First-Line Supervisors of Office and Administrative Support Workers
In short: today's best AI models could do about 54% of this job's working time (projected from METR's April 2026 measurement and Epoch's November 2026 index) if the work were set up for them, and about 58% by the end of 2028 if progress keeps its long-run pace. The conversations, in-person and hands-on work, about 42% of the time, stays with people.
Directly supervise and coordinate the activities of clerical and administrative support workers.
1,436,680 people do this job in the US. $69,500 a year.
Reviewed on September 30, 2026: what each task is made of, and what handing it over would ask.
A typical 40-hour week
- AI could take on7 h
- A person checks AI's work15 h
- Desk work AI can't do yet1 h
- Stays with people17 h
First-Line Supervisors of Office and Administrative Support Workers, now: of a 40-hour week, AI could take on 7 hours, 15 hours become checking its work, 1 hours are desk work it can't do yet, and 17 hours stay with people.
The largest pieces: Prepare reports, manuals and correspondence (about 3 h, a person checks); Develop or update procedures and standards (about 2 h, a person checks); Design training and service programs (about 2 h, a person checks).
Estimates for a typical week of this job, if progress keeps its long-run pace, counting work the best models finish four times in five. Every task is below.
of the working time. Now is projected from METR's April 2026 measurement and Epoch's November 2026 index.
- 46%
- 12%
- 41%
- 0%
- 1%
of the work: Anthropic's measure of what people already bring to Claude at work (2025). It counts help with part of a task, so it can be higher than the share within reach.
On the chosen pace and reliability. Estimate.
Share of the working time within reach, now to 2030
Change assumptionsHide assumptionsLong-run pace, four in five
What each choice means: , , , , . Every pace starts from .
At this date and pace, models finish tasks up to 2.4 work days long four times in five.
What handing it over would take, now
The 54% within reach splits by what a model would need. The dates, pace and reliability follow the controls above. Estimates.
of the working time. The material can be handed to a model and the result handed back.
of the working time. The model has to be connected to the system the work lives in.
is conversation short enough by length. This site leaves conversation with people, so it is not in the total.
How far this has come
With GPT-4, measured in March 2023, 0% of this job's working time was within reach at . With Claude 3.7 Sonnet, measured in February 2025, 0%. With Claude Mythos Preview (early), measured in April 2026, 28%. Today's estimate: 54%.
A backcast: today's task data with the best model METR had measured by each date. It shows how fast the models have moved, not what anyone forecast at the time.
Measured use over time
Of the Claude.ai conversations Anthropic sampled and tied to a work task, 0.39% went to this job's tasks in May 2026, the 64th largest of the 447 jobs that showed up at all; 5 of its 28 tasks showed up. Within each of Anthropic's methods, never across a change: 0.36% to 0.15% (released February and March 2025); 0.24% to 0.29% (August 2025 to February 2026); 0.38% to 0.39% (April to May 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.36% | 55 of 708 | 13 of 28 |
| Released March 2025 | 0.15% | 119 of 703 | 10 of 28 |
| The week of Aug 4, 2025 (released September 2025) | 0.24% | 75 of 655 | 10 of 28 |
| The week of Nov 13, 2025 (released January 2026) | 0.3% | 56 of 672 | 16 of 28 |
| The week of Feb 5, 2026 (released March 2026) | 0.29% | 69 of 677 | 16 of 28 |
| April 2026 (released June 2026) | 0.38% | 64 of 434 | 5 of 28 |
| May 2026 (released June 2026) | 0.39% | 64 of 447 | 5 of 28 |
Measured, not estimated: Anthropic's samples of Claude.ai conversations, each tied by a model to an O*NET task, from the Anthropic Economic Index. It says where Claude's use goes, not how much of this job's working time it covers, so it is not on the same scale as the reach above. The releases differ in their sample, their classifier and the smallest share they report (the June 2026 file rounds each task to a hundredth of a percent, so a smaller task reads as none), which is why a change of method starts a new line. At least 96% of each older release's task-tied use matched this site's tasks, and all of the newest. Claude.ai only, so use through other tools and other companies' models is not in it. Every job ranked.
Robots and the physical work
Anthropic rates almost none of this job's working time as physical work, so robots do not reach it.
Anthropic's rating, not this site's estimate: Claude Opus 5, searching the web, rated each physical O*NET task by the kind of setting in which a robot it could cite (deployed, sold or demonstrated) does most of the task, weighted by its own estimate of each task's share of the time (What work can robots do?, September 30, 2026, data CC BY 4.0; every job ranked). A robot shown somewhere is not a robot in your building: cost, setup and safety decide that. The share within reach on this page still counts no body work. The robot behind each rated task is under the task below.
