← Risk register SOC 53-7061 · reviewed 2026-08-11

Cleaners of Vehicles and Equipment

380,430 US workers · median $35,830/yr · Transportation

EXPOSED

Almost nothing here is text or screen work, so language AI barely touches the job — washing, waxing, vacuuming interiors, steam-cleaning heavy equipment and detailing wheel wells all require hands in awkward physical spaces. The real threat is old-fashioned mechanization: tunnel washes, automated undercarriage sprayers and self-service bays already absorb the high-volume exterior work, and AI-driven scheduling and payment kiosks strip out the attendant roles around them. What resists is interior detailing, paint correction, and cleaning irregular fleet and construction equipment, where every unit is shaped differently and machines can't reach.

10-year outlook: Employment holds up in interior detailing and mobile/fleet work but keeps thinning at fixed-site washes as automated tunnels and self-service bays expand, with wages staying low unless you sell a specialty service.

US employment, 2019–2025-0.6%
382,670380,430 workers

Roughly flat across the period, with year-to-year wobble.

Median pay $25,800 → $35,830 +11.1% in real terms (nominal +38.9%, 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

+3.9% 410,100 → 426,200 on the projections basis

Exposed, but growing

AI can already do a lot of these tasks, and the BLS still expects +3.9% 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.

~56,200 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.

WiperTalcerWasherCleanerFlusherScraperSteamerDetailerPlatemanPolisherSalvagerCar DryerCar WiperSimonizerBus WasherCan WasherCar CarderCar CooperCar WasherNet WasherPan WasherSoapstonerSterilizerTub Washer

Score — 40/100 resistance

Holding it up: embodiment (17/20). Weakest point: liability shield (1/20).

Five dimensions, 0–20 each, summed. Higher means more protected. The arithmetic is shown so you can check it: 15 + 17 + 1 + 4 + 3 = 40. · Scored 2026-08-11, and re-examined when evidence accumulates rather than on a schedule.

Task resistance 15/20

Tasks largely resist digitisation Reaching under a bulldozer track to steam off caked mud, extracting pet hair from seat seams and hand-polishing a clearcoat without burning through it are tasks no tunnel-wash gantry performs — 15 rather than 18 because the highest-volume part of the trade, exterior sedan washing, has already been mechanized for decades.

Embodiment 17/20

Hands-on in uncontrolled environments The work is done kneeling on wet concrete, in outdoor lots in July heat and January cold, handling pressure wands at 1,500+ PSI and solvent chemicals inside unventilated cabs — 17 rather than 20 only because a share of the workforce operates inside a fixed bay rather than roadside or on a job site.

Liability shield 1/20

No licence, no signature requirement No state licence gates vehicle washing; you can start Monday with no credential, and if a wand strips trim or a wheel-acid etches a rim the shop's insurance and the owner absorb it, not you.

Trust premium 4/20

Anonymous artifact production Fleet contracts and dealership prep work are awarded on price and turnaround time by a manager who never learns the washer's name, though a small tier of independent high-end detailers does build a repeat client book on reputation — that minority is what keeps this off the floor.

Judgment & accountability 3/20

Executes defined procedures on defined inputs Chemical selection, wash sequence and dry-time are set by the shop's SOP and product labels; the discretion is limited to spotting a scratch before you start and flagging it, not deciding what happens next.

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, physical-presence

How to future-proof this job

Training paths for your skill gaps: MIT OpenCourseWare — problem-solving and analytical method courses free · Coursera — critical thinking and logic, audit free free to audit · Coursera — teaching and instructional design, audit free free to audit · Coursera — project coordination and cross-team delivery free to audit · Purdue OWL — the standard reference for professional writing free · Khan Academy — reading and vocabulary, all levels, free free · 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.

Tree Trimmers and Pruners SAFE · 70/100 · you already have ~68% of the skill profile

Skills to close: Complex Problem Solving, Critical Thinking, Instructing, Coordination

Tank Car, Truck, and Ship Loaders EXPOSED · 53/100 · you already have ~67% of the skill profile

Skills to close: Writing, Reading Comprehension, Complex Problem Solving, Management of Personnel Resources

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 54/100, still EXPOSED.

5 specific changes that would raise this score
  • already happening trust premium +4

    High-end detailing already sells the human: ceramic-coating and paint-correction warranties from brands like Gtechniq or XPEL are only honored when applied by a named accredited installer, so the buyer is paying for a specific person's hands. Expansion of installer-accreditation warranty models raises this.

  • already happening task resistance +2

    Tunnel and automated-bay systems absorb the remaining volume exterior work, leaving the occupation defined by interior extraction, paint correction, odor/biohazard remediation and odd-shaped equipment — tasks no gantry reaches. This is a genuine two-tier job and the routine tier is already being stripped out.

  • plausible liability shield +3

    Environmental permitting could bite harder: EPA/state stormwater rules (NPDES) plus local ordinances already require wash-water containment, and OSHA-regulated confined-space and respirator rules apply to tanker and rail-car interior cleaning. If mobile detailing operators are pushed into named-permit-holder or certified-technician regimes (as some California and Washington municipalities have moved toward), a specific human's certification is attached to each job.

  • plausible judgment accountability +3

    Aviation and rail cleaning where the cleaner's inspection is part of the safety chain — biohazard and infectious-material decontamination protocols, or IATA/airline cabin release sign-offs — makes the worker the person who decides an asset is fit to return to service.

  • plausible embodiment +2

    Growth in EV and ADAS fleets makes cleaning a sensor-aware task: manufacturer service bulletins (e.g. Tesla, Rivian) already restrict pressure washing near camera housings, radar and HV connectors, forcing hand work in confined, variable geometry rather than machine passes.

The limit. Even with all of these, the bulk of the 380k workforce is high-volume car wash and fleet labor where wages, turnover and mechanization set the ceiling; the licensed, warranty-backed detailing tier is a small minority of the SOC and cannot lift the occupation-level score far.

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 388 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

New York-Newark-Jersey City, NY-NJ 19,280 $41,540 +16%
Los Angeles-Long Beach-Anaheim, CA 15,950 $37,540 +5%
Chicago-Naperville-Elgin, IL-IN 12,030 $36,580 +2%
Dallas-Fort Worth-Arlington, TX 9,970 $31,350 -13%
Houston-Pasadena-The Woodlands, TX 9,020 $29,650 -17%
Atlanta-Sandy Springs-Roswell, GA 7,040 $31,690 -12%
Miami-Fort Lauderdale-West Palm Beach, FL 6,880 $34,310 -4%
Philadelphia-Camden-Wilmington, PA-NJ-DE-MD 5,680 $35,160 -2%

Best paid

Grand Island, NE 460 $50,320 +40%
Decatur, IL 150 $49,370 +38%
St. Joseph, MO-KS 430 $49,140 +37%

Percentages are against this occupation's national median of $35,830. 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 40. 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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