First-Line Supervisors of Production and Operating Workers
In short: today's best AI models could do about 48% 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 54% by the end of 2028 if progress keeps its long-run pace. The conversations, in-person and hands-on work, about 46% of the time, stays with people.
Directly supervise and coordinate the activities of production and operating workers, such as inspectors, precision workers, machine setters and operators, assemblers, fabricators, and plant and system operators. Excludes team or work leaders.
673,430 people do this job in the US. $74,450 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 on0 h
- A person checks AI's work19 h
- Desk work AI can't do yet2 h
- Stays with people19 h
First-Line Supervisors of Production and Operating Workers, now: of a 40-hour week, AI could take on 0 hours, 19 hours become checking its work, 2 hours are desk work it can't do yet, and 19 hours stay with people.
The largest pieces: Plan schedules and production sequences (about 4 h, a person checks); Read schedules and reports to plan production (about 3 h, a person checks); Develop new products and processes (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.
- 44%
- 10%
- 4%
- 24%
- 18%
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 48% 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, 27%. Today's estimate: 48%.
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, 0.011% went to this job's tasks in May 2026, the 374th largest of the 447 jobs that showed up at all; 1 of its 20 tasks showed up. Within each of Anthropic's methods, never across a change: 0.0028% to 0.0034% (released February and March 2025); 0.0024% to 0.0044% (August 2025 to February 2026); 0.011% to 0.011% (April to May 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.0028% | 666 of 708 | 1 of 20 |
| Released March 2025 | 0.0034% | 618 of 703 | 2 of 20 |
| The week of Aug 4, 2025 (released September 2025) | 0.0024% | 613 of 655 | 1 of 20 |
| The week of Nov 13, 2025 (released January 2026) | none | n/a | 0 of 20 |
| The week of Feb 5, 2026 (released March 2026) | 0.0044% | 585 of 677 | 2 of 20 |
| April 2026 (released June 2026) | 0.011% | 358 of 434 | 1 of 20 |
| May 2026 (released June 2026) | 0.011% | 374 of 447 | 1 of 20 |
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 10% of this job's working time as physical work. For 10% of the working time, a robot has been shown doing most of the task somewhere: 10% in a purpose-built cell. 0.10 of 3, the 519th highest of the 923 jobs.
- Not physical 90%
- In a purpose-built cell 10%
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
46% of the working time: the conversation, in-person and hands-on parts of the tasks.
- Observe work and monitor gauges, the hands-on work, 6%
- Enforce safety and sanitation rules, the in-person work, 6%
- Inspect materials, products and equipment, the hands-on work, 5%
- Develop new products and processes, the hands-on work, 4%
- Direct and coordinate production employees, the in-person work, 4%
- Resolve worker problems and grievances, the in-person work, 4%
What becomes checking the machine
54% 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.
- Plan schedules and production sequences, costly if wrong, 11%
- Develop new products and processes, costly if wrong, 10%
- Read schedules and reports to plan production, costly if wrong, 8%
- Set standards, budgets and production goals, costly if wrong, 6%
- Calculate labor and equipment requirements, costly if wrong, 5%
- Keep production data and prepare reports, costly if wrong, 3%
What to learn
- 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.
- Briefing a model and checking its drafts. About 44% 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.
- The conversations. About 28% of the time is conversation and in-person work, which this site leaves with people: listening, explaining, persuading, calming.
- The hands-on craft. About 18% of the time is hands-on work, which no model here does; robots are rated separately on this page.
- Judgment where errors are severe. Some tasks are severe if wrong. Knowing when not to trust an output matters more there than speed.
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 . 20 tasks from .
