Computer Numerically Controlled Tool Operators
In short: today's best AI models could do about 24% 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 76% of the time, stays with people.
Operate computer-controlled tools, machines, or robots to machine or process parts, tools, or other work pieces made of metal, plastic, wood, stone, or other materials. May also set up and maintain equipment.
169,450 people do this job in the US. $50,690 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 work9 h
- Desk work AI can't do yet0 h
- Stays with people31 h
Computer Numerically Controlled Tool Operators, now: of a 40-hour week, AI could take on 0 hours, 9 hours become checking its work, 0 hours are desk work it can't do yet, and 31 hours stay with people.
The largest pieces: Write simple machine programs (about 2 h, a person checks); Change machine programs (about 2 h, a person checks); Calculate speeds, feeds and cuts (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.
- 21%
- 3%
- 0%
- 1%
- 75%
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 24% 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, 2%. With Claude Mythos Preview (early), measured in April 2026, 22%. Today's estimate: 24%.
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 27 tasks showed up. Within each of Anthropic's methods, never across a change: 0.093% to 0.023% (released February and March 2025); 0.063% to 0.017% (August 2025 to February 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.093% | 175 of 708 | 5 of 27 |
| Released March 2025 | 0.023% | 397 of 703 | 3 of 27 |
| The week of Aug 4, 2025 (released September 2025) | 0.063% | 206 of 655 | 3 of 27 |
| The week of Nov 13, 2025 (released January 2026) | 0.024% | 363 of 672 | 4 of 27 |
| The week of Feb 5, 2026 (released March 2026) | 0.017% | 419 of 677 | 5 of 27 |
| April 2026 (released June 2026) | none | n/a | 0 of 27 |
| May 2026 (released June 2026) | none | n/a | 0 of 27 |
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 84% of this job's working time as physical work. For 84% of the working time, a robot has been shown doing most of the task somewhere: 68% in a purpose-built cell, 16% in a structured facility. 1.00 of 3, the 116th highest of the 923 jobs.
- Not physical 16%
- In a purpose-built cell 68%
- In a structured facility 16%
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
76% of the working time: the conversation, in-person and hands-on parts of the tasks.
- Set up and operate CNC machines, the hands-on work, 17%
- Mount and align tools and workpieces, the hands-on work, 10%
- Maintain machines and replace tools, the hands-on work, 6%
- Measure finished workpieces, the hands-on work, 5%
- Listen to machines and adjust, the hands-on work, 5%
- Review specifications and set operations, the hands-on work, 4%
What becomes checking the machine
24% 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.
- Write simple machine programs, costly if wrong, 5%
- Change machine programs, costly if wrong, 5%
- Calculate speeds, feeds and cuts, costly if wrong, 4%
- Review specifications and set operations, costly if wrong, 4%
- Modify cutting programs, costly if wrong, 3%
- Transfer programs over the network, costly if wrong, 2%
What to learn
- The hands-on craft. About 75% 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 21% 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 . 27 tasks from .
| Task | ||||
|---|---|---|---|---|
| Set up and operate computer-controlled machines or robots to perform one or more machine functions on metal or plastic workpieces.Setting up and running the machine on the pieces.Done hourly or more by most who do it. Robots: in a purpose-built cell, AWR Flex Series DC-2 machine tending cell (FANUC R-2000 / M-710 robots) (Automation Within Reach / Gosiger / FANUC America) (deployed). Anthropic's rating. | 17% | 50 min25 min to 1.7 h | Hands-on 100% | Stays with people |
| Mount, install, align, and secure tools, attachments, fixtures, and workpieces on machines, using hand tools and precision measuring instruments.Securing tools, fixtures and pieces with hand tools and instruments.Done hourly or more by most who do it. Robots: in a purpose-built cell, HALTER LoadAssistant (Universal/TurnStacker/MillStacker) (sold). Anthropic's rating. | 10% | 33 min13 min to 1.4 h | Hands-on 100% | Stays with people |
| Review program specifications or blueprints to determine and set machine operations and sequencing, finished workpiece dimensions, or numerical control sequences.Reading the program or blueprint and setting the machine to it.Done hourly or more by most who do it. | 7% | 25 min8 min to 50 min | Documents 50%, hands-on 50% | 50%Desk part half by now |
| Maintain machines and remove and replace broken or worn machine tools, using hand tools.Replacing broken or worn tools by hand.Done daily by most who do it. Robots: in a purpose-built cell, Fastems Central Tool Storage (CTS) / Gantry Tool Storage with tool-transport robots and MMS software (deployed). Anthropic's rating. | 6% | 38 min13 min to 1.7 h | Hands-on 100% | Stays with people |
