AI exposure by occupation, O*NET 51-9192.00

Will AI replace Cleaning, Washing, and Metal Pickling Equipment Operators and Tenders?

Cleaning, Washing, and Metal Pickling Equipment Operators and Tenders: AI does not yet handle any of the role's 11 tasks; most of the work is hands-on, and the part AI can address mostly needs an efficient-tier model.

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Every task, scored

The 11 tasks O*NET 30.3 lists for Cleaning, Washing, and Metal Pickling Equipment Operators and Tenders, from most to least exposed. None reaches 60, the level at which AI already handles a task.

Task AI exposure Evidence Model tier Importance
Drain, clean, and refill machines or tanks at designated intervals, using cleaning solutions or water. 50 Estimated Efficient 4.0
Add specified amounts of chemicals to equipment at required times to maintain solution levels and concentrations. 20 Estimated Efficient 4.3
Observe machine operations, gauges, or thermometers, and adjust controls to maintain specified conditions. 20 Estimated Efficient 4.1
Examine and inspect machines to detect malfunctions. 20 Estimated Efficient 3.8
Set controls to regulate temperature and length of cycles, and start conveyors, pumps, agitators, and machines. 15 Estimated No tier 4.1
Draw samples for laboratory analysis, or test solutions for conformance to specifications, such as acidity or specific gravity. 15 Estimated No tier 4.1
Adjust, clean, and lubricate mechanical parts of machines, using hand tools and grease guns. 15 Estimated No tier 4.0
Operate or tend machines to wash and remove impurities from items such as barrels or kegs, glass products, tin plate surfaces, dried fruit, pulp, animal stock, coal, manufactured articles, plastic, or rubber. 15 Estimated No tier 4.0
Record gauge readings, materials used, processing times, or test results in production logs. 15 Estimated No tier 3.8
Load machines with objects to be processed and unload them after cleaning, placing them on conveyors or racks. 15 Estimated No tier 3.8
Measure, weigh, or mix cleaning solutions, using measuring tanks, calibrated rods or suction tubes. 15 Estimated No tier 3.6

Observed: scored from AI use recorded in the Anthropic Economic Index (June 2026 release), 0 of 11 tasks. Estimated: scored from the task's O*NET 30.3 work activity, 11 of 11. Importance is O*NET's 1 to 5 rating of how central the task is. Model tier is the lowest tier that can do the task under the published rubric; "No tier" marks hands-on work.

The model tier this role needs

An efficient-tier model or lower covers 37% of the role's importance-weighted task work. 37% of the work is something AI can address at some tier, and 63% is hands-on.

Efficient, standard and frontier tiers come from the JobRoute model tier reference. The recommended tier is the lowest one that covers 80% of the work AI can address. How the method works.

Wages, employment and outlook

US employment
14,760
Median annual wage
$43,530
Middle half of earners
$37,310 to $49,320
Projected change, 2024 to 2034
+3.6%

Employment and wages: BLS Occupational Employment and Wage Statistics, May 2025, national. Projection: BLS Employment Projections 2024 to 2034.

Adjacent roles

The occupations that reuse the most of this role's skills, with the usual time to move. These are the first places to look when you plan to redeploy or retrain people in this role.

Skill overlap and transition time from the JobRoute role adjacency graph on O*NET 30.3 skills.

Questions about Cleaning, Washing, and Metal Pickling Equipment Operators and Tenders and AI

Will AI replace Cleaning, Washing, and Metal Pickling Equipment Operators and Tenders?

Not on current evidence. None of the 11 tasks O*NET lists for this occupation reaches a task exposure of 60, the level at which JobRoute counts a task as handled by AI, and the role's importance-weighted exposure is 20 out of 100. JobRoute scores tasks, not whole jobs, so the score shows how much of the work changes rather than whether the job disappears.

What is the AI exposure of Cleaning, Washing, and Metal Pickling Equipment Operators and Tenders?

20 out of 100 on JobRoute's task exposure measure, the importance-weighted average of the role's O*NET task scores. Higher means more of the work is AI-doable today. 0 of the 11 task scores are observed in the Anthropic Economic Index (June 2026 release), and the other 11 are estimated from each task's O*NET work activity.

Which Cleaning, Washing, and Metal Pickling Equipment Operators and Tenders tasks can AI already do?

None reaches 60 yet. The most exposed task is: Drain, clean, and refill machines or tanks at designated intervals, using cleaning solutions or water, at 50 out of 100.

What AI model tier does this role need?

An efficient-tier model or lower covers 37% of the role's importance-weighted task work, and 63% is hands-on work that no model tier covers. JobRoute assigns each task the lowest tier that can do it under a published rubric and recommends the lowest tier that covers 80% of the work AI can address.

How many people work as Cleaning, Washing, and Metal Pickling Equipment Operators and Tenders, and what do they earn?

14,760 people in the United States, with a median annual wage of $43,530 (BLS Occupational Employment and Wage Statistics, May 2025). BLS Employment Projections expect a change of +3.6% from 2024 to 2034.

How to cite

Data version 2026-11-02, JobRoute method v1.0.0. Download all occupations or this occupation as JSON. Methodology.

JobRoute (2026). AI exposure: Cleaning, Washing, and Metal Pickling Equipment Operators and Tenders. Data version 2026-11-02, method v1.0.0. Built on O*NET 30.3, BLS OEWS May 2025 and the Anthropic Economic Index (June 2026). CC BY 4.0. https://www.jobroute.ai/jobs/cleaning-washing-and-metal-pickling-equipment-operators-and-tenders

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