EXPOSED
The ideation layer of this job — trend research, mood boards, colorways, flat sketches, print and pattern variations, tech-pack line drawings — is exactly what generative image models now produce in bulk, and CAD/3D tools like CLO already compress sample iterations. What survives is physical: selecting and handling fabric, draping and correcting fit on a live body, judging drape and hand-feel on a sample, and riding factories through production. The modal worker here is a mid-market apparel designer inside a brand or supplier, not a runway name, and their sketch-and-spec hours are the most exposed part of the week.
Roughly flat across the period, with year-to-year wobble.
Median pay $73,790 → $80,960 -12.2% in real terms
This line is counted by the Bureau of Labor Statistics — the one figure on this page that isn't a judgement of ours. Headcount moves on demand, offshoring, demographics and the business cycle, and automation is one term among several, often not the loudest.
So a falling line is not evidence that AI did it, and a rising one is not evidence that it won't. Both happen in this register: some occupations resist automation and shrink anyway, others are highly automatable and keep growing. The marked year is 2020.
BLS projection, 2024–2034
+2%
Percentage only. The projection counts a different population from the 21,450 above — it includes self-employed workers, which for this occupation is most of them, so the two headcounts are not comparable.
Exposed, but growing
AI can already do a lot of these tasks, and the BLS still expects +2% more of these jobs by 2034. Demand for the output is growing faster than the work is being automated away — the mechanism BLS gives for software developers, and the combination people most often misread as an error.
Different clocks. The score is what current AI could do to this work today. The projection is how many of these jobs will exist in 2034. Everything between the two — how fast employers actually adopt, whether demand grows in the meantime — is why they can point opposite ways without either being wrong.
~2,300 openings a year on average, including replacing people who leave.
StylistCostumerDesignerFur StylistFur DesignerHat DesignerFur RemodelerShoe DesignerStyle AdvisorCustom FurrierDenim DesignerDesign ManagerDress DesignerFashion AdvisorFashion StylistJewelry AdvisorApparel DesignerClothes DesignerCostume DesignerFashion DesignerFurrier DesignerHandbag DesignerImage ConsultantJewelry Designer
Holding it up: judgment & accountability . Weakest point: liability shield .
Mixed — a routine tier and a judgment tier At 8 the job splits roughly in half: mood boards, colorways, repeat prints, flat sketches and tech-pack line art are now first-drafted by diffusion models and CLO 3D, while first-fit correction, choosing a 12oz twill over a 10oz by hand, and pushing a factory through pre-production sample rounds still need a person in the room — it sits above 6 because the fit and fabric half genuinely does not digitize, and below 14 because the sketch-and-spec half already has.
Some physical or field component A 10 reflects fittings on a live model, draping muslin on a form, feeling hand and drape on lab dips and strike-offs, and periodic mill or factory visits — real physical work, but in a studio or showroom with the model standing still, not the uncontrolled conditions that push a score past 13, and plenty of weeks are spent entirely in Illustrator and PLM.
No licence, no signature requirement There is no licence, no board, no CE requirement to call yourself a fashion designer; CPSIA flammability and children's-sleepwear compliance and the care-label rules attach to the brand and its testing lab, and design work itself is copyright-thin — hence 1 rather than 0 only because a named designer's reputation is personally on the line when a garment fails.
Meaningful discretion At 11 the calls are real — committing a colorway and fabric to a six-figure production minimum, killing a style at the fit stage, judging whether a trend has another season in it — but they are made inside a merchandising calendar, against a costed line plan, and signed off by a design director or VP, so the ambiguous bet is shared rather than owned.
The verdict above describes this occupation as a whole. Almost nobody does the typical version of a job — tick what's actually in your week and see how your own mix sits.
Your task mix speaks to task resistance (8/20 here) — how much of the day's work current AI already does. That is the dimension the boxes above are about.
It cannot move the other three. Liability shield (1/20) is whether the law requires a licensed human to sign. Trust premium (8/20) is whether buyers specifically pay for a person. Judgment and accountability (11/20) is whether the role exists to own consequential calls. Those are facts about the occupation's standing, not about which tasks are in your week — a paralegal who does only trial exhibits still holds no licence. Together they are 20 of this occupation's 38 points (53%).
Embodiment (10/20) is also a property of the work rather than the worker, but we don't tag individual tasks as physical or not, so the picker can't tell you anything about it. That's a limit of this tool, not a claim.
Did we get the list right? Tell us what's missing — the tasks are written from the outside, and you're reading this from the inside.
No occupation passed every test: close enough to fashion designers on skills and subject matter, at least 10 points more resistant, no big jump in training, no new licence, no pay cut, and not shrinking on its own. That happens for 223 of the 654 occupations here that aren't SAFE, and it is worth stating plainly rather than leaving the section off.
