← Risk register SOC 51-4199 · reviewed 2026-08-11

Metal Workers and Plastic Workers, All Other

15,900 US workers · median $45,950/yr · Production

EXPOSED

This is a catch-all bucket for shop-floor metal and plastic workers who don't fit the named machine-operator titles — hand-forming, trimming, fixture loading, deburring, heat-treat tending, inspecting and reworking parts. Language AI barely touches this work, but purpose-built industrial automation does: CNC cells, robotic tending, and vision inspection have been eating exactly these tasks for two decades and continue to. The moat is physical, not legal or relational — no license, no client relationship, and little decision authority beyond scrap/rework calls, so the job is protected by capital cost and part variety rather than by anything AI can't learn.

10-year outlook: Headcount in this residual category keeps shrinking as high-volume tasks migrate to automated cells, while workers who can set up, troubleshoot, and salvage low-volume custom work stay in demand and out-earn the loaders.

US employment, 2019–2025-34.7%
24,34015,900 workers

Part 2020 shock, part continued decline in the years since.

Median pay $34,830 → $45,950 +5.5% in real terms (nominal +31.9%, less ~25% US inflation over the period)

The job count is not the verdict

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

-9.5%

Percentage only. The projection counts a different population from the 15,900 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 -9.5% 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.

~1,700 openings a year on average, including replacing people who leave.

One email if this score changes. Watch as many occupations as you like from the same address — no account, and nothing is sent on a schedule, only when a verdict actually moves.

Also known as — 24 job titles this covers

Titles reported by people doing this work, from the US Department of Labor's O*NET survey. If your job title is here, this page is about your work even though the name doesn't match.

TruerCoilerPasserPusherRipperTapperBradderDrifterPipemanPoke-InRiveterStaplerTrimmerBalancerChainmanBand MakerBit ShaverBit TapperBlacksmithJob SetterKey CutterNail MakerTack MakerBolt Header

This is a catch-all code, not a single job

The BLS uses Metal Workers and Plastic Workers, All Other for work that doesn't fit any named occupation, so it covers roles that have little in common with each other. Two consequences worth knowing before you read anything below:

If a more specific occupation on the register describes what you actually do, that page is the one to trust.

Score — 43/100 resistance

Holding it up: embodiment (16/20). Weakest point: liability shield (2/20).

Five dimensions, 0–20 each, summed. Higher means more protected. The arithmetic is shown so you can check it: 14 + 16 + 2 + 4 + 7 = 43. · Scored 2026-08-11, and re-examined when evidence accumulates rather than on a schedule.

Task resistance 14/20

Tasks largely resist digitisation At 14 the work sits just above the automation line because the tasks that land in this catch-all bucket — hand-deburring odd castings, shimming a fixture that won't seat, straightening warped plastic trim, feeding short-run parts nobody wrote a program for — are the leftovers precisely because they resisted the cells that already took the high-volume work, but they are physical routines a robot arm with decent vision will eventually reach, which is why this isn't 18.

Embodiment 16/20

Hands-on in uncontrolled environments 16 reflects standing at a press, oven, or bench for a full shift handling hot stock, sharp flash and slippery coolant, where grip force, part orientation by feel, and reacting to a jam are the job — not 19 or 20 only because the shop floor is an indoor, fixtured environment with known machines rather than a field site or crawlspace.

Liability shield 2/20

No licence, no signature requirement A 2 is honest: there is no state license to trim plastic or tend a heat-treat furnace, and while a shop may carry AWS or ISO/AS9100 requirements, those certify the employer's process and the QC signoff, not you personally — the 2 rather than 0 acknowledges forklift or crane certs and some welding-ticket holders in the bucket.

Trust premium 4/20

Anonymous artifact production 4 is where an anonymous part number puts you — the customer receives a bracket, not you, and the only relationship that shields the job is the shift lead who knows you can eyeball a bad shot; that internal familiarity is worth 4, not 0, but it doesn't survive a plant relocation.

Judgment & accountability 7/20

Meaningful discretion 7 puts you at the bottom edge of real discretion: scrap-versus-rework calls, deciding when a die needs pulling, and catching drift before the inspection sample does are judgment with money attached, but the print, the spec, and the router define the acceptable answer, and a supervisor or QC signs off on anything expensive.

