First-Line Supervisors of Material-Moving Machine and Vehicle Operators
In short: today's best AI models could do about 45% 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 the same by the end of 2028 if progress keeps its long-run pace. The conversations, in-person and hands-on work, about 55% of the time, stays with people.
Directly supervise and coordinate activities of material-moving machine and vehicle operators and helpers.
$62,890 a year (for the broader BLS group this job sits in).
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 work18 h
- Desk work AI can't do yet0 h
- Stays with people22 h
First-Line Supervisors of Material-Moving Machine and Vehicle Operators, now: of a 40-hour week, AI could take on 0 hours, 18 hours become checking its work, 0 hours are desk work it can't do yet, and 22 hours stay with people.
The largest pieces: Plan assignments and equipment (about 5 h, a person checks); Set schedules (about 3 h, a person checks); Work out sequences from orders (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.
- 29%
- 15%
- 9%
- 23%
- 24%
Anthropic's data does not cover this job.
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 45% 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, 34%. Today's estimate: 45%.
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, no reportable share went to this job's tasks in May 2026; 0 of its 22 tasks showed up. Within each of Anthropic's methods, never across a change: 0.011% to 0.0097% (released February and March 2025); 0.0069% to 0.0056% (August 2025 to February 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.011% | 520 of 708 | 5 of 22 |
| Released March 2025 | 0.0097% | 512 of 703 | 4 of 22 |
| The week of Aug 4, 2025 (released September 2025) | 0.0069% | 501 of 655 | 3 of 22 |
| The week of Nov 13, 2025 (released January 2026) | 0.0027% | 627 of 672 | 1 of 22 |
| The week of Feb 5, 2026 (released March 2026) | 0.0056% | 562 of 677 | 2 of 22 |
| April 2026 (released June 2026) | none | n/a | 0 of 22 |
| May 2026 (released June 2026) | none | n/a | 0 of 22 |
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 20% of this job's working time as physical work. For 17% of the working time, a robot has been shown doing most of the task somewhere: 7% in a purpose-built cell, 10% in a structured facility. 0.27 of 3, the 398th highest of the 923 jobs.
- Not physical 80%
- No robot shown 3%
- In a purpose-built cell 7%
- In a structured facility 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
55% of the working time: the conversation, in-person and hands-on parts of the tasks.
- Drive and operate equipment, the hands-on work, 10%
- Resolve worker problems, the in-person work, 6%
- Monitor field work, the in-person work, 6%
- Train new workers on the floor, the in-person work, 4%
- Confer to resolve problems, the conversation, 4%
- Help load vehicles, the hands-on work, 3%
What becomes checking the machine
45% 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 assignments and equipment, costly if wrong, 12%
- Set schedules, costly if wrong, 7%
- Work out sequences from orders, costly if wrong, 6%
- Recommend operational improvements, costly if wrong, 5%
- Write activity and accident reports, costly if wrong, 4%
- Keep time and materials records, 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 or sign: spotting what a draft gets wrong is a skill of its own.
- The conversations. About 32% of the time is conversation and in-person work, which this site leaves with people: listening, explaining, persuading, calming.
- Briefing a model and checking its drafts. About 29% 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 hands-on craft. About 24% 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 . 22 tasks from .
