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Craft and related trades workers · code 7223

Metal working machine tool setters and operators

The CNC machine cuts the part. Setting it up and spotting a bad cut is still skilled work.

Inspecting and measuring finished pieces is mostly out of AI's reach. It barely touches five of the six tasks, including watching machines for faults and changing worn tools.

What they actually do (and what else they get called)

Metal working machine tool setters and operators set and/or operate various machine tools, working to fine tolerances. Tasks include - (a) setting one or more types of machine tool for production of metal articles in standardized series; (b) operating and monitoring metal working machines such as lathes, milling, planing, boring, drilling, grinding or honing machines, including multipurpose numerically controlled metal working machines; (c) performing similar tasks when machining plastics and other metal substitutes; (d) observing machine operations to detect work piece defects or machine malfunctions, and adjusting machines as necessary; (e) inspecting work pieces for defects, and measuring work pieces to determine accuracy of machine operation, using rules, templates or other measuring instruments; (f) changing worn machine accessories such as cutting tools and brushes, using hand tools. Examples of the occupations classified here: - Boring machine operator - Casting machine operator - Machine tool operator - Machine tool setter - Machine tool setter-operator - Metal turner - Rivet production machine operator - Tool production machine operator

  • swaging machine operator
  • upsetting machine operator
  • chain making machine operator
  • stamping press operator
  • ornamental metal worker
  • fitter and turner
  • scrap metal operative
  • metal planer operator
  • drilling machine operator
  • oxy fuel burning machine operator
  • gear machinist
  • moulding machine operator
  • computer numerical control machine operator
  • heat treatment furnace operator
  • plasma cutting machine operator
  • spark erosion machine operator
  • metal nibbling operator
  • briquetting machine operator
  • drill press operator
  • screw machine operator
  • straightening machine operator
  • thread rolling machine operator
  • router operator
  • laser marking machine operator
  • boring machine operator

Job titles from the EU's ESCO list. Search for any of them on the jobs page and you'll end up here.

82 / 100

Strongly holds up against AI

Most of this job still needs an actual human. AI would mostly be making the tea.

Not the odds you keep your job. It's how much of the everyday work still needs a person, out of 100.

← Robot's turf Human's turf →

The ILO's official verdict: Not Exposed

119 of 427 for holding up against AI

Why this score?

The ILO rated each of this job's 6 tasks for how much of it AI could do. They average 18.2 out of 100, so it holds up at 100 − 18.2 = 81.8.

That's the whole sum. No black box, no secret sauce: you can check it against the ILO's study. ILO group “Not Exposed”: None of this job's tasks scored high enough to count.

from the source Working Paper 140, Generative AI and Jobs 2025 index data 0.8-observed-use

Pinch of salt: this number is probably too rosy

It only asks what AI software could do, and this job is 67 out of 100 hands-on. A chatbot can't do that part. A robot might, one day, and nobody measures how close that is.

Man v Bot · compare

Who holds up better?

Metal working machine tool setters and operators 82

v

Go on, try your partner's job. Or your sibling's. We won't tell.

Man v Bot

Where the bot helps, and where the human wins

Bot

What AI takes

The routine stuff. You may not miss it.

  • CNC programming from digital models.
  • Automated measurement and inspection.
  • Production records.

Man

What people still do better

Judgement, trust and skilled hands. Hard to download.

  • Setting up machines and tooling.
  • Spotting problems by sound and feel.
  • Changing tools and making adjustments.

Both

What's arriving

New work that only exists because the AI does.

  • Running multi-axis and automated machining cells.
  • Additive manufacturing alongside machining.
  • Precision parts for energy and medical industries.

Written by a human, from the ILO's task ratings below. Yes, we see the irony. Read it as one person's take.

Meet your two rivals

They're not the same machine. AI software can only reach the parts of a job done on a screen or in words. A chatbot can't climb a ladder. A robot might, one day, if it doesn't fall off.

The AI

Lives in a screen. Never had to fix a boiler.

Threat level: Low

27 could do without you

It could take over very little of the work on its own. It could help with 63 of 100.

The robot

The wildcard. Has hands, still working out stairs.

How much it matters here: Higher

67 how hands-on

Most of this job needs hands, a body or turning up. That's robot territory, and nobody measures how far robots have got well enough to give you a number. We won't make one up.

So could a robot do the physical part?

More fine handwork, and more time in cramped or awkward spots, than a typical hands-on job. That is exactly what machines find hardest: they do best in tidy, predictable places.