What changes for the people in this job
From the task-by-task review, by the end of 2028 on the long-run pace at four in five. It says which parts of the work stay with people and which change, not whether anyone keeps a job: that depends on decisions no data set can see.
What stays with people
41% of the working time: the conversation, in-person and hands-on parts of the tasks.
- Supervise office and service employees, the conversation, 9%
- Implement policies and service standards, the conversation, 7%
- Guide employees through hard problems, the conversation, 4%
- Train employees in duties and policies, the conversation, 4%
- Design training and service programs, the conversation, 3%
- Recruit, interview and select employees, the conversation, 2%
What becomes checking the machine
40% of the working time: desk work a model could do by then, in tasks where a mistake costs something or a licensed person signs. A person checks it. Another 17% is desk work that is small if wrong, which can be handed over with lighter checks.
- Prepare reports, manuals and correspondence, costly if wrong, 8%
- Design training and service programs, costly if wrong, 7%
- Develop or update procedures and standards, costly if wrong, 6%
- Implement policies and service standards, costly if wrong, 5%
- Review production, payroll or shipping records, costly if wrong, 3%
- Supervise office and service employees, costly if wrong, 2%
What to learn
- Briefing a model and checking its drafts. About 46% of the time is documents and data, the part models reach first: writing a clear brief, giving the right material, and checking what comes back.
- Reviewing work you did not do yourself. The tasks under What becomes checking the machine, where a mistake costs something, stay a person's to check: spotting what a draft gets wrong is a skill of its own.
- The conversations. About 41% of the time is conversation and in-person work, which this site leaves with people: listening, explaining, persuading, calming.
- Running AI inside the business systems. About 12% of the time is work inside business systems, which a model can do only once it is connected: knowing the systems well enough to set that up and watch it.
- Handling protected records. Much of the work touches protected personal records: knowing what may be shared with a model, and how, is part of the job.
Your own version of this job: read it against your job description. The headline is free; the full personal report, every task with its timeline and what to learn, is $19 (a sample).
The tasks
Sorted by . 28 tasks from .
| Task | ||||
|---|---|---|---|---|
| Implement corporate or departmental policies, procedures, and service standards in conjunction with management.Mostly conversation with staff and management, plus the written standard.Done daily by most who do it. | 12% | 2.5 h50 min to 1 work day | Conversation 60%, documents 40% | 37%Desk part half by now |
| Supervise the work of office, administrative, or customer service employees to ensure adherence to quality standards, deadlines, and proper procedures, correcting errors or problems.Day to day conversation with a desk team, and checking their work.Done daily by most who do it. | 11% | 1.3 h25 min to 3.3 h | Conversation 80%, documents 20% | 20%Desk part half by now |
| Design, implement, or evaluate staff training and development programs, customer service initiatives, or performance measurement criteria.Program design on paper, with meetings to shape it.Done more than yearly by most who do it. | 10% | 5 h1.7 h to 2.1 work days | Documents 70%, conversation 30% | 51%Desk part half by now |
| Research, compile, and prepare reports, manuals, correspondence, or other information required by management or governmental agencies.Pure document work.Done more than monthly by most who do it. AI observed on this task. | 8% | 2.5 h50 min to 1 work day | Documents 100% | 92%Half by now |
| Develop or update procedures, policies, or standards.Writing procedures.Done more than yearly by most who do it. | 6% | 2.5 h50 min to 6.7 h | Documents 100% | 96%Half by now |
| Prepare and issue work schedules, deadlines, and duty assignments for office or administrative staff.Building the schedule in a system, with some planning and telling people.Done daily by most who do it. | 5% | 50 min25 min to 2.5 h | Systems 50%, documents 30%, conversation 20% | 80%Desk part half by now |
| Train or instruct employees in job duties or company policies or arrange for training to be provided.Showing and telling, with some prepared material.Done daily by most who do it. | 4% | 1.3 h25 min to 4.2 h | Conversation 80%, documents 20% | 20%Desk part half by now |
| Provide employees with guidance in handling difficult or complex problems or in resolving escalated complaints or disputes.Talking a case through with a member of the team.Done daily by most who do it. AI observed on this task. | 4% | 38 min13 min to 1.7 h | Conversation 100% | Stays with people |
| Develop work schedules according to budgets and workloads.Planning the hours, then building the schedule in a system.Done more than monthly by most who do it. | 4% | 1.7 h38 min to 4.2 h | Documents 50%, systems 50% | 100%Half by now |
| Participate in the work of subordinates to facilitate productivity or to overcome difficult aspects of work.Doing the team's own desk work: entry, documents and calls.Done daily by most who do it. | 4% | 1.3 h25 min to 3.3 h | Systems 50%, documents 30%, conversation 20% | 80%Desk part half by now |
| Review records or reports pertaining to activities such as production, payroll, or shipping to verify details, monitor work activities, or evaluate performance.Reading records and reports to check the work.Done more than monthly by most who do it. | 3% | 50 min17 min to 2.5 h | Documents 80%, systems 20% | 100%Half by now |
| Evaluate employees' job performance and conformance to regulations and recommend appropriate personnel action.Writing the review, and the conversation that goes with it.Done more than yearly by most who do it. AI observed on this task. | 3% | 1.3 h38 min to 3.3 h | Documents 60%, conversation 40% | 60%Desk part half by now |
Within reach, per task: the share of the task's time whose instances are short enough for a model to finish at the chosen date, pace and reliability. Half by: the date half of that time comes within reach. Made of: how the task's time splits among five kinds of doing. Only the documents and systems parts can count as within reach, so a task that is 30% documents can be at most 30% within reach.