Confidence: medium · reviewed 2026-08-11 · how scoring works

What this job involves — and which parts are yours

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.

AI already does these at usable quality

These still need a person

Active moats on the surviving side: embodiment, physical-presence

How to future-proof this job

All 35 skills ranked by how many jobs they open →

What would move this back up — beyond any one person

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.

4 specific changes that would raise this score
  • already happening task resistance +3

    Task-mix shift within the bucket: as robotic tending and vision inspection absorb the high-volume repeat work, what remains is low-volume/one-off fixturing, hand-forming of non-repeating geometries, and rework of parts that failed automated inspection — work where each piece is dimensionally unique. Watch for shops reclassifying these workers as 'rework/first-article technicians' tied to prototype and MRO lines rather than production runs.

  • plausible liability shield +4

    Named-operator traceability requirements in safety-critical part chains: AS9100/NADCAP heat-treat and special-process rules already require certified operator sign-off on process runs, and FAA Part 21 production approval requires identified personnel for inspection buy-off. If primes push per-part named-certifier records (as some already do for weld and heat-treat lots) rather than shop-level certification, the individual operator becomes the required signature.

  • plausible judgment accountability +3

    Ownership of the disposition call on nonconforming material — if MRB (material review board) authority for scrap/rework/use-as-is is formally delegated to floor certifiers rather than engineers, as happens in lean shops, the role owns a consequential ambiguous call with cost and airworthiness consequences.

  • plausible embodiment +2

    Growth of the defense/aerospace MRO and repair segment, where the workpiece is a used, deformed, corroded part with no as-built CAD model — Navy shipyard and depot-level repair hiring (e.g., NAVSEA public shipyard trades expansion) puts this work in unfixtured, in-situ positions robots cannot reach or model.

The limit. No realistic route to a trust premium: buyers purchase parts to spec and never learn who touched them. Even with every lever, the moat stays capital-cost-and-part-variety, which erodes as cell setup cost falls; ceiling is roughly the mid-50s.

These are conditions, not forecasts — what would have to happen, not what will. Specific rules, cases and bills are named so you can go and check whether they exist and where they stand; verify before relying on any of them. Nothing here is legal or financial advice.

Where this work is, and what it pays there

BLS metro figures for 68 areas. The verdict above does not change by city — the rubric judges what the work involves, not where it happens — but pay and headcount do, and the national median hides a very wide range.

Most of these jobs

Atlanta-Sandy Springs-Roswell, GA 980 $44,440 -3%
Los Angeles-Long Beach-Anaheim, CA 910 $47,860 +4%
Dallas-Fort Worth-Arlington, TX 370 $48,890 +6%
Riverside-San Bernardino-Ontario, CA 370 $45,270 -1%
Houston-Pasadena-The Woodlands, TX 330 $38,270 -17%
Philadelphia-Camden-Wilmington, PA-NJ-DE-MD 330 $50,070 +9%
Portland-Vancouver-Hillsboro, OR-WA 330 $57,140 +24%
Seattle-Tacoma-Bellevue, WA 300 $65,760 +43%

Best paid

Davenport-Moline-Rock Island, IA-IL 40 $83,870 +83%
Albany-Schenectady-Troy, NY 50 $74,050 +61%
Seattle-Tacoma-Bellevue, WA 300 $65,760 +43%

Percentages are against this occupation's national median of $45,950. Counts are jobs in that metro, not vacancies. Metros where the BLS suppressed the cell are absent rather than shown as zero.

Who is actually doing this — nobody, on the record

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.

Read that as a gap in the reporting we can see, not proof of absence — the dispatch runs on English-language feeds and misses plenty. If you know of a case, tell us, or add a field report from inside the job.

Quick take — do you do this job?

Has AI actually changed your work? One tap, anonymous, and the running tally is public. Nothing else is asked of you.

Self-reported and unverified — a sentiment signal, not a survey. One response per person per occupation; you can change your answer.

Field reports — what people say has changed

No field reports yet. A written account takes a paragraph rather than a tap, goes to an editor before it appears, and is the one thing on this page the rubric cannot produce on its own.

File a field report

Concrete beats general: a tool that arrived, a task that moved, a headcount decision you watched happen. Don't include anything that identifies you or your employer if that would put you at risk.

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