive | 1.2% |
| Compute figures such as balances, totals, or commissions. | Directive | 0.9% |
| Research, compile, and prepare reports, manuals, correspondence, or other information required by management or governmental agencies. | Directive | 0.8% |
| Evaluate employees' job performance and conformance to regulations and recommend appropriate personnel action. | Iteration | 0.7% |
| Prepare and issue work schedules, deadlines, and duty assignments for office or administrative staff. | Directive | 0.4% |
| Recruit, interview, and select employees. | Iteration | 0.4% |
Tasks where the model most often judged that a person remained necessary — a useful read on the current boundary, not a guarantee.
| Interpret and communicate work procedures and company policies to staff. | 100.0% | |
| Compute figures such as balances, totals, or commissions. | 98.9% | |
| Participate in the work of subordinates to facilitate productivity or to overcome difficult aspects of work. | 98.8% | |
| Research, compile, and prepare reports, manuals, correspondence, or other information required by management or governmental agencies. | 98.8% | |
| Evaluate employees' job performance and conformance to regulations and recommend appropriate personnel action. | 98.6% | |
| Provide employees with guidance in handling difficult or complex problems or in resolving escalated complaints or disputes. | 98.4% |
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 participate in the work of subordinates to facilitate productivity or to overcome difficult aspects of work. From: Participate in the work of subordinates to facilitate productivity or to overcome difficult aspects of work. · 18.2% of measured AI use · task iteration
Help me provide employees with guidance in handling difficult or complex problems or in resolving escalated complaints or disputes. From: Provide employees with guidance in handling difficult or complex problems or in resolving escalated complaints or disputes. · 3.7% of measured AI use · task iteration
Help me resolve customer complaints or answer customers' questions regarding policies and procedures. From: Resolve customer complaints or answer customers' questions regarding policies and procedures. · 1.2% of measured AI use · directive
Help me compute figures such as balances, totals, or commissions. From: Compute figures such as balances, totals, or commissions. · 0.9% of measured AI use · directive
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.
O*NET importance rating, from 1 (not important) to 5 (extremely important).
| Oral Comprehension | 4.1 | |
| Written Comprehension | 4.0 | |
| Oral Expression | 4.0 | |
| Written Expression | 3.9 | |
| Speech Recognition | 3.9 | |
| Speech Clarity | 3.9 | |
| Problem Sensitivity | 3.8 | |
| Deductive Reasoning | 3.6 | |
| Information Ordering | 3.6 | |
| Inductive Reasoning | 3.5 | |
| Near Vision | 3.5 | |
| Fluency of Ideas | 3.4 | |
| Originality | 3.4 | |
| Category Flexibility | 3.3 |
| Reading Comprehension | 4.0 | |
| Active Listening | 4.0 | |
| Speaking | 4.0 | |
| Monitoring | 4.0 | |
| Critical Thinking | 3.9 | |
| Writing | 3.8 | |
| Active Learning | 3.8 | |
| Learning Strategies | 3.6 |
| Social Perceptiveness | 4.0 | |
| Coordination | 4.0 | |
| Instructing | 3.8 | |
| Judgment and Decision Making | 3.8 | |
| Time Management | 3.8 | |
| Management of Personnel Resources | 3.8 | |
| Persuasion | 3.6 | |
| Negotiation | 3.6 | |
| Service Orientation | 3.6 | |
| Complex Problem Solving | 3.4 | |
| Systems Evaluation | 3.1 |
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 63.
Showing the top 40 of 88.
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: Agriculture, Agriculture Operations, and Related Sciences , Business, Management, Marketing, and Related Support Services , Health Professions and Related Programs . Fields of study crosswalked to this occupation (NCES CIP–SOC), not a requirement.
Share of people in this occupation at each level of education.
| Bachelor's Degree | 45.2% | |
| High School Diploma | 23.2% | |
| Some College Courses | 20.0% | |
| Associate's Degree (or other 2-year degree) | 9.6% | |
| Master's Degree | 1.3% | |
| Post-Secondary Certificate | 0.6% |
The interests and personal qualities O*NET associates with people who do this work.
| Enterprising | 6.9 | |
| Conventional | 5.7 | |
| Social | 4.3 |
| Management/Administration | 6.4 | |
| Office Work | 5.6 | |
| Human Resources | 4.5 | |
| Accounting | 3.8 | |
| Personal Service | 2.7 | |
| Public Speaking | 2.6 | |
| Business Initiatives | 2.5 | |
| Professional Advising | 2.5 |
| Dependability | 6.0 | |
| Attention to Detail | 5.0 | |
| Cooperation | 4.0 | |
| Social Orientation | 3.0 | |
| Leadership Orientation | 2.5 |
U.S. · annual wages (BLS OEWS)
| 10th percentile | $43,920 |
| 25th percentile | $53,190 |
| Median (50th) | $66,140 |
| 75th percentile | $82,340 |
| 90th percentile | $102,980 |
| People employed | 1,495,580 |
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 |
|---|---|---|
| Health Care and Social Assistance · Sector | 250,320 | $62,240 |
| Finance and Insurance · Sector | 184,520 | $72,590 |
| Professional, Scientific, and Technical Services · Sector | 122,400 | $72,320 |
| Retail Trade · Sector | 113,620 | $58,560 |
| Administrative and Support and Waste Management and Remediation Services · Sector | 105,510 | $61,730 |
| Transportation and Warehousing · Sector | 95,390 | $77,430 |
| Educational Services · Sector | 73,490 | $65,250 |
| Manufacturing · Sector | 70,470 | $74,730 |
| Wholesale Trade · Sector | 70,310 | $71,590 |
| Management of Companies and Enterprises · Sector | 63,170 | $79,070 |
| Construction · Sector | 56,120 | $67,060 |
| Accommodation and Food Services · Sector | 45,640 | $50,050 |
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 | 4.46× | 6,310 |
| Offices of Optometrists · National industry | 4.01× | 5,930 |
| Finance and Insurance · Sector | 3.06× | 184,520 |
| Direct Health and Medical Insurance Carriers · National industry | 2.99× | 13,020 |
| Veterinary Services · National industry | 2.73× | 12,260 |
| Management of Companies and Enterprises · Sector | 2.32× | 63,170 |
| Insurance Agencies and Brokerages · National industry | 2.23× | 21,440 |
| Labor Unions and Similar Labor Organizations · National industry | 1.87× | 1,920 |
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 First-Line Supervisors of Office and Administrative Support Workers — 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 80th percentile of 427 international occupations.
First-Line Supervisors of Office and Administrative Support Workers show 80th-percentile AI task overlap — and about 144,500 annual U.S. openings
First-Line Supervisors of Office and Administrative Support Workers show 80th-percentile AI task overlap — and about 144,500 annual U.S. openings • First-Line Supervisors of Office and Administrative Support Workers rank in the 80th 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 144,500 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 (-0.3%) from 2024 to 2034. (BLS Employment Projections 2024–34) • Median annual pay is $66,140, across about 1,495,580 U.S. workers. (BLS OEWS (May 2024)) • Of the AI use actually observed for this work, 63% 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 — "First-Line Supervisors of Office and Administrative Support Workers". https://singulariki.com/roles/role-43-1011-00 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. "First-Line Supervisors of Office and Administrative Support Workers." 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-43-1011-00
Singulariki. (2026). First-Line Supervisors of Office and Administrative Support Workers. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-43-1011-00
@misc{singulariki-role-43-1011-00,
title = {First-Line Supervisors of Office and Administrative Support Workers},
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-43-1011-00}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.