← Risk register SOC 51-9124 · reviewed 2026-08-11

Coating, Painting, and Spraying Machine Setters, Operators, and Tenders

158,740 US workers · median $48,250/yr · Production

EXPOSED

Spray painting is the one factory task industrial robots genuinely mastered decades ago — automotive and appliance lines are already largely robotic, and the remaining human jobs cluster in small-batch, odd-geometry, touch-up, and mixed-material work where fixturing and programming a robot costs more than a person. The work is physical and hands-on, which shields it from language AI entirely, but not from continued capital substitution as vision-guided spray cells get cheaper and easier to reprogram. No license, no client relationship, and most of the judgment is recipe-following on viscosity, film thickness, and cure specs.

10-year outlook: Employment keeps eroding in high-volume plants while stable-to-growing demand persists in small-batch, repair, and custom finishing — expect the job to survive mainly as robot-tending plus skilled touch-up.

US employment, 2019–2025+8.5%
146,350158,740 workers

Dipped in 2020, then grew past where it started.

Median pay $38,150 → $48,250 +1.2% in real terms (nominal +26.5%, 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

+0.7% 165,500 → 166,700 on the projections basis

Exposed, but growing

AI can already do a lot of these tasks, and the BLS still expects +0.7% 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.

~15,800 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.

DoperCoaterDaggerDipperTinnerBlackerBronzerBrownerDopemanLatexerPainterColormanEnamelerRedipperAir DrierBlackenerVarnisherBonderizerDip FillerHot DipperMarbleizerParaffinerSensitizerTip Bander

Score — 35/100 resistance

Holding it up: embodiment (14/20). 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: 10 + 14 + 2 + 3 + 6 = 35. · Scored 2026-08-11, and re-examined when evidence accumulates rather than on a schedule.

Task resistance 10/20

Mixed — a routine tier and a judgment tier Robotic spray cells took over high-volume flat and predictable-geometry work decades ago, but the surviving jobs — masking irregular castings, blending a repair panel, spraying furniture or one-off fabricated parts, hand-tending powder booths between color changes — still need someone to hang, mask, feel out overspray and adjust the gun mid-pass, which is why this sits at 10 rather than the 4 an automotive line operator would get.

Embodiment 14/20

Hands-on in uncontrolled environments You are inside a booth in a Tyvek suit and supplied-air respirator, on your feet, reaching around parts on hangers or a turntable, handling solvents and flammable coatings under OSHA 1910.107 booth ventilation rules — the environment is uncontrolled enough (part geometry, temperature, humidity affecting flash-off) to sit near the top, held off 18-20 only because you work in a fixed booth rather than climbing a bridge or a tank exterior.

Liability shield 2/20

No licence, no signature requirement There is no coating operator license; the 2 reflects only the narrow credentialing that does exist — respirator fit-testing, hazmat and confined-space training, sometimes an EPA 6H rule certification for autobody refinishing — none of which makes you personally answerable for a defect, since the shop and its QC sign-off carry the warranty.

Trust premium 3/20

Anonymous artifact production The customer sees a finished part, not you; a fleet manager or OEM buyer judges the gloss, DFT reading, and adhesion test, and the only relationship that carries weight is the internal one where a foreman knows which sprayer to give the hard blend job to.

Judgment & accountability 6/20

Executes defined procedures on defined inputs Most calls are against a written spec — mix ratio, viscosity by Zahn cup, gun distance, mil thickness, flash and cure times, booth temp — and the discretion you do own (stop and re-sand, adjust for humidity, reject a run) affects rework cost rather than safety or money at scale, so 6 rather than 10.

Confidence: high · 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

How to future-proof this job

Training paths for your skill gaps: MIT OpenCourseWare — operations management free · Coursera — customer service and client-facing skill courses free to audit · Coursera — teaching and instructional design, audit free free to audit · Coursera — people management and team leadership specialisations free to audit

All 35 skills ranked by how many jobs they open →

Where this experience transfers — occupations you could move toward

Computed from U.S. Dept. of Labor O*NET skill and knowledge profiles: high overlap with what you already do, a materially higher resistance score, no large jump in required training, and no licence you would have to start a new pipeline to get. Targets that pay meaningfully less, that are themselves COOKED, or whose own headcount is falling are excluded — a move into a shrinking trade is not an escape.

Refractory Materials Repairers, Except Brickmasons EXPOSED · 65/100 · you already have ~90% of the skill profile

Skills to close: Operations Analysis

Furniture Finishers EXPOSED · 52/100 · you already have ~82% of the skill profile

Skills to close: Service Orientation, Instructing, Management of Personnel Resources, Operations Analysis

Refuse and Recyclable Material Collectors EXPOSED · 55/100 · you already have ~81% of the skill profile

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 50/100, still EXPOSED.

5 specific changes that would raise this score
  • already happening liability shield +4

    Named-applicator certification schemes tied to warranty rather than occupational license: SSPC/AMPP QP-1 and NACE coating applicator certification are already contract prerequisites on DOT bridge and Navy work, and NBIS bridge-coating specs increasingly require a certified applicator of record on the daily report. Wider adoption of certified-applicator sign-off on the inspection record, plus EPA 6H/NESHAP rules requiring documented trained-operator status for spray of target HAPs, moves this from 2 toward the low end of protected work

  • already happening embodiment +3

    If remaining volume concentrates further in genuinely un-fixturable work — aerospace MRO touch-up on assembled airframes, bridge and tank field coating, restoration and custom refinish — the residual job is confined-space, scaffolded, variable-geometry spraying that vision-guided cells cannot reach without per-job tooling cost exceeding a person's wage

  • plausible task resistance +3

    Genuine two-tier split: if robotic cells absorb flat/repeatable panels, what remains is defect diagnosis (fisheye, orange peel, solvent pop), blend-and-fade color matching on metallics, and adhesion troubleshooting across mixed substrates — the tier that requires reading a failed film and deciding on rework

  • plausible judgment accountability +3

    If surface-prep and cure decisions become the documented failure point in coating-warranty disputes — the applicator's call on dew point, hold-time, and recoat window entered in a signed daily log that insurers and owners rely on — the role owns a consequential call under ambiguity rather than following a recipe

  • plausible trust premium +2

    Narrow route only: custom/restoration refinish (classic auto, motorcycle, guitar, high-end furniture) where buyers pay explicitly for hand-laid finish. Real but tiny relative to 158k workers; no route exists for industrial-line coating

The limit. Even with every lever, this stays a capital-substitution story rather than an AI-capability story: the binding constraint is robot cell cost per part variant, and that falls regardless of what language models do. Certification levers protect the infrastructure and MRO segments, not the shop-floor majority.

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 336 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

Dallas-Fort Worth-Arlington, TX 5,050 $49,350 +2%
Houston-Pasadena-The Woodlands, TX 4,590 $46,950 -3%
Los Angeles-Long Beach-Anaheim, CA 4,580 $54,870 +14%
Chicago-Naperville-Elgin, IL-IN 3,680 $48,910 +1%
New York-Newark-Jersey City, NY-NJ 3,250 $58,520 +21%
Seattle-Tacoma-Bellevue, WA 2,640 $63,030 +31%
Detroit-Warren-Dearborn, MI 2,590 $44,220 -8%
Atlanta-Sandy Springs-Roswell, GA 2,350 $46,930 -3%

Best paid

Norwich-New London-Willimantic, CT 70 $69,600 +44%
Ames, IA 60 $69,090 +43%
Springfield, OH 110 $67,070 +39%

Percentages are against this occupation's national median of $48,250. 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 35. 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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Kept current

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