EXPOSED
Hand sewing — basting seams, attaching linings and trim, sewing buttons, finishing hems, closing stuffed goods — is almost untouched by language AI, and limp-fabric manipulation remains one of robotics' hardest unsolved problems, so automation pressure per se is low. The real threat to this occupation is not AI but offshoring and the collapse of domestic apparel finishing: employment is already down to about 2,200 nationally. No licensure, little client relationship for the modal factory or sample-room sewer, and the work follows a spec someone else set.
Part 2020 shock, part continued decline in the years since.
Median pay $29,950 → $36,480 -2.6% 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
-7%
Percentage only. The projection counts a different population from the 2,190 above — it includes self-employed workers, which for this occupation is most of them, so the two headcounts are not comparable.
Exposed, and shrinking
Both signals point the same way: the tasks are largely automatable and the BLS projects -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.
~700 openings a year on average, including replacing people who leave.
SewerKnitterClothierStitcherCouturierHat MakerBale SewerBeadworkerHand SewerHat MenderSeamstressHand-WeaverCasing SewerHand KnitterHand QuilterPelota MakerHand FinisherHand StitcherThread MarkerHosiery MenderMattress SewerCustom ClothierCustom DesignerHand Sole Sewer
Holding it up: task resistance . Weakest point: liability shield .
Tasks largely resist digitisation Blind-stitching a hem so no thread shows on the face, basting a canvas front to a jacket shell, or hand-tacking a lining pleat all require reading how a specific piece of cloth is behaving under tension at that moment — no sewing automat has replicated the felt feedback of a needle passing through interlining, which is why 16 rather than a mid-band score.
Hands-on in uncontrolled environments The work is entirely in the hands: pinching seam allowance, easing fullness into a sleevehead, closing a stuffed toy from the outside with a ladder stitch — but it happens seated at a bench or table in a controlled shop, not on a roof or in a trench, which keeps it at 16 rather than the high teens.
No licence, no signature requirement There is no state licence, no certification board, and no exam standing between anyone and a hand-sewing job; a mis-set button is a reject ticket at QC, not a claim against you personally, so the shield is genuinely zero rather than merely thin.
Executes defined procedures on defined inputs You are executing a spec sheet or a designer's mock-up: stitch type, spacing, and placement are set upstream, and your discretion is confined to how much ease to work into a curve or whether a piece needs re-pressing before it goes on — real skill, but not a call with consequences beyond that one unit, hence 5.
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 (16/20 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 (0/20) 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 (5/20) 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 11 of this occupation's 43 points (26%).
Embodiment (16/20) 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.
Cooks, Restaurant EXPOSED
Maids and Housekeeping Cleaners 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 55/100, still EXPOSED.
Task-mix shift within the trade: if remaining domestic work concentrates in sample rooms, alterations, theatrical/costume, museum textile conservation and upholstery repair — one-off garments with no repeatable spec — the residual job is diagnosis-and-repair on unique objects rather than repetitive piecework. This is already the direction of the surviving 2,200 jobs.
Enforced country-of-origin and 'hand-finished' labeling claims, plus growth of couture/bridal/heritage-brand marketing where the buyer is explicitly paying for hand pad-stitching and hand-set linings (Savile Row, Brooks Brothers-style 'hand-finished' claims; FTC Made in USA rule enforcement). If a certification scheme audits actual hand labor — analogous to Woolmark or the Handloom Mark in India — the premium becomes checkable rather than rhetorical.
If conservation-grade work grows, sewers in museum/archival textile roles own irreversible calls on stitch choice and material compatibility under AIC (American Institute for Conservation) treatment-documentation standards — a documented, attributable decision rather than following a spec.
The limit. liability_shield has no realistic route: there is no licensing body for hand sewing anywhere and no plausible bill creating one. Also note the score is misleading as a safety signal — this occupation's decline driver is offshoring and the collapse of domestic finishing capacity, not AI, so a high AI-resistance score does not imply job security.
| New York-Newark-Jersey City, NY-NJ | 140 | $37,380 +2% |
| New York-Newark-Jersey City, NY-NJ | 140 | $37,380 +2% |
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 43. 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.