Robots hate fiddly work in awkward spaces. On that measure, this job scores 40 out of 100. The higher it is, the longer the robot waits.

67 How
hands-on
40 How fiddly
and cramped

Kind of hands-on work Hands-on, fiddly work in tight spaces

The small print

They aren't a robot score, and nothing on this page is. Nobody measures how far robots have got well enough to put a number on it. These are the closest thing we have: how hands-on the job is, and how much fiddly, cramped work it takes, which is what Frey and Osborne found hardest for machines.

From O*NET, averaged across 11 US jobs , so treat it as rough.

finger skill 45.8 · hand skill 44.8 · cramped spaces 28.3 · averaged · rule: hands-on 50+ · fiddly 39.4+

estimated O*NET 31.0 BLS occupational crosswalk chain ISCO-08 to 2010 SOC (Aug 2012, rev. Jun 2015); 2010 to 2018 SOC (Nov 2017); O*NET-SOC 2019 taxonomy data 0.8-observed-use measures chosen by Frey & Osborne (2017) · the grouping is a sorting, not a measurement

The job, task by task

Every job is really a bundle of tasks. Here's this one unpacked, with how much of each AI could do, out of 100. The score is the average, and averages can hide a lot.

AI's favourite task here scores 25, against an average of 18. The bigger the gap, the more lopsided the job: some of it wide open to AI, some of it barely touched.

  1. 25

    Inspecting work pieces for defects, and measuring work pieces to determine accuracy of machine operation, using rules, templates or other measuring instruments

    Low
  2. 24

    Observing machine operations to detect work piece defects or machine malfunctions, and adjusting machines as necessary

    Very Low
  3. 16

    Setting one or more types of machine tool for production of metal articles in standardized series

    Very Low
  4. 16

    Operating and monitoring metal working machines, such as lathes, milling, planing, boring, drilling, grinding or honing machines, including multipurpose numerically controlled metal working machines

    Very Low
  5. 15

    Performing similar tasks when machining plastics and other metal substitutes

    Very Low
  6. 13

    Changing worn machine accessories, such as cutting tools and brushes, using hand tools.

    Very Low

6 tasks · the High to Very Low labels are the ILO's

from the source Working Paper 140, Generative AI and Jobs 2025 index data 0.8-observed-use

Sidekick or replacement?

A tool that makes you faster is a very different thing from one that does the task while you watch. Jobs and Skills Australia measured the two separately, which is handy.

AI helps you
63
AI does it for you
27

Sidekick wins, by 36 points.

How good a match is this?

2 Australian jobs match this one, and we've simply averaged them. Treat the numbers as a rough guide.

estimated Our Gen AI Transition (Gen AI Capacity Study) September 2025 detailed data release data 0.8-observed-use matched to Australian jobs 3232, 7123

Meanwhile, in real life…

Everything else here is about what AI could do. This is what people actually did. When they asked Claude for help with this kind of work, did they hand the whole task over, or roll their sleeves up and work through it together?

Tiny sample alert This job makes up 0.03% of all the conversations: a tiny slice, mostly the paperwork rather than the work. People using AI for a job isn't the same as AI being able to do it.

Out of every 100 conversations

72
28

worked through it together handed it over

The small print

Anthropic publishes this about its own product, and it doesn't feed into any score here. These are people who use Claude, not workers in general, so little use here doesn't mean AI can't reach the job.

The data is sorted by US job, and this one matches 2 of them. We've combined them, counting each by how often it comes up in the conversations, so the busiest one counts most.

These two add up to 100. The bars elsewhere on the page don't, because each is scored on its own, so we don't put them side by side.

observed use Anthropic Economic Index release 2026-06-26, period beginning 2026-05-01 data 0.8-observed-use 2026-05-01 · Anthropic, about its own product

So, should machinists and tool setters be worried?

Short answer: not really. Put the kettle on.

No, but the machines keep getting smarter. The most exposed task is inspecting and measuring parts, rated Low; setting, running and adjusting machines rate Very Low. Automated inspection and CNC programming tools are changing the job towards setting up and supervising.

Worth remembering: we score tasks, not jobs. When AI takes on a task, the job usually reshuffles around it rather than vanishing.

Where this job could lead

None of the new jobs we've written up start from here yet. Could be you're the first. See the jobs AI is creating →

How are the neighbours doing?

There are 65 jobs in the “Craft and related trades workers” family, averaging 84. This one is below the family average.

Pit this against any other job →