| Task | ||||
|---|---|---|---|---|
| Plan work assignments and equipment allocations to meet transportation, operations or production goals.Planning at the desk and entering it.Done daily by most who do it. | 12% | 1.3 h25 min to 2.5 h | Documents 60%, systems 40% | 100%Half by now |
| Drive vehicles or operate machines or equipment to complete work assignments or to assist workers.Driving and running the machines.Done daily by most who do it. Robots: in a structured facility, Fox Robotics FoxBot autonomous forklift (deployed). Anthropic's rating. | 10% | 1.7 h25 min to 3.3 h | Hands-on 100% | Stays with people |
| Recommend and implement measures to improve worker motivation, equipment performance, work methods, or customer services.Written recommendations, worked through.Done more than monthly by most who do it. | 7% | 1.3 h25 min to 3.3 h | Documents 70%, conversation 30% | 70%Desk part half by now |
| Plan and establish schedules.Planning at the desk and entering the schedule. | 7% | 1.7 h25 min to 3.3 h | Documents 60%, systems 40% | 99%Half by now |
| Resolve worker problems or collaborate with employees to assist in problem resolution.Conversations on the floor.Done daily by most who do it. | 6% | 33 min13 min to 1.3 h | In person 100% | Stays with people |
| Monitor field work to ensure proper performance and use of materials.Out with the crews watching the work.Done daily by most who do it. | 6% | 50 min17 min to 1.7 h | In person 60%, hands-on 40% | Stays with people |
| Review orders, production schedules, blueprints, or shipping or receiving notices to determine work sequences and material shipping dates, types, volumes, or destinations.Reading the orders and notices and planning the sequence.Done daily by most who do it. | 6% | 33 min13 min to 1.3 h | Documents 100% | 100%Half by now |
| Perform or schedule repairs or preventive maintenance of vehicles or other equipment.Some fixes by hand, and the maintenance booked.Done daily by most who do it. | 5% | 50 min17 min to 3.3 h | Systems 50%, hands-on 50% | 49%Desk part half by now |
| Prepare, compile, and submit reports on work activities, operations, production, or work-related accidents.Reports written and filed.Done daily by most who do it. | 4% | 50 min17 min to 1.7 h | Documents 70%, systems 30% | 100%Half by now |
| Explain and demonstrate work tasks to new workers or assign training tasks to experienced workers.Showing the work in person.Done daily by most who do it. Robots: no robot shown. Anthropic's rating. | 4% | 50 min17 min to 1.7 h | In person 100% | Stays with people |
| Confer with customers, supervisors, contractors, or other personnel to exchange information or to resolve problems.Calls and conversations on site.Done daily by most who do it. | 4% | 21 min8 min to 50 min | Conversation 70%, in person 30% | Stays with people |
| Assist workers in tasks, such as loading vehicles.Hands-on loading.Robots: in a structured facility, Fox Robotics FoxBot Mk3 autonomous trailer loader/unloader (sold). Anthropic's rating. | 3% | 50 min17 min to 1.7 h | Hands-on 100% | 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 Helpers, Laborers, and Material Movers, Hand33% now, 34% by 2028
- First-Line Supervisors of Mechanics, Installers, and Repairers47% now, 57% by 2028
- First-Line Supervisors of Production and Operating Workers48% now, 54% by 2028
- First-Line Supervisors of Construction Trades and Extraction Workers32% now, 32% by 2028
- First-Line Supervisors of Passenger Attendants32% now, 33% by 2028
- First-Line Supervisors of Farming, Fishing, and Forestry Workers23% now, 24% by 2028
Where this job works
The industry groups that employ the most of it (BLS, May 2025). Counts are for the broader BLS group this job sits in.
Where the most of these jobs are
The metro areas with the most people in it (BLS, May 2025). Counts are for the broader BLS group this job sits in.
Questions about this job
- How much of the work of First-Line Supervisors of Material-Moving Machine and Vehicle Operators is within reach of AI now?
- An estimated 45% of the working time is within reach of AI models now and 45% 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 Material-Moving Machine and Vehicle Operators 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 assignments and equipment (100% of the task's time now); Set schedules (99% of the task's time now); and Work out sequences from orders (100% of the task's time now).
- Which tasks of First-Line Supervisors of Material-Moving Machine and Vehicle Operators stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Drive and operate equipment; Resolve worker problems; and Monitor field work. Together such tasks are about 46% of the working time, and the people and body parts of the other tasks stay with people too.
- What should First-Line Supervisors of Material-Moving Machine and Vehicle Operators 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; the conversations; and briefing a model and checking its drafts. By the end of 2028 on the long-run pace at four in five, about 55% of the working time stays with people, 45% 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 Material-Moving Machine and Vehicle Operators?
- In the Claude.ai conversations Anthropic sampled for May 2026, no reportable share went to this job's tasks. 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 Material-Moving Machine and Vehicle Operators?
- Anthropic's robot exposure rating (September 2026) finds 20% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 17% of the working time, 10% in a structured facility. Its index is 0.27 of 3. One example: Fox Robotics FoxBot autonomous forklift for "drive and operate 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 22 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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