Machinists
In short: today's best AI models could do about 27% 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 33% by the end of 2028 if progress keeps its long-run pace. The conversations, in-person and hands-on work, about 67% of the time, stays with people.
Set up and operate a variety of machine tools to produce precision parts and instruments out of metal. Includes precision instrument makers who fabricate, modify, or repair mechanical instruments. May also fabricate and modify parts to make or repair machine tools or maintain industrial machines, applying knowledge of mechanics, mathematics, metal properties, layout, and machining procedures.
287,050 people do this job in the US. $58,750 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 work11 h
- Desk work AI can't do yet2 h
- Stays with people27 h
Machinists, now: of a 40-hour week, AI could take on 0 hours, 11 hours become checking its work, 2 hours are desk work it can't do yet, and 27 hours stay with people.
The largest pieces: Design fixtures and tooling (about 4 h, a person checks); Set procedures for new products (about 2 h, a person checks); Recommend machining improvements (about 1 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%
- 5%
- 2%
- 3%
- 63%
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 27% 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, 7%. Today's estimate: 27%.
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, 0.032% went to this job's tasks in May 2026, the 271st largest of the 447 jobs that showed up at all; 1 of its 29 tasks showed up. Within each of Anthropic's methods, never across a change: 0.055% to 0.035% (released February and March 2025); 0.0083% to 0.0047% (August 2025 to February 2026); 0.034% to 0.032% (April to May 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.055% | 259 of 708 | 3 of 29 |
| Released March 2025 | 0.035% | 334 of 703 | 3 of 29 |
| The week of Aug 4, 2025 (released September 2025) | 0.0083% | 474 of 655 | 1 of 29 |
| The week of Nov 13, 2025 (released January 2026) | 0.0067% | 535 of 672 | 1 of 29 |
| The week of Feb 5, 2026 (released March 2026) | 0.0047% | 574 of 677 | 1 of 29 |
| April 2026 (released June 2026) | 0.034% | 266 of 434 | 1 of 29 |
| May 2026 (released June 2026) | 0.032% | 271 of 447 | 1 of 29 |
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 79% of this job's working time as physical work. For 77% of the working time, a robot has been shown doing most of the task somewhere: 71% in a purpose-built cell, 6% in a structured facility. 0.83 of 3, the 213th highest of the 923 jobs.
- Not physical 21%
- No robot shown 2%
- In a purpose-built cell 71%
- In a structured facility 6%
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
67% of the working time: the conversation, in-person and hands-on parts of the tasks.
- Machine parts to specification, the hands-on work, 12%
- Carry projects from plan to test, the hands-on work, 7%
- Fit and assemble machine tools, the hands-on work, 5%
- Diagnose machine tool faults, the hands-on work, 4%
- Set up and run machine tools, the hands-on work, 4%
- Run brazing and welding equipment, the hands-on work, 4%
What becomes checking the machine
32% 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.
- Design fixtures and tooling, costly if wrong, 10%
- Carry projects from plan to test, costly if wrong, 5%
- Program numerically controlled machines, costly if wrong, 5%
- Set procedures for new products, costly if wrong, 4%
- Recommend machining improvements, costly if wrong, 3%
- Plan machining from the drawings, costly if wrong, 2%
What to learn
- The hands-on craft. About 63% of the time is hands-on work, which no model here does; robots are rated separately on this page.
- 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 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.
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 . 29 tasks from .
| Task | ||||
|---|---|---|---|---|
| Machine parts to specifications, using machine tools, such as lathes, milling machines, shapers, or grinders.Cutting the part on the machine.Done hourly or more by most who do it. Robots: in a purpose-built cell, Productive Robotics OB7 cobots tending CNC mills/lathes at ABACORP (deployed). Anthropic's rating. | 12% | 2.5 h25 min to 1 work day | Hands-on 100% | Stays with people |
| Support metalworking projects from planning and fabrication through assembly, inspection, and testing, using knowledge of machine functions, metal properties, and mathematics.Planning on paper and the making by hand.Done daily by most who do it.Robots: in a purpose-built cell, Hadrian factory-as-a-service machining and inspection cell (sold). Anthropic's rating. | 12% | 1.7 work days3.3 h to 4.2 work days | Hands-on 60%, documents 40% | 13%Desk part half by Mar 2027 |
| Design fixtures, tooling, or experimental parts to meet special engineering needs.Design at the desk.Done daily by most who do it. | 10% | 5 h1.7 h to 1.3 work days | Documents 100% | 89%Half by now |
| Program computers or electronic instruments, such as numerically controlled machine tools.Writing and loading the program at the controller.Done daily by most who do it. | 7% | 2.5 h25 min to 1 work day | Systems 70%, hands-on 30% | 50%Desk part half by now |
