Craft and related trades workers · code 7536

Shoemakers and related workers

AI can scan your foot. Making a shoe that fits is still handwork.

Reading specifications and checking leather quality are mostly out of AI's reach. It barely touches eleven of the thirteen tasks, including making saddles and bags and mending shoes and belts.

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

Shoemakers and related workers make, modify and repair standard, custom or orthopaedic footwear and natural or synthetic leather articles such as luggage, handbags and belts (except for leather garments, hats and gloves), or participate in the manufacture of shoes and related goods. They decorate, reinforce or finish shoes, luggage, handbags and belts. Tasks include - (a) making, modifying and repairing standard footwear to meet individual requirements; (b) making, modifying and repairing orthopaedic or therapeutic footwear according to doctors’ prescriptions, or modifying existing footwear for people with foot problems and special needs; (c) repairing belts, luggage, purses and similar products; (d) taking plaster casts of deformed legs or feet to prepare drawings; (e) preparing inserts, heel pads and lifts from casts of customers’ feet; (f) studying drawings and other specifications to make footwear according to customers’ needs; (g) studying work orders and/or shoe part tags to obtain information about workloads, specifications and the types of materials to be used; (h) checking the texture, colour and strength of leather to ensure that it is adequate for a particular purpose; (i) cutting out, shaping and padding parts for making leather articles; (j) sewing rips or patching holes to repair articles such as purses, belts, shoes and luggage; (k) removing and examining shoes, shoe parts and designs to verify conformity with specifications, such as proper embedding of stitches in channels; (l) attaching accessories or ornamentation to decorate or protect products; (m) making and repairing articles such as saddles and harnesses for animals, luggage, handbags, briefcases, leather bags, belts and other accessories. Examples of the occupations classified here: - Cobbler - Orthopaedic shoemaker - Saddler - Shoemaker Some related occupations classified elsewhere: - Furrier - 7531 - Hatter - 7531 - Shoe production machine operator - 8156

leather goods manual operator
shoemaker

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

83 / 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

94 of 427 for holding up against AI

Why this score?

The ILO rated each of this job's 13 tasks for how much of it AI could do. They average 16.9 out of 100, so it holds up at 100 − 16.9 = 83.1.

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 59 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?

Shoemakers and related workers 83

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.

Foot scans and digital designs.
Work orders and specifications.
Quotes and bookings.

Man

What people still do better

Judgement, trust and skilled hands. Hard to download.

Making and repairing shoes by hand.
Orthopaedic footwear for individual feet.
Judging leather quality.

Both

What's arriving

New work that only exists because the AI does.

3D-printed insoles and parts.
Repair services as people keep shoes longer.
Custom-fit footwear from scans.

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

23 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: Some

59 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?

Less fine handwork and fewer cramped spaces than a typical hands-on job. That clears one hurdle for machines. It doesn't mean machines are doing this work yet.

Robots hate fiddly work in awkward spaces. On that measure, this job scores 37 out of 100. The higher it is, the longer the robot waits.

59 How
hands-on

37 How fiddly
and cramped

Kind of hands-on work Hands-on, less fiddly work

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 44.6 · hand skill 44.6 · cramped spaces 20.8 · averaged · rule: hands-on 50+ · fiddly under 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 32, against an average of 17. The bigger the gap, the more lopsided the job: some of it wide open to AI, some of it barely touched.

32
Studying drawings and other specifications to make footwear according to customer‚Äôs needs

Low
26
Checking the texture, colour and strength of leather to ensure that it is adequate for a particular purpose

Low
23
Studying work orders and/or shoe part tags to obtain information about workloads, specifications and the types of materials to be used

Very Low
17
Attaching accessories or ornamentation to decorate or protect products

Very Low
17
Removing and examining shoes, shoe parts and designs to verify conformance to specifications such as proper embedding of stitches in channels

Very Low
15
Making, modifying and repairing standard footwear to meet individual requirements

Very Low
15
Making, modifying and repairing orthopaedic or therapeutic footwear according to doctors' prescriptions, or modifying existing footwear for people with foot problems and special needs

Very Low
14
Taking plaster casts of deformed legs or feet to prepare drawings

Very Low
14
Preparing inserts, heel pads and lifts from casts of customers' feet

Very Low
12
Cutting out, shaping and padding parts for making leather articles

Very Low
12
Repairing belts, luggage, purses and similar products

Very Low
12
Making and repairing articles such as saddles and harnesses for animals, luggage, handbags, brief-cases, leather bags, belts and other accessories.

Very Low
11
Sewing rips or patching holes to repair articles, such as purses, belts, shoes and luggage

Very Low

13 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: 23

Sidekick wins, by 40 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 3931

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 under 0.01% 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

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.

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 shoemakers and cobblers be worried?

Short answer: not really. Put the kettle on.

No. The most exposed tasks are studying drawings and checking leather, both Low; making and repairing shoes and orthopaedic footwear rate Very Low. Foot scanning and digital design help, but fitting and repair 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 below the family average.

Pit this against any other job →