First-Line Supervisors of Construction Trades and Extraction Workers
In short: today's best AI models could do about 32% 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 68% of the time, stays with people.
Directly supervise and coordinate activities of construction or extraction workers.
812,210 people do this job in the US. $79,920 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 on1 h
- A person checks AI's work12 h
- Desk work AI can't do yet0 h
- Stays with people27 h
First-Line Supervisors of Construction Trades and Extraction Workers, now: of a 40-hour week, AI could take on 1 hours, 12 hours become checking its work, 0 hours are desk work it can't do yet, and 27 hours stay with people.
The largest pieces: Estimate materials and labor (about 4 h, a person checks); Read blueprints to plan the work (about 2 h, a person checks); Analyze crew and production problems (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.
- 28%
- 4%
- 6%
- 38%
- 25%
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 32% 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, 23%. Today's estimate: 32%.
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, 0.021% went to this job's tasks in May 2026, the 308th largest of the 447 jobs that showed up at all; 2 of its 15 tasks showed up. Within each of Anthropic's methods, never across a change: 0.028% to 0.017% (released February and March 2025); 0.0098% to 0.014% (August 2025 to February 2026); 0.023% to 0.021% (April to May 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.028% | 385 of 708 | 4 of 15 |
| Released March 2025 | 0.017% | 441 of 703 | 3 of 15 |
| The week of Aug 4, 2025 (released September 2025) | 0.0098% | 455 of 655 | 2 of 15 |
| The week of Nov 13, 2025 (released January 2026) | 0.013% | 445 of 672 | 4 of 15 |
| The week of Feb 5, 2026 (released March 2026) | 0.014% | 438 of 677 | 4 of 15 |
| April 2026 (released June 2026) | 0.023% | 301 of 434 | 2 of 15 |
| May 2026 (released June 2026) | 0.021% | 308 of 447 | 2 of 15 |
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 28% of this job's working time as physical work. For 28% of the working time, a robot has been shown doing most of the task somewhere: 6% in a purpose-built cell, 22% in any setting. 0.73 of 3, the 249th highest of the 923 jobs.
- Not physical 72%
- In a purpose-built cell 6%
- In any setting 22%
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
68% of the working time: the conversation, in-person and hands-on parts of the tasks.
- Supervise and schedule construction workers, the in-person work, 14%
- Inspect work and site safety, the hands-on work, 12%
- Work alongside the crew with tools, the hands-on work, 8%
- Train workers in methods and safety, the in-person work, 7%
- Coordinate with other project activities, the in-person work, 7%
- Measure and mark site locations, the hands-on work, 5%
What becomes checking the machine
29% 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 3% is desk work that is small if wrong, which can be handed over with lighter checks.
- Estimate materials and labor, costly if wrong, 11%
- Read blueprints to plan the work, costly if wrong, 6%
- Analyze crew and production problems, costly if wrong, 5%
- Supervise and schedule construction workers, severe if wrong, 4%
- Order materials and supplies, costly if wrong, 2%
- Suggest promotions, transfers and hires, costly if wrong, 1%
What to learn
- The conversations. About 44% of the time is conversation and in-person work, which this site leaves with people: listening, explaining, persuading, calming.
- 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.
- Judgment where errors are severe. Some tasks are severe if wrong. Knowing when not to trust an output matters more there than speed.
- Briefing a model and checking its drafts. About 28% 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 25% of the time is hands-on work, which no model here does; robots are rated separately on this page.
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 . 15 tasks from .