Jobs that share skills with this one
From O*NET's related occupations. Within reach now and by the end of 2028, long-run pace, four in five.
- First-Line Supervisors of Non-Retail Sales Workers46% now, 49% by 2028
- First-Line Supervisors of Mechanics, Installers, and Repairers47% now, 57% by 2028
- First-Line Supervisors of Passenger Attendants32% now, 33% by 2028
- First-Line Supervisors of Entertainment and Recreation Workers, Except Gambling Services27% now, 28% by 2028
- First-Line Supervisors of Housekeeping and Janitorial Workers43% now, 44% by 2028
- Administrative Services Managers52% now, 70% by 2028
Where this job works
The industry groups that employ the most of it (BLS, May 2025).
Where the most of these jobs are
The metro areas with the most people in it (BLS, May 2025).
Questions about this job
- How much of the work of First-Line Supervisors of Office and Administrative Support Workers is within reach of AI now?
- An estimated 54% of the working time is within reach of AI models now and 58% by the end of 2028, on METR's long-run pace at four in five. Within reach means a model could finish work that long at that reliability. It is not a forecast of jobs lost or of savings.
- Which tasks of First-Line Supervisors of Office and Administrative Support Workers come within reach first?
- Weighted by the time each takes, the tasks with the most within reach now (projected from METR's April 2026 measurement and Epoch's November 2026 index) are: Prepare reports, manuals and correspondence (92% of the task's time now, 100% by the end of 2028); Develop or update procedures and standards (96% of the task's time now); and Design training and service programs (51% of the task's time now, 70% by the end of 2028).
- Which tasks of First-Line Supervisors of Office and Administrative Support Workers stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Guide employees through hard problems; and Discuss performance problems with employees. Together such tasks are about 5% of the working time, and the people and body parts of the other tasks stay with people too.
- What should First-Line Supervisors of Office and Administrative Support Workers learn as AI takes on more of the work?
- By the job's own task-by-task review, the first things to learn are briefing a model and checking its drafts; reviewing work you did not do yourself; and the conversations. By the end of 2028 on the long-run pace at four in five, about 41% of the working time stays with people, 40% becomes checking a model's work and 17% could be handed over with lighter checks. It says which parts of the work change, never whether anyone keeps a job.
- Do people already use AI for the work of First-Line Supervisors of Office and Administrative Support Workers?
- In the Claude.ai conversations Anthropic sampled for May 2026 and tied to a work task, 0.39% went to this job's tasks, the 64th largest share of the 447 jobs that showed up; 5 of its 28 tasks appeared. Anthropic's labor market measure puts the share of the job's tasks seen in real Claude use at work at 19%. These are measures of use, not of how much of the work AI could finish, and they cover Claude only.
- Can robots do the physical work of First-Line Supervisors of Office and Administrative Support Workers?
- Anthropic's robot exposure rating (September 2026) finds almost none of the working time is physical work, so robots do not reach it.
- How is this estimated?
- From the 28 tasks O*NET lists for the occupation, each with an estimated length checked against GDPval and a share of the working time, reviewed one task at a time on September 30, 2026 for what each is made of (documents, business systems, conversation, in person, hands-on), and METR's measurements of how long a task the best AI models can finish, carried forward to the date from the latest, Claude Mythos Preview (early) in April 2026. Data checked November 10, 2026.
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