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Craft and related trades workers · code 7314

Potters and related workers

AI can suggest a glaze. Throwing a pot on the wheel is still your hands.

Reading technical drawings and getting work ready for sale are mostly out of AI's reach. It barely touches nine of the eleven tasks, including making and finishing pottery and porcelain.

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

Potters and related workers prepare pottery, porcelain ware, sanitary ware, bricks, tiles and abrasive wheels by hand or by machine. Tasks include - (a) making articles of pottery and porcelain; (b) making clay or plaster-of-paris moulds; (c) reading technical drawings to know customer’s requirements; (d) forming articles on the potter’s wheel by pressing thumbs into centres of revolving clay to form hollows, and pressing on the inside and outside of emerging clay cylinders with hands and fingers, gradually raising and shaping clay to desired forms and sizes; (e) adjusting wheel speeds according to the feel of the clay as pieces enlarge and walls become thinner; (f) operating jigger machines to form ceramic ware such as bowls, cups, plates and saucers; (g) adjusting and setting controls of pug mills that mix, extrude, cut, and deposit clay charges in or over moulds as specified; (h) smoothening surfaces of finished pieces, using rubber scrapers and wet sponges; (i) forming abrasive wheels by moulding and pressing an abrasive mixture by hand or by machine; (j) examining finished ware for defects and verifying accuracy of shapes and sizes of objects, using callipers and templates; (k) preparing work for sale or exhibition, and maintaining relationships with retail, pottery, art and resource networks that can facilitate sale or exhibition of work. Examples of the occupations classified here: - Abrasive wheel moulder - Brick and tile moulder - Potter - Pottery and porcelain caster - Pottery and porcelain modeller Some related occupations classified elsewhere: - Ceramic artist - 2651 - Kiln operator (brick and tile) - 8181 - Kiln operator (pottery and porcelain) - 8181

  • hand brick moulder
  • production potter

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

113 of 427 for holding up against AI

Why this score?

The ILO rated each of this job's 11 tasks for how much of it AI could do. They average 17.8 out of 100, so it holds up at 100 − 17.8 = 82.2.

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 60 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?

Potters and related workers 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.

  • Selling work and managing listings online.
  • Reading orders and specifications.
  • Kiln scheduling and records.

Man

What people still do better

Judgement, trust and skilled hands. Hard to download.

  • Throwing and shaping clay by feel.
  • Glazing and firing.
  • Making one-off pieces.

Both

What's arriving

New work that only exists because the AI does.

  • Selling directly to buyers worldwide.
  • Pottery classes and workshops.
  • 3D-printed moulds for small production runs.

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

16 could do without you

It could take over very little of the work on its own. It could help with 57 of 100.

The robot

The wildcard. Has hands, still working out stairs.

How much it matters here: Some

60 how hands-on

A fair part of this job is hands-on, so robots would be needed for that part, not just software.

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

60 How
hands-on
39 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 5 US jobs .

finger skill 54.4 · hand skill 50 · cramped spaces 13.7 · 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 34, 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. 34

    Reading technical drawings to know customer’s requirements

    Low
  2. 26

    Preparing work for sale or exhibition, and maintaining relationships with retail, pottery, art and resource networks that can facilitate sale or exhibition of work.

    Low
  3. 24

    Adjusting and setting controls of pug mill that mix, extrudes, cuts, and deposits clay charges in or over moulds as specified

    Very Low
  4. 19

    Examining finished ware for defects verifying accuracy of shapes and sizes of objects, using callipers and templates

    Very Low
  5. 15

    Adjusting wheel speeds according to the feel of the clay as pieces enlarge and walls become thinner

    Very Low
  6. 15

    Forming abrasive wheels by moulding and pressing an abrasive mixture by hand or by machine

    Very Low
  7. 15

    Operating jigger machines to form ceramic ware, such as bowls, cups, plates and saucers

    Very Low
  8. 13

    Making clay or plaster-of-Paris moulds

    Very Low
  9. 13

    Forming articles on potter's wheel by pressing thumbs into centres of revolving clay to form hollows, and press on the inside and outside of emerging clay cylinders with hands and fingers, gradually raising and shaping clay to desired forms and sizes

    Very Low
  10. 12

    Making articles of pottery and porcelain

    Very Low
  11. 10

    Smoothening surfaces of finished pieces, using rubber scrapers and wet sponges

    Very Low

11 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
57
AI does it for you
16

Sidekick wins, by 41 points.

How good a match is this?

One Australian job matches this one closely, so this is about as reliable as it gets here.

estimated Our Gen AI Transition (Gen AI Capacity Study) September 2025 detailed data release data 0.8-observed-use matched to Australian jobs 2114

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?

Out of every 100 conversations

58
42

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. This job makes up 0.14% of the conversations.

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 potters be worried?

Short answer: not really. Put the kettle on.

No. The most exposed tasks are reading technical drawings and preparing work for sale, both Low; throwing, moulding and finishing rate Very Low. AI helps with selling and admin; the clay stays in your hands.

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 →