| Task | ||||
|---|---|---|---|---|
| Supervise, coordinate, or schedule the activities of construction or extractive workers.Leading a crew on site.Done daily by most who do it. | 18% | 1.3 h25 min to 3.3 h | In person 80%, documents 20% | 20%Desk part half by now |
| Inspect work progress, equipment, or construction sites to verify safety or to ensure that specifications are met.Walking the site to look.Done daily by most who do it. Robots: in any setting, Boston Dynamics Spot with FieldAI Field Foundation Models (deployed). Anthropic's rating. | 12% | 50 min25 min to 2.5 h | Hands-on 100% | Stays with people |
| Estimate material or worker requirements to complete jobs.A calculation from the plans.Done daily by most who do it. | 11% | 1.3 h25 min to 3.3 h | Documents 100% | 99%Half by now |
| Analyze worker or production problems and recommend solutions, such as improving production methods or implementing motivational plans.Working out the cause, and talking it through on site.Done daily by most who do it. | 8% | 1.3 h25 min to 3.3 h | Documents 60%, in person 40% | 60%Desk part half by now |
| Read specifications, such as blueprints, to determine construction requirements or to plan procedures.Reading drawings and specifications to plan the job for the crew.Done daily by most who do it. AI observed on this task. | 8% | 38 min17 min to 1.7 h | Documents 70%, in person 30% | 70%Desk part half by now |
| Provide assistance to workers engaged in construction or extraction activities, using hand tools or other equipment.Hands-on construction work.Done daily by most who do it. Robots: in a purpose-built cell, Kawasaki BX250L wall sheathing cell (integrator SCADAware) (deployed). Anthropic's rating. | 8% | 1.3 h25 min to 3.3 h | Hands-on 100% | Stays with people |
| Train workers in construction methods, operation of equipment, safety procedures, or company policies.Showing and teaching the crew on site.Done daily by most who do it. | 7% | 1.7 h25 min to 3.3 h | In person 100% | Stays with people |
| Coordinate work activities with other construction project activities.Conversations with the other trades, mostly on site.Done daily by most who do it. | 7% | 50 min17 min to 1.7 h | In person 60%, conversation 40% | Stays with people |
| Assign work to employees, based on material or worker requirements of specific jobs.Telling the crew on site, from a plan.Done several times a day by most who do it. | 5% | 25 min13 min to 50 min | In person 80%, documents 20% | 20%Desk part half by now |
| Locate, measure, and mark site locations or placement of structures or equipment, using measuring and marking equipment.Layout work on the ground.Done more than weekly by most who do it. Robots: in any setting, Dusty Robotics FieldPrinter (deployed). Anthropic's rating. | 5% | 50 min25 min to 2.5 h | Hands-on 100% | Stays with people |
| Suggest or initiate personnel actions, such as promotions, transfers, or hires.A recommendation written up, and talked over in person.Done more than yearly by most who do it. | 3% | 1.7 h25 min to 3.3 h | Documents 50%, in person 50% | 49%Desk part half by now |
| Confer with managerial or technical personnel, other departments, or contractors to resolve problems or to coordinate activities.Conversations on site and by phone.Done daily by most who do it. | 3% | 38 min17 min to 1.7 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 Production and Operating Workers48% now, 54% 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 Landscaping, Lawn Service, and Groundskeeping Workers29% now, 30% by 2028
- Solar Energy Installation Managers54% now, 61% 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 Construction Trades and Extraction Workers is within reach of AI now?
- An estimated 32% of the working time is within reach of AI models now and 32% 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 Construction Trades and Extraction 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: Estimate materials and labor (99% of the task's time now); Read blueprints to plan the work (70% of the task's time now); and Analyze crew and production problems (60% of the task's time now).
- Which tasks of First-Line Supervisors of Construction Trades and Extraction Workers stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Inspect work and site safety; Work alongside the crew with tools; and Train workers in methods and safety. Together such tasks are about 41% of the working time, and the people and body parts of the other tasks stay with people too.
- What should First-Line Supervisors of Construction Trades and Extraction 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 the conversations; reviewing work you did not do yourself; and judgment where errors are severe. By the end of 2028 on the long-run pace at four in five, about 68% of the working time stays with people, 29% becomes checking a model's work and 3% 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 Construction Trades and Extraction Workers?
- In the Claude.ai conversations Anthropic sampled for May 2026 and tied to a work task, 0.021% went to this job's tasks, the 308th largest share of the 447 jobs that showed up; 2 of its 15 tasks appeared. Anthropic's labor market measure puts the share of the job's tasks seen in real Claude use at work at 3%. 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 Construction Trades and Extraction Workers?
- Anthropic's robot exposure rating (September 2026) finds 28% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 28% of the working time, 22% in any setting. Its index is 0.73 of 3. One example: Boston Dynamics Spot with FieldAI Field Foundation Models for "inspect work and site safety". 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 15 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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