EXPOSED
The screen half of this job — drafting blocks in Gerber/Optitex/CLO, grading a base pattern across a size range, nesting markers for cutting efficiency, writing spec sheets — is exactly the parametric, rules-driven work that software already automates well and generative 3D tools are eating faster. What survives is physical: draping muslin on a form, reading how a specific knit or bias-cut fabric actually behaves, and correcting fit on a live model during a fitting session. This occupation sits right on the COOKED/EXPOSED line mainly because it has no licensure, no client accountability shield, and has already been thinned by offshoring, so automation lands on an eroded base.
This fall is concentrated in 2020 and has not recovered since.
Median pay $45,070 → $62,750 +11.4% 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
-10.2% 2,800 → 2,500 on the projections basis
Exposed, and shrinking
Both signals point the same way: the tasks are largely automatable and the BLS projects -10.2% by 2034. This is the case where the score and the forecast agree, and it is the one worth taking seriously.
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.
~300 openings a year on average, including replacing people who leave.
CutterDraperDesignerPatternatorMarker MakerPatternmakerFabric CutterGrader MarkerPattern MakerFabric SourcerPattern GraderPattern DesignerShoe PatternmakerFurniture DesignerPattern TechnicianPleat PatternmakerTechnical DesignerEmbroidery OperatorSail Lay-Out WorkerApparel PatternmakerFashion PatternmakerGarment PatternmakerPattern Chart WriterTextile Patternmaker
Holding it up: embodiment . Weakest point: liability shield .
Mixed — a routine tier and a judgment tier Grading and marker-making are already one-click operations in Gerber/Lectra, and CLO's parametric blocks now generate a first pattern from a sketch — what keeps this at 7 rather than 3 is that muslin draping on a dress form, pinning out a bias-cut swing, and diagnosing why a rib-knit sleeve twists on a fit model still require hands on cloth that no solver reproduces reliably.
Some physical or field component A 12 reflects a job split roughly evenly between a CAD workstation and a cutting table — walking hard-paper or tag-board patterns, notching, pinning muslin on a form, and standing through fittings — all inside a controlled sample room, not on a roof or a job site, which is what keeps it out of the 13+ band.
No licence, no signature requirement There is no state licence, no exam, no registered stamp on a pattern; a graded nest that comes out short-yielding is caught by the cutter or the sample maker and reworked internally, so nothing legally attaches to your name — hence 1, not zero only because an ASTM/ISO spec-sheet signoff occasionally carries your initials.
Meaningful discretion Deciding ease allowances, where to place a dart versus a princess seam, and how much to shrink for a 4% wool relax are real calls made from experience rather than a table, but they are reversible at the next fitting and reviewed by a designer or technical director before production cutting — that review loop is why this is 8 and not 14.
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 (7/20 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 (6/20) is whether buyers specifically pay for a person. Judgment and accountability (8/20) 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 15 of this occupation's 34 points (44%).
Embodiment (12/20) 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 fabric and apparel patternmakers 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 47/100, still EXPOSED.
Task-mix shift: as CAD grading, marker nesting and spec-sheet writing get fully automated, the residual role is fit correction on live bodies and material behavior judgment — draping bias-cut silk, unstable knits, stretch swimwear, and adaptive/plus-size fit where 3D avatar simulation still fails to predict drape. Watch for job postings that drop 'Gerber/Optitex proficiency' as the headline requirement and lead with 'fit technician / draping' instead.
Growth of adaptive apparel and made-to-measure lines (Zappos Adaptive, Tommy Adaptive, Nike FlyEase) where each body is an outlier and pattern correction must be done on a real person or custom form rather than a standard block; also onshore sample rooms rebuilt for speed-to-market, which push more hands-on first-sample work back into US patternmaking.
Continued expansion of bespoke tailoring, bridal, and costume/theatrical work where the buyer is paying explicitly for a named cutter's hand — plus union-shop custom work under IATSE Local 764/Local 705 in film and stage costume, where a credited human patternmaker is contractually part of the deliverable.
If US textile/apparel traceability and content-claim enforcement tightens (FTC Green Guides revision, NY Fashion Act-style bills, EU Digital Product Passport applied to US exporters), someone must own the call that a graded pattern and marker actually match the declared fiber content, yield, and waste claims — making the patternmaker or tech-design lead the signing owner of spec accuracy rather than an anonymous input.
The limit. There is no realistic route to a liability_shield here: no state or federal body licenses patternmakers, and no professional association is pursuing certification with personal legal exposure. Even with every lever above, this stays a small, offshored, non-licensed craft occupation — the levers change what the surviving 2,950 jobs look like, not how many there are.
| Los Angeles-Long Beach-Anaheim, CA | 830 | $89,010 +42% |
| New York-Newark-Jersey City, NY-NJ | 630 | $101,250 +61% |
| Hickory-Lenoir-Morganton, NC | 150 | $48,380 -23% |
| Greensboro-High Point, NC | 70 | $40,090 -36% |
| San Diego-Chula Vista-Carlsbad, CA | 40 | $85,490 +36% |
| Boston-Cambridge-Newton, MA-NH | 30 | $55,540 -11% |
| New York-Newark-Jersey City, NY-NJ | 630 | $101,250 +61% |
| Los Angeles-Long Beach-Anaheim, CA | 830 | $89,010 +42% |
| San Diego-Chula Vista-Carlsbad, CA | 40 | $85,490 +36% |
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 34. 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.