COOKED
The core loop — load fabric, set blade height and marker layout, run the cut, inspect pieces, clear scrap — is exactly what computer-controlled cutting tables and automated spreaders were built to do, and nesting software already optimizes marker layout better than hand placement. What holds the job in place is not AI difficulty but capital cost: handling limp, stretchy, slippery goods and re-threading a misfeed remains awkward for machines, so plants keep humans on the floor. Employment is already small (9,000) and shrinking with domestic apparel volume, so displacement here looks like plants consolidating onto CNC tables rather than a sudden AI event.
Most of this decline happened after 2021 — it is not the pandemic dip.
Median pay $28,730 → $38,760 +7.9% 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
-11.7% 9,300 → 8,200 on the projections basis
Exposed, and shrinking
Both signals point the same way: the tasks are largely automatable and the BLS projects -11.7% 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.
~1,000 openings a year on average, including replacing people who leave.
CutterSilkerClipperCropperTrimmerSpreaderScalloperDie CutterHat CutterRib CutterRug CutterTab CutterBand CutterBolt CutterCuff CutterFelt CutterLace CutterWelt CutterCloth CutterCut OperatorGlove CutterKnife CutterLabel PinkerLaser Cutter
Holding it up: embodiment . Weakest point: liability shield .
Mixed — a routine tier and a judgment tier A 9 reflects the split inside the shift: the cutting itself — marker nesting, blade path, ply depth on a CNC table — is already software's job, but spreading limp knit goods without bowing the grain, unrolling and matching stripes or plaid across plies, and clearing a jam mid-cut still need hands, which is why the score sits above the fully-automatable band rather than at 14.
Some physical or field component You are standing at a 30-foot table lifting bolt rolls, sweeping vacuum-held plies flat, bundling and tying cut parts, and swapping blades or dies — real physical work, but in a lit, climate-stable cutting room with fixed equipment and known material, not a job site or a moving vehicle, which is what keeps it at 12 instead of 17.
No licence, no signature requirement There is no cutting-operator licence anywhere in the US; a plant can put someone on the table the week they are hired, and the OSHA machine-guarding and lockout/tagout duties under 29 CFR 1910.212 and 1910.147 land on the employer, not on you personally — hence a 1.
Executes defined procedures on defined inputs The calls you make — how many plies to stack, when a blade is dull, whether a flaw gets spliced around — are real but bounded by the marker, the spec sheet, and the tolerance the plant already set, and a wrong call costs fabric yardage rather than anyone's safety or a contract, which places this at 4.
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 (9/20 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 (2/20) is whether buyers specifically pay for a person. Judgment and accountability (4/20) 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 7 of this occupation's 28 points (25%).
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.
Furniture Finishers EXPOSED
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 39/100 — EXPOSED.
Task-mix shift: once CNC tables and nesting software own straight-goods production runs, the human tier left is spreading tension calibration on stretch knits, shade/dye-lot matching across rolls, misfeed recovery, and first-article verification against pattern tolerance. This is a genuine two-tier job and the judgment tier is a real residual
If the surviving domestic cut-and-sew niches concentrate further in limp, high-variability materials — leather hides and technical performance knits — where each ply must be judged and hand-placed around defects, the remaining work is fabric handling no gantry table does reliably (Gerber/Lectra leather nesting still requires an operator to mark hide flaws)
If Berry Amendment / DFARS 252.225-7012 defense apparel work (uniforms, body armor shells, parachutes) grows as a share of domestic cutting, operators sign first-article and in-process inspection records under a documented quality system, making the cut-approval call attributable to a named person
The limit. Realistic ceiling is roughly the high 30s. Nothing licenses a cutting-table operator, no buyer specifies a human tender, and the binding constraint is domestic apparel volume, not AI capability — a shrinking denominator caps every lever regardless of how the score moves.
| Dalton, GA | 570 | $37,820 -2% |
| Atlanta-Sandy Springs-Roswell, GA | 560 | $45,220 +17% |
| Los Angeles-Long Beach-Anaheim, CA | 560 | $37,860 -2% |
| Boston-Cambridge-Newton, MA-NH | 270 | $43,680 +13% |
| Hickory-Lenoir-Morganton, NC | 270 | $48,640 +25% |
| Miami-Fort Lauderdale-West Palm Beach, FL | 240 | $35,390 -9% |
| Greenville-Anderson-Greer, SC | 230 | $49,390 +27% |
| Chicago-Naperville-Elgin, IL-IN | 200 | $38,600 +0% |
| Greenville-Anderson-Greer, SC | 230 | $49,390 +27% |
| Hickory-Lenoir-Morganton, NC | 270 | $48,640 +25% |
| Atlanta-Sandy Springs-Roswell, GA | 560 | $45,220 +17% |
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 28. 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.