The usual reason is that exposure travels with the skill profile. The jobs most similar to yours tend to be exposed for the same reasons yours is, so the near neighbours don't clear the gap — and the ones that do are a different kind of work, not a transfer of what you already know. Read that as a limit of this method, not a verdict that you're stuck: it only compares whole occupations, and it cannot see specialisation, industry, or anything you'd bring that isn't in a federal skill survey.
Here is that claim on your own job rather than in the abstract. These are the three occupations closest to this one by skill and subject matter — the places the work would most naturally transfer — with what the register scores them:
That is the whole problem in three lines. The nearest work is not meaningfully safer, so there is no move here that trades a similar skill set for a better verdict. This is not us running out of ideas — it is what the neighbourhood looks like.
The moves above are yours to make. This is the other half: what would have to change in the world for the occupation itself to score higher. None of it is in any one person's gift, but it is where the floor actually comes from. Scores here are not a one-way ratchet. Only two of the five dimensions — task resistance and embodiment — track what machines can do. The other three track law, what buyers will pay for, and who is answerable, and those move in both directions, often in response to the same pressure AI creates. If every lever below landed, this occupation would score around 54/100, still EXPOSED.
Task-mix collapse onto the non-generative tier: if flat sketching, colorway and print variation, and tech-pack line art are fully absorbed by generative tools plus CLO/Browzwear, the remaining defined job is fabric sourcing and qualification, fit correction across a size range, grading decisions, and factory correction cycles — work that is judgment and touch, not image output. Watch for job postings that drop 'strong Illustrator/sketching' and lead with 'fit sessions, fabric development, vendor management'.
Human authorship becoming a commercial requirement because of IP: the US Copyright Office's Thaler/Zarya line and its 2025 guidance deny registration to material lacking human authorship, and design patents require a natural-person inventor. If brands' licensing and anti-counterfeit enforcement depends on registrable prints and surface designs, they must document a named human designer's contribution — turning human origination into a contract term rather than a marketing story.
Ownership of margin-consequential calls concentrating in the designer: if the sketch layer is free, the accountable decision becomes which fabric at which price, which fit block, and which of hundreds of AI options actually gets bought and cut — a call with six-figure inventory consequences and no model able to absorb the blame. Watch for design roles retitled to merge with product development or merchandising sign-off.
Product-compliance sign-off attaching to a named product developer: EU ESPR/Digital Product Passport and the CPSC's children's-apparel and flammability regimes already require an identified responsible person for substantiation claims. If durability, fiber-content, and recycled-content claims in the DPP must be attested by a named individual at the brand, the design/development role acquires a personal signature it does not currently have.
Disclosure-driven premium at the label level: if 'AI-generated design' disclosure becomes standard (via EU AI Act transparency norms bleeding into product marketing, or a retailer's supplier code), a visible split emerges between disclosed-AI mass tiers and 'designed by' human tiers, the way 'handmade' operates on Etsy after its 2024 policy fights.
The limit. Even with every lever, this stays a mid-range occupation. There is no license, no board, and no exam anywhere in US apparel design, so liability_shield cannot rise far; the 'human-designed' premium is real only at the top of the market and for IP-registration reasons, not for the mid-market brand designer who is the modal worker here. The realistic ceiling is roughly the low 50s, and it is reached by the job shrinking into its fabric-and-fit core rather than by protection.
| New York-Newark-Jersey City, NY-NJ | 5,540 | $99,560 +23% |
| Los Angeles-Long Beach-Anaheim, CA | 5,050 | — |
| Dallas-Fort Worth-Arlington, TX | 590 | $63,210 -22% |
| Boston-Cambridge-Newton, MA-NH | 480 | $106,630 +32% |
| San Francisco-Oakland-Fremont, CA | 450 | $102,370 +26% |
| San Diego-Chula Vista-Carlsbad, CA | 320 | $82,010 +1% |
| Denver-Aurora-Centennial, CO | 250 | $99,420 +23% |
| Riverside-San Bernardino-Ontario, CA | 180 | $96,760 +20% |
| Santa Maria-Santa Barbara, CA | 70 | $108,220 +34% |
| Boston-Cambridge-Newton, MA-NH | 480 | $106,630 +32% |
| San Francisco-Oakland-Fremont, CA | 450 | $102,370 +26% |
We have no reported case of a named organisation automating this occupation. Not one deployment, not one announcement.
That is worth saying out loud next to a score of 38. The verdict above is about what the work exposes — what current AI could do to these tasks. It is not a claim that anyone has done it. For this occupation those two things have come apart completely: the capability argument is on this page, and the evidence column is empty.
Has AI actually changed your work? One tap, anonymous, and the running tally is public. Nothing else is asked of you.
Rather than check back: get the digest and we'll tell you what changed — or watch a single occupation from its own page.