Professionals · code 2163
Product and garment designers
AI can generate a hundred concepts. Deciding which one works is still design.
The ILO files this under product and garment designers. Writing up a design for production is the one task AI could take a fair chunk of; sketching, briefing clients and making prototypes are mostly or entirely out of its reach.
What they actually do (and what else they get called)
Product and garment designers design and develop products for manufacture and prepare designs and specifications of products for mass, batch and one-off production. Tasks include - (a) determining the objectives and constraints of the design brief by consulting with clients and stakeholders; (b) formulating design concepts for clothing, textiles, industrial, commercial and consumer products, and jewellery; (c) harmonizing aesthetic considerations with technical, functional, ecological and production requirements; (d) preparing sketches, diagrams, illustrations, plans, samples and models to communicate design concepts; (e) negotiating design solutions with clients, management, and sales and manufacturing staff; (f) selecting, specifying and recommending functional and aesthetic materials, production methods and finishes for manufacture; (g) detailing and documenting the selected design for production; (h) preparing and commissioning prototypes and samples; (i) supervising the preparation of patterns, programmes and tooling, and of the manufacturing process. Examples of the occupations classified here: - Costume designer - Fashion designer - Industrial designer - Jewellery designer Some related occupations classified elsewhere: - Engine designer - 2144 - Building architect - 2161 - Landscape architect - 2162 - Interior designers - 3432
- industrial designer
- textile product developer
- textile colourist
Job titles from the EU's ESCO list. Search for any of them on the jobs page and you'll end up here.
65 / 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.
The ILO's official verdict: Minimal Exposure
275 of 427 for holding up against AI
Not quite your week? Make it yours ↓
Why this score?
The ILO rated each of this job's 9 tasks for how much of it AI could do. They average 35 out of 100, so it holds up at 100 − 35 = 65.
That's the whole sum. No black box, no secret sauce: you can check it against the ILO's study. ILO group “Minimal Exposure”: A few tasks are affected, but the heart of the job isn't.
This job rates 31.8 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?
Product and garment designers 65
vGo 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.
- Concept sketches and variations.
- Documenting designs for production.
- Material research.
Man
What people still do better
Judgement, trust and skilled hands. Hard to download.
- Understanding clients and users.
- Balancing aesthetics, cost and manufacturing.
- Prototyping and testing.
Both
What's arriving
New work that only exists because the AI does.
- Designing with AI tools.
- Sustainable materials.
- Made-to-order and personalised products.
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: Medium
39 could do without you
It could take over some of the work, and help with more. It could help with 71 of 100.
The robot
The wildcard. Has hands, still working out stairs.
How much it matters here: Lower
32 how hands-on
Not much of this job needs hands, so the robot can sit this one out.
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 27 out of 100. The higher it is, the longer the robot waits.
hands-on
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, averaged across 2 US jobs .
finger skill 40.2 · hand skill 27.7 · cramped spaces 13.6 · 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 51, against an average of 35. The bigger the gap, the more lopsided the job: some of it wide open to AI, some of it barely touched.
- 51
Detailing and documenting the selected design for production
Medium - 44
Preparing sketches, diagrams, illustrations, plans, samples and models to communicate design concepts
Low - 35
Determining the objectives and constraints of the design brief by consulting with clients and stakeholders
Low - 35
Harmonizing aesthetic considerations with technical, functional, ecological and production requirements
Low - 35
Negotiating design solutions with clients, management, and sales and manufacturing staff
Low - 34
Selecting, specifying and recommending functional and aesthetic materials, production methods and finishes for manufacture
Low - 32
Formulating design concepts for clothing, textiles, industrial, commercial and consumer products, and jewellery
Low - 30
Supervising the preparation of patterns, programmes and tooling, and of the manufacturing process.
Low - 20
Preparing and commissioning prototypes and samples
Very Low
9 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
New · the weekly task audit
Your week, your score
The score above assumes product and garment designers spend the same time on every task. You don't. Slide each task to how much of your week it takes, and we'll re-weight the same ILO ratings to fit your job.
- Some
- Some
- Some
- Some
- Some
- Some
- Some
- Some
- Some
Your score
65 / 100
Same as the job as a whole, so far.
Move the sliders to make it yours.
The job as a whole: 65 / 100
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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
- 71
- AI does it for you
- 39
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 2323
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
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 0.17% of the conversations.
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 product and garment designers be worried?
Short answer: not much. Some of the chores will change, and good riddance.
Parts of the work are changing. Documenting designs for production is rated Medium, and sketches, briefs, balancing requirements, negotiating, specifying materials, concepts and supervising production are Low; prototypes rate Very Low. AI speeds up concepts and documentation; judgement stays human.
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 92 jobs in the “Professionals” family, averaging 61. This one is above the family average.
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A closer look
There is a written profile for a job in this group.