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Craft and related trades workers · code 7531

Tailors, dressmakers, furriers and hatters

AI can suggest the pattern. Fitting a suit to a real body still takes a tailor's eye.

Adapting shop-bought patterns is mostly out of AI's reach. It barely touches ten of the eleven tasks, including choosing fabrics and fitting and altering garments.

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

Tailors, dressmakers, furriers and hatters fabricate, fit, alter and repair tailored or handmade clothing. They produce made-to-measure clothing such as suits, overcoats and dresses from textile fabrics, light leather, fur and other material, or make hats or wigs according to customers’ and clothing manufacturers’ specifications. Tasks include - (a) making overcoats, suits, skirts, shirts, blouses, lingerie, corsetry, hats, wigs and similar garments, often to clients’ individual requirements; (b) selecting textile fabrics, leather or fur pelts matching the desired size, colour, texture and quality of the garment; cutting to shape them to garment pattern and arranging them on the pattern according to the design of the garment; (c) making garment style changes, such as tapering trouser legs or narrowing lapels, and adding or removing padding; (d) selecting and modifying commercial patterns to customers’ and clothing manufacturers’ specifications and fit; (e) fitting, altering and repairing tailored clothing, dresses, coats and other made-to-measure garments according to customers’ requests; (f) making and caring for costumes used in theatrical, television and motion picture productions; (g) folding, twisting and draping material such as satin or silk, or sewing ribbon or cloth in the form of artificial flowers or bows around crown and brim to shape and decorate hats; (h) sewing and fastening together materials and hair strands to make wigs; (i) blending shades of hair to give a natural appearance to wigs, arranging woven hair in specified positions and sewing hair together to form hairpieces; (j) making, altering, restyling and repairing fur garments and other fur articles; (k) reclaiming furs or skins from old coats, gluing fabric to the interior of fur coats and trimming fur garments. Examples of the occupations classified here: - Dressmaker - Furrier - Fur grader - Hatter - Milliner - Tailor Some related occupations classified elsewhere: - Textiles handicraft worker - 7318 - Sewing machine operator - 8153

  • costume maker
  • milliner
  • tailor
  • hide grader
  • wig and hairpiece maker
  • dressmaker

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

85 / 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

71 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 14.6 out of 100, so it holds up at 100 − 14.6 = 85.4.

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.

This job rates 47.4 out of 100 for how hands-on it is. The score above only looks at AI tools, not robots, but for work this far from the physical that matters less.

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

Man v Bot · compare

Who holds up better?

Tailors, dressmakers, furriers and hatters 85

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.

  • Adapting patterns with software.
  • Measurements from body scans or photos.
  • Orders, fittings and invoices.

Man

What people still do better

Judgement, trust and skilled hands. Hard to download.

  • Fitting garments to real bodies.
  • Cutting and sewing by hand.
  • Theatre costumes, wigs and one-off pieces.

Both

What's arriving

New work that only exists because the AI does.

  • Made-to-measure orders from online measurements.
  • Alterations and repairs as people keep clothes longer.
  • 3D pattern design.

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 60 of 100.

The robot

The wildcard. Has hands, still working out stairs.

How much it matters here: Some

47 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 than half of this job is hands-on. Robots still matter, but for a smaller part of the work, so we don't sort it any further.

Robots hate fiddly work in awkward spaces. On that measure, this job scores 34 out of 100. The higher it is, the longer the robot waits.

47 How
hands-on
34 How fiddly
and cramped

Kind of hands-on work Less than half hands-on

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 55.4 · hand skill 46.4 · cramped spaces 0.8 · averaged · rule: hands-on under 50

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 30, against an average of 15. The bigger the gap, the more lopsided the job: some of it wide open to AI, some of it barely touched.

  1. 30

    Selecting and modifying commercial patterns to customers' and clothing manufacturers' specifications and fit

    Low
  2. 16

    Selecting textile fabrics, leather or fur pelts matching the desired size, colour, texture, and quality of the garment; cutting to shape them to garment pattern and arranging them on pattern according to the design of the garment

    Very Low
  3. 15

    Making garment style changes, such as tapering trouser legs, narrowing lapels, and adding or removing padding

    Very Low
  4. 14

    Reclaiming furs or skins from old coats, gluing fabric to interior of fur coats and trimming fur garments.

    Very Low
  5. 14

    Making and caring for costumes used in theatrical, television and motion picture productions

    Very Low
  6. 14

    Making overcoats, suits, skirts, shirts, blouses, lingerie, corsetry, hats, wigs and similar garments, often to clients' individual requirements

    Very Low
  7. 14

    Folding, twisting and draping material, such as satin or silk, or sewing ribbon or cloth in the form of artificial flowers or bows around crown and brim to shape and decorate hats

    Very Low
  8. 12

    Sewing, and fastening together materials and hair strands to make wigs

    Very Low
  9. 12

    Making, altering, restyling and repairing fur garments and other fur articles

    Very Low
  10. 11

    Fitting, altering and repairing tailored clothing, dresses, coats and other made-to-measure garments according to customers' requests

    Very Low
  11. 10

    Blending shades of hair to give natural appearance to wigs and arranging woven hair in specified position and sewing hair together to form hairpiece

    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
60
AI does it for you
27

Sidekick wins, by 33 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 3932

So, should tailors and dressmakers be worried?

Short answer: not really. Put the kettle on.

No. The most exposed task is adapting commercial patterns, rated Low; cutting, sewing, fitting and alterations all rate Very Low. Pattern software and body scanning help, but made-to-measure work depends on fitting real people.

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 83. This one is above the family average.

Pit this against any other job →