| Fit and assemble parts to make or repair machine tools.Assembly by hand.Done more than weekly by most who do it. Robots: in a purpose-built cell, RND Automation Modular Assembly Platform with Epson T3/G3/C8 robots, SCHUNK grippers, ATI compliance device (deployed). Anthropic's rating. | 5% | 2.5 h38 min to 6.7 h | Hands-on 100% | Stays with people |
| Test experimental models under simulated operating conditions, for purposes such as development, standardization, or feasibility of design.Running the test and writing up the results.Done more than yearly by most who do it.Robots: no robot shown. Anthropic's rating. | 5% | 4.2 h1.7 h to 1 work day | Hands-on 60%, documents 40% | 39%Desk part half by now |
| Establish work procedures for fabricating new structural products, using a variety of metalworking machines.Working out the procedure on paper.Done daily by most who do it. | 4% | 3.3 h1.7 h to 6.7 h | Documents 100% | 100%Half by now |
| Diagnose machine tool malfunctions to determine need for adjustments or repairs.Finding the fault at the machine.Done daily by most who do it. Robots: no robot shown. Anthropic's rating. | 4% | 1.3 h17 min to 3.3 h | Hands-on 100% | Stays with people |
| Study sample parts, blueprints, drawings, or engineering information to determine methods or sequences of operations needed to fabricate products.Reading the drawings and the sample and working out the sequence.Done daily by most who do it. | 4% | 1.3 h17 min to 2.5 h | Documents 60%, in person 40% | 59%Desk part half by now |
| Set up, adjust, or operate basic or specialized machine tools used to perform precision machining operations.Machining at the machine.Done daily by most who do it. Robots: in a purpose-built cell, Productive Robotics OB7 collaborative robot (machine tending) (deployed). Anthropic's rating. | 4% | 50 min25 min to 2.5 h | Hands-on 100% | Stays with people |
| Set up or operate metalworking, brazing, heat-treating, welding, or cutting equipment.Hot work by hand.Done hourly or more by most who do it.Robots: in a purpose-built cell, Flexxbotics FlexxCORE + FANUC RoboDrill robotic machining workcells (Ruland Manufacturing) (deployed). Anthropic's rating. | 4% | 1.7 h25 min to 3.3 h | Hands-on 100% | Stays with people |
| Maintain machine tools in proper operational condition.Cleaning and upkeep by hand.Done daily by most who do it. Robots: in a purpose-built cell, Okuma ARMROID (ROID series, e.g. MULTUS B250II) (sold). Anthropic's rating. | 4% | 50 min13 min to 3.3 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.
- Computer Numerically Controlled Tool Operators24% now, 24% by 2028
- Milling and Planing Machine Setters, Operators, and Tenders, Metal and Plastic18% now, 18% by 2028
- Tool and Die Makers31% now, 39% by 2028
- Lathe and Turning Machine Tool Setters, Operators, and Tenders, Metal and Plastic38% now, 38% by 2028
- Computer Numerically Controlled Tool Programmers84% now, 84% by 2028
- Multiple Machine Tool Setters, Operators, and Tenders, Metal and Plastic10% now, 10% by 2028
Where this job works
The industry groups that employ the most of it (BLS, May 2025).
- Machine Shops; Turned Product; and Screw, Nut, and Bolt Manufacturing77,100 people
- Machinery Manufacturing (3331, 3332, 3334, and 3339 only)28,550 people
- Metalworking Machinery Manufacturing21,200 people
- Aerospace Product and Parts Manufacturing19,950 people
- Fabricated Metal Product Manufacturing (3321, 3322, 3325, 3326, and 3329 only)16,400 people
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 Machinists is within reach of AI now?
- An estimated 27% of the working time is within reach of AI models now and 33% by the end of 2028, on METR's long-run pace at four in five (32% to 33% 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 Machinists 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: Design fixtures and tooling (89% of the task's time now, 100% by the end of 2028); Set procedures for new products (100% of the task's time now); and Recommend machining improvements (99% of the task's time now).
- Which tasks of Machinists stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Machine parts to specification; Fit and assemble machine tools; and Diagnose machine tool faults. Together such tasks are about 53% of the working time, and the people and body parts of the other tasks stay with people too.
- What should Machinists 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 hands-on craft; reviewing work you did not do yourself; and briefing a model and checking its drafts. By the end of 2028 on the long-run pace at four in five, about 67% of the working time stays with people, 32% becomes checking a model's work and 1% 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 Machinists?
- In the Claude.ai conversations Anthropic sampled for May 2026 and tied to a work task, 0.032% went to this job's tasks, the 271st largest share of the 447 jobs that showed up; 1 of its 29 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 Machinists?
- Anthropic's robot exposure rating (September 2026) finds 79% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 77% of the working time, 6% in a structured facility. Its index is 0.83 of 3. One example: TMAC (Tool Monitoring Adaptive Control), Caron Engineering for "watch feeds and speeds". 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 29 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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