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Craft and related trades workers · code 7522

Cabinet-makers and related workers

AI can draw the cabinet. Cutting a dovetail joint is still a craft.

Studying plans and preparing specifications is mostly out of AI's reach. It barely touches five of the six tasks, including making furniture, running woodworking machines and finishing surfaces.

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

Cabinet-makers and related workers make, decorate and repair wooden furniture, carts and other vehicles, wheels, parts, fittings, patterns, models and other wooden products using woodworking machines, machine tools and specialized hand tools. Tasks include - (a) operating woodworking machines such as power saws, jointers, mortisers and shapers, and using hand tools to cut, shape and form parts and components; (b) studying plans, verifying dimensions of articles to be made, or preparing specifications and checking the quality and fit of pieces in order to ensure adherence to specifications; (c) trimming joints and fitting parts and subassemblies together to form complete units using glue and clamps, and reinforcing joints using nails, screws or other fasteners; (d) making, restyling and repairing various wooden articles such as cabinets, furniture, vehicles, scale models, sports equipment and other parts or products; (e) decorating furniture and fixtures by inlaying wood or applying veneer and carving designs; (f) finishing surfaces of wooden articles or furniture. Examples of the occupations classified here: - Cabinet-maker - Cartwright - Furniture cabinet-maker - Wheelwright - Wood patternmaker Some related occupations classified elsewhere: - Carpenters and joiners - 7115 - Wood and related products assemblers - 8219

  • furniture finisher
  • frame maker
  • cabinet maker
  • furniture restorer
  • antique furniture reproducer
  • cooper
  • recreation model maker

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

84 / 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

84 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 16.2 out of 100, so it holds up at 100 − 16.2 = 83.8.

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?

Cabinet-makers and related workers 84

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.

  • Drawings, cutting lists and quotes.
  • Computer-controlled cutting of parts.
  • Checking dimensions against plans.

Man

What people still do better

Judgement, trust and skilled hands. Hard to download.

  • Fitting joints and assembling by hand.
  • Veneering, inlay and carving.
  • Restoring antique furniture.

Both

What's arriving

New work that only exists because the AI does.

  • Programming CNC routers.
  • Bespoke furniture sold online.
  • Repair and restoration as people keep furniture longer.

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

25 could do without you

It could take over very little of the work on its own. It could help with 61 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 41 out of 100. The higher it is, the longer the robot waits.

67 How
hands-on
41 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 4 US jobs .

finger skill 51.8 · hand skill 53.1 · cramped spaces 19.2 · 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 29, against an average of 16. The bigger the gap, the more lopsided the job: some of it wide open to AI, some of it barely touched.

  1. 29

    Studying plans, verifying dimensions of articles to be made, or preparing specifications and checking the quality and fit of pieces in order to ensure adherence to specifications

    Low
  2. 15

    Making, restyling and repairing various wooden articles, such as cabinets, furniture, vehicles, scale models, sports equipment and other parts or products

    Very Low
  3. 15

    Decorating furniture and fixtures by inlaying wood, applying veneer and carving designs

    Very Low
  4. 14

    Trimming joints and fitting parts and subassemblies together to form complete units using glue and clamps, and reinforcing joints using nails, screws or other fasteners

    Very Low
  5. 14

    Operating woodworking machines, such as power saws, jointers, mortisers and shapers, and using hand tools to cut, shape and form parts and components

    Very Low
  6. 11

    Finishing surfaces of wooden articles or furniture.

    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
61
AI does it for you
25

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 3941, 3942

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 0.02% 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

62
38

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 cabinet makers be worried?

Short answer: not really. Put the kettle on.

No. The most exposed task is studying plans and checking dimensions, rated Low; making, carving and finishing rate Very Low. Design software and computer-controlled cutting speed up the workshop; joinery, restoration and finishing stay skilled work.

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 above the family average.

Pit this against any other job →