AI Automation Index

Will AI Replace Grinding and Polishing Workers, Hand?

Task-level automation exposure for Grinding and Polishing Workers, Hand: 17 O*NET tasks scored against their work activities, plus the simulator.

E-E-A-T Verified

Developed & audited by Gini Loh

Automation Exposure

21% weighted task index

17 of 17 tasks scored

Median Salary

$42,660 / year

BLS OEWS, May 2025 — this exact occupation

Employment Level

Low

10,510 people hold this job — size, not growth

Projected 2025–35

-19.2% employment change

700 openings a year · BLS line item

Pay by state

BLS OEWS publishes 40 state estimates for this occupation. Each is its own survey estimate, not the national median adjusted for local prices.

$28,640 – $56,850

Highest medians

Vermont $56,850

Minnesota $51,930

Rhode Island $51,630

Montana $50,460

Virginia $48,830

Lowest medians

New Mexico $28,640

Louisiana $33,160

Tennessee $33,830

Alabama $35,620

Illinois $36,590

State figures come from the 51-9022 row in the May 2025 state panel. States where the estimate was suppressed or too small to publish are absent.

What the score is made of

Each task is mapped to its work activities, scored for AI automation potential, and weighted by how important those activities are to the job. These are the components.

Automation potential 21%

Importance-weighted mean of the scored tasks. This is the headline index.

Physical work 61%

Share of weighted tasks in hands-on or machine-operating work activities.

Judgment & influence 7%

Share in analysis, decisions, teaching, directing, advising, or caring for others.

Routine administration 4%

Share in documenting, recording, and administrative activities.

Rewritten by O*NET 0%

Share of weighted tasks O*NET rewrote in a recent update. Reported, not folded into the score.

Consequence of error 8/100 Low

O*NET's own rating of how serious an uncorrectable mistake would be here — respondents, not us. Deliberately not in the index: the score measures what AI can do with the task content, and multiplying it by stakes would be our judgment dressed as data.

Constituent Task Mix

17 tasks for this occupation, weighted by work-activity importance. Shares below are of total task weight, not task count.

High exposure (≥ 60% of the task is automatable) 11%

2 tasks

Medium exposure (≥ 35%) 7%

1 tasks

Low exposure (below 35%) 82%

14 tasks

How would you survive?

Move your week away from the high-exposure tasks and toward the ones that need judgment. The simulator recalculates the index as you shift the mix.

Simulate Upskilling →

Constituent Tasks

#14334 · Core · 29% automatable

Verify quality of finished workpieces by inspecting them, comparing them to templates, measuring their dimensions, or testing them in working machinery.

visual inspection — Vision AI assists but physical comparison is human

Compare physical characteristics of materials or products to specifications or standards. Measure dimensions of completed products or workpieces to verify conformance to specifications.

#14329 · Core · 8% automatable

Grind, sand, clean, or polish objects or parts to correct defects or to prepare surfaces for further finishing, using hand tools and power tools.

physical manipulation — Hands-on cleaning of physical workpieces

Clean workpieces or finished products. Polish materials, workpieces, or finished products. Smooth metal surfaces or edges.

#14333 · Core · 22% automatable

Measure and mark equipment, objects, or parts to ensure grinding and polishing standards are met.

physical manipulation — Marking reference points requires hands-on measurement

Measure materials to mark reference points, cutting lines, or other indicators.

#14336 · Core · 8% automatable

Trim, scrape, or deburr objects or parts, using chisels, scrapers, and other hand tools and equipment.

physical manipulation — Manual trimming of workpieces

Trim excess material from workpieces.

#14330 · Core · 12% automatable

Mark defects, such as knotholes, cracks, and splits, for repair.

physical manipulation — Marking workpieces is hands-on physical task

Mark products, workpieces, or equipment with identifying information.

#14340 · Core · 66% automatable

Study blueprints or layouts to determine how to lay out workpieces or saw out templates.

visual inspection — Blueprints need spatial reading, human verifies sequence

Review blueprints or other instructions to determine operational methods or sequences.

#14331 · Core · 12% automatable

Move controls to adjust, start, or stop equipment during grinding and polishing processes.

physical manipulation — Grinding requires hands-on control and feel

Operate grinding equipment.

#14338 · Core · 5% automatable

Load and adjust workpieces onto equipment or work tables, using hand tools.

physical manipulation — Mounting workpieces is physical loading

Load materials into production equipment. Mount materials or workpieces onto production equipment.

#14344 · Core · 10% automatable

Repair and maintain equipment, objects, or parts, using hand tools.

physical manipulation — Hands-on repair of production machinery

Repair production equipment or tools. Maintain production or processing equipment.

#14332 · Core · 55% automatable

Select files or other abrasives, according to materials, sizes and shapes of workpieces, amount of stock to be removed, finishes specified, and steps in finishing processes.

decision support — Equipment selection against specs; human verifies fit

Select production equipment according to product specifications.

#14346 · Core · 4% automatable

File grooved, contoured, and irregular surfaces of metal objects, such as metalworking dies and machine parts, to conform to templates, other parts, layouts, or blueprint specifications.

physical manipulation — Reshaping metal requires hands-on machining

Reshape metal workpieces to established specifications.

#14345 · Core · 10% automatable

Sharpen abrasive grinding tools, using machines and hand tools.

physical manipulation — Manual sharpening of cutting tools

Sharpen cutting or grinding tools.

#14339 · Core · 8% automatable

Transfer equipment, objects, or parts to specified work areas, using moving devices.

physical manipulation — Physical moving of products between work areas

Move products, materials, or equipment between work areas.

#14337 · Supplemental · 6% automatable

Remove completed workpieces from equipment or work tables, using hand tools, and place workpieces in containers.

physical manipulation — Physically extracting parts from production equipment

Remove products or workpieces from production equipment.

#14335 · Supplemental · 82% automatable

Record product and processing data on specified forms.

data analysis — Record production data into structured logs

Record operational or production data.

#14341 · Supplemental · 10% automatable

Apply solutions and chemicals to equipment, objects, or parts, using hand tools.

physical manipulation — Applying solutions to equipment is manual

Apply solutions to production equipment.

#14348 · Supplemental · 5% automatable

Clean brass particles from files by drawing file cards through file grooves.

physical manipulation — Hands-on cleaning of equipment in unstructured settings

Clean production equipment.

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Community Sentiment

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Do you agree with the AI automation risk score calculated for this occupation?

Method

How this was scored

1. Tasks. O*NET task statements for this occupation, from a release whose newest record is dated 08/2026.
2. Work activities. Each task maps to 1–5 Detailed Work Activities; each activity belongs to one of 41 Generalized Work Activities that O*NET rates for importance (1–5) in this occupation.
3. Automation potential. Every work activity carries one score for how far current AI can perform it end-to-end. Tasks inherit the mean of their activities.
4. Weighting. Task weight = 0.35 + 0.65 × (importance − 1)/4, scaled by how often the task is performed and by 0.7 for Supplemental tasks. Importance is the task's own O*NET rating where it exists (18,369 of 18,838 tasks); the rest inherit their work activities' importance. The index is the weighted mean.

Check: across the 910 occupations where O*NET also rates how far machine speed sets the pace, this index moves opposite to it (Spearman ρ = -0.49). The more a job is paced by equipment, the less of its task content AI can address — the relationship you would expect if the scoring is working.

Sources · O*NET 31.0 (task records to 08/2026) · BLS OEWS May 2025 · BLS projections 2025-2035 · rubric v2.1 · tasks for O*NET, not a forecast

See the full method →

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