| Task | ||||
|---|---|---|---|---|
| Plan and develop new products and production processes.Design work, with trials on the floor.Done more than yearly by most who do it. | 15% | 1 work day3.3 h to 4.2 work days | Documents 70%, hands-on 30% | 36%Desk part half by now |
| Plan and establish work schedules, assignments, and production sequences to meet production goals.Planning the run, then the schedule in the system.Done daily by most who do it. | 11% | 1.7 h25 min to 4.2 h | Documents 60%, systems 40% | 97%Half by now |
| Read and analyze charts, work orders, production schedules, and other records and reports to determine production requirements and to evaluate current production estimates and outputs.Reading production records and working out what is needed.Done daily by most who do it. | 8% | 42 min17 min to 1.7 h | Documents 80%, systems 20% | 100%Half by now |
| Direct and coordinate the activities of employees engaged in the production or processing of goods, such as inspectors, machine setters, or fabricators.Mostly conversation with the crew on the floor, plus reading and deciding.Done daily by most who do it. | 7% | 50 min25 min to 3.3 h | In person 60%, documents 40% | 40%Desk part half by now |
| Observe work and monitor gauges, dials, and other indicators to ensure that operators conform to production or processing standards.Walking the line to watch operators and instruments.Done daily by most who do it. | 6% | 50 min13 min to 3.3 h | Hands-on 70%, in person 30% | Stays with people |
| Enforce safety and sanitation regulations.Watching the floor and speaking to workers in person.Done daily by most who do it. | 6% | 38 min13 min to 1.7 h | In person 70%, hands-on 30% | Stays with people |
| Determine standards, budgets, production goals, and rates, based on company policies, equipment and labor availability, and workloads.Analysis on paper.Done daily by most who do it. | 6% | 3.3 h50 min to 6.7 h | Documents 100% | 91%Half by now |
| Inspect materials, products, or equipment to detect defects or malfunctions.Looking things over on the floor.Done daily by most who do it. Robots: in a purpose-built cell, Koh Young Zenith 3D AOI (sold). Anthropic's rating. | 5% | 38 min13 min to 2.5 h | Hands-on 100% | Stays with people |
| Recommend or implement measures to motivate employees and to improve production methods, equipment performance, product quality, or efficiency.Working out the change, and putting it to the crew and management.Done daily by most who do it. | 5% | 1.7 h25 min to 5 h | Documents 50%, in person 50% | 47%Desk part half by now |
| Calculate labor and equipment requirements and production specifications, using standard formulas.Calculation with standard formulas.Done daily by most who do it. | 5% | 1.3 h25 min to 3.3 h | Documents 100% | 99%Half by now |
| Confer with management or subordinates to resolve worker problems, complaints, or grievances.Conversations with workers and management.Done daily by most who do it. | 4% | 50 min17 min to 2.1 h | In person 60%, conversation 40% | Stays with people |
| Confer with other supervisors to coordinate operations and activities within or between departments.Conversations across departments, on the floor and by phone.Done daily by most who do it. | 3% | 38 min13 min to 1.3 h | Conversation 50%, in person 50% | Stays with people |
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 Mechanics, Installers, and Repairers47% now, 57% by 2028
- First-Line Supervisors of Construction Trades and Extraction Workers32% now, 32% by 2028
- First-Line Supervisors of Helpers, Laborers, and Material Movers, Hand33% now, 34% by 2028
- First-Line Supervisors of Material-Moving Machine and Vehicle Operators45% now, 45% by 2028
- First-Line Supervisors of Farming, Fishing, and Forestry Workers23% now, 24% by 2028
- First-Line Supervisors of Office and Administrative Support Workers54% now, 58% 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 Production and Operating Workers is within reach of AI now?
- An estimated 48% of the working time is within reach of AI models now and 54% by the end of 2028, on METR's long-run pace at four in five (53% to 54% across the three paces the site shows). 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 Production and Operating 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: Plan schedules and production sequences (97% of the task's time now); Read schedules and reports to plan production (100% of the task's time now); and Develop new products and processes (36% of the task's time now, 70% by the end of 2028).
- Which tasks of First-Line Supervisors of Production and Operating Workers stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Observe work and monitor gauges; Enforce safety and sanitation rules; and Inspect materials, products and equipment. Together such tasks are about 30% of the working time, and the people and body parts of the other tasks stay with people too.
- What should First-Line Supervisors of Production and Operating 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 reviewing work you did not do yourself; briefing a model and checking its drafts; and the conversations. By the end of 2028 on the long-run pace at four in five, about 46% of the working time stays with people, 54% becomes checking a model's work and 0% 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 Production and Operating Workers?
- In the Claude.ai conversations Anthropic sampled for May 2026 and tied to a work task, 0.011% went to this job's tasks, the 374th largest share of the 447 jobs that showed up; 1 of its 20 tasks appeared. Anthropic's labor market measure puts the share of the job's tasks seen in real Claude use at work at 0%. 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 Production and Operating Workers?
- Anthropic's robot exposure rating (September 2026) finds 10% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 10% of the working time. Its index is 0.10 of 3. One example: Koh Young Zenith 3D AOI for "inspect materials, products and equipment". A robot shown somewhere is not one in every workplace; this site's own estimates still count no physical work as within reach.
- How is this estimated?
- From the 20 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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