| Measure dimensions of finished workpieces to ensure conformance to specifications, using precision measuring instruments, templates, and fixtures.Checking dimensions with precision instruments.Done hourly or more by most who do it. Robots: in a purpose-built cell, Méca-Précis robotic measurement cell (Mitutoyo MiSTAR CMM + articulated robot, integrated by Engineering Data) (deployed). Anthropic's rating. | 5% | 13 min4 min to 33 min | Hands-on 100% | Stays with people |
| Write simple programs for computer-controlled machine tools.Writing programs for the machine tool.Done several times a day by most who do it. | 5% | 50 min17 min to 2.5 h | Documents 100% | 100%Half by now |
| Listen to machines during operation to detect sounds such as those made by dull cutting tools or excessive vibration, and adjust machines to compensate for problems.Hearing a dull tool or vibration and adjusting the machine.Done hourly or more by most who do it. Robots: in a structured facility, TMAC (Tool Monitoring Adaptive Control) v3 (Caron Engineering) (sold). Anthropic's rating. | 5% | 13 min4 min to 38 min | Hands-on 100% | Stays with people |
| Set up future jobs while machines are operating.Preparing the next job at the machine while it runs, with the plan read.Done daily by most who do it. Robots: in a purpose-built cell, HAIMER Automation Cube One (sold). Anthropic's rating. | 5% | 38 min13 min to 1.7 h | Hands-on 70%, documents 30% | 30%Desk part half by now |
| Implement changes to machine programs, and enter new specifications, using computers.Editing the program and entering the new specifications.Done daily by most who do it. | 5% | 21 min8 min to 50 min | Documents 70%, systems 30% | 100%Half by now |
| Calculate machine speed and feed ratios and the size and position of cuts.Working out the ratios and cut positions.Done several times a day by most who do it. | 4% | 17 min8 min to 33 min | Documents 100% | 100%Half by now |
| Adjust machine feed and speed, change cutting tools, or adjust machine controls when automatic programming is faulty or if machines malfunction.Adjusting the machine by hand when the program is faulty.Done daily by most who do it. Robots: in a purpose-built cell, Okuma Machining Navi (OSP-P control option) (sold). Anthropic's rating. | 3% | 17 min4 min to 50 min | Hands-on 100% | Stays with people |
| Modify cutting programs to account for problems encountered during operation, and save modified programs.Editing the program for problems met in the run and saving it.Done daily by most who do it. | 3% | 25 min8 min to 1.1 h | Documents 100% | 100%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.
- Milling and Planing Machine Setters, Operators, and Tenders, Metal and Plastic18% now, 18% by 2028
- Machinists27% now, 33% by 2028
- Lathe and Turning Machine Tool Setters, Operators, and Tenders, Metal and Plastic38% now, 38% by 2028
- Multiple Machine Tool Setters, Operators, and Tenders, Metal and Plastic10% now, 10% by 2028
- Computer Numerically Controlled Tool Programmers84% now, 84% by 2028
- Grinding, Lapping, Polishing, and Buffing 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 Manufacturing32,130 people
- Fabricated Metal Product Manufacturing (3321, 3322, 3325, 3326, and 3329 only)17,400 people
- Machinery Manufacturing (3331, 3332, 3334, and 3339 only)16,020 people
- Aerospace Product and Parts Manufacturing13,470 people
- Metalworking Machinery Manufacturing10,020 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 Computer Numerically Controlled Tool Operators is within reach of AI now?
- An estimated 24% of the working time is within reach of AI models now and 24% 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 Computer Numerically Controlled Tool 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: Write simple machine programs (100% of the task's time now); Change machine programs (100% of the task's time now); and Calculate speeds, feeds and cuts (100% of the task's time now).
- Which tasks of Computer Numerically Controlled Tool Operators stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Set up and operate CNC machines; Mount and align tools and workpieces; and Maintain machines and replace tools. Together such tasks are about 69% of the working time, and the people and body parts of the other tasks stay with people too.
- What should Computer Numerically Controlled Tool 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 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 76% of the working time stays with people, 24% 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 Computer Numerically Controlled Tool Operators?
- In the Claude.ai conversations Anthropic sampled for May 2026, no reportable share went to this job's tasks. Anthropic's labor market measure puts the share of the job's tasks seen in real Claude use at work at 2%. 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 Computer Numerically Controlled Tool Operators?
- Anthropic's robot exposure rating (September 2026) finds 84% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 84% of the working time, 16% in a structured facility. Its index is 1.00 of 3. One example: TMAC (Tool Monitoring Adaptive Control) v3 for "listen to machines and adjust". 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 27 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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