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Craft and related trades workers · code 7523

Woodworking-machine tool setters and operators

AI can read the job sheet. Setting the cutter heads is still hands-on.

Reading specifications and following instructions is the one task AI could take a fair chunk of. Setting up machines and fitting blades and bits it barely touches.

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

Woodworking machine tool setters and operators set-up, operate and monitor automatic or semi-automatic woodworking machines such as precision sawing, shaping, planing, boring, turning and woodcarving machines to fabricate or repair wooden parts for furniture, fixtures and other wooden products. Tasks include - (a) setting up, programming, operating and monitoring several types of woodworking machines for sawing, shaping, boring, drilling, planing, pressing, turning, sanding or carving to fabricate or repair wooden parts for furniture, fixtures and other wooden products; (b) operating preset special-purpose woodworking machines to fabricate wooden products such as coat hangers, mop handles, clothespins and other products; (c) selecting knives, saws, blades, cutter heads, cams, bits or belts according to work piece, machine functions and product specifications; (d) installing and adjusting blades, cutter heads, boring-bits and sanding-belts, and using hand tools and rules; (e) setting and adjusting various kinds of woodworking machines for operation by others; (f) reading and interpreting specifications or following verbal instructions. Examples of the occupations classified here: - Carving machine operator (wood) - Furniture production machine operator - Precision woodworking sawyer - Wood products machine operator - Wood turner - Woodworking lathe operator - Woodworking machine setter - Woodworking machine setter-operator - Woodworking machine set-up operator Some related occupations classified elsewhere: - Wood and related products assemblers - 8219

  • nailing machine operator
  • wood pallet maker
  • wood boring machine operator
  • woodturner
  • wooden furniture machine operator
  • wood sander

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

78 / 100

Mostly holds up against AI

AI can take a few chores off your plate, but most of the day is still yours.

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

164 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 21.6 out of 100, so it holds up at 100 − 21.6 = 78.4.

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 61 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?

Woodworking-machine tool setters and operators 78

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.

  • Reading specifications and job sheets.
  • Programming CNC machines.
  • Production records.

Man

What people still do better

Judgement, trust and skilled hands. Hard to download.

  • Setting up and adjusting machines.
  • Selecting and fitting cutters.
  • Checking quality.

Both

What's arriving

New work that only exists because the AI does.

  • CNC and automated woodworking cells.
  • Engineered timber products.
  • Small-batch custom furniture.

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

26 could do without you

It could take over very little of the work on its own. It could help with 58 of 100.

The robot

The wildcard. Has hands, still working out stairs.

How much it matters here: Higher

61 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 48 out of 100. The higher it is, the longer the robot waits.

61 How
hands-on
48 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, matched to one US job .

finger skill 46.4 · hand skill 46.4 · cramped spaces 49.8 · 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 54, against an average of 22. The bigger the gap, the more lopsided the job: some of it wide open to AI, some of it barely touched.

  1. 54

    Reading and interpreting specifications or following verbal instructions.

    Medium
  2. 17

    Setting and adjusting various kinds of woodworking machines for operation by others

    Very Low
  3. 15

    Selecting knives, saws, blades, cutter heads, cams, bits or belts according to work piece, machine functions and product specifications

    Very Low
  4. 15

    Setting-up, programming, operating and monitoring several types of woodworking machines for sawing, shaping, boring, drilling, planing, pressing, turning, sanding or carving to fabricate or repair wooden parts for furniture, fixtures and other wooden products

    Very Low
  5. 15

    Installing and adjusting blades, cutter heads, boring-bits and sanding-belts, and using hand tools and rules

    Very Low
  6. 14

    Operating preset special-purpose woodworking machines to fabricate wooden products such as coat hangers, mop handles, clothes pins and other products

    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
58
AI does it for you
26

Sidekick wins, by 32 points.

How good a match is this?

One Australian job matches, but only partly: not everyone in it does this job. 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 3942

So, should woodworking machinists be worried?

Short answer: not much. Some of the chores will change, and good riddance.

Some of it. Reading specifications is rated Medium; setting up, selecting blades and running machines rate Very Low. CNC machines take more programming and less manual setup, so the job shifts towards programming 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 →