Skills it runs on
The capabilities O*NET rates most important for this occupation — the human ground the work is built on.
See all skills →Grinding and Polishing Workers, Hand
Occupation · SOC 51-9022.00
Grind, sand, or polish, using hand tools or hand-held power tools, a variety of metal, wood, stone, clay, plastic, or glass objects. Includes chippers, buffers, and finishers.
Also called: Chipper · Finisher · Grinder · Polisher · Buffer · Casting Finisher · Jewelry Polisher · Knife Grinder · Metal Finisher · Stand Grinder · Aircraft Skin Burnisher · Balance Wheel Arm Burnisher
Job family: Production Occupations
Take this to your AI
A source-stamped Markdown brief of this occupation — paste it into an agent, or fetch
/roles/role-51-9022-00/context.md directly.
AI work map
A fast read on where AI already shows up in this occupation, where it stays a copilot, where humans remain in the loop, and what the labor market is doing. Built from observed Claude.ai conversations mapped to O*NET tasks and from published research — measures of usage and exposure, not advice or predictions that the job is going away.
Market signal
Independent published positions, read together — not a forecast.
- Declining employment outlook (-21.2% by 2034)
- 800 openings/yr
- Low AI exposure
- Median pay $41,690/yr
- Work is mostly on-site (not teleworkable)
- 2013 flagged this for computerization (94th); today's AI task-overlap is comparatively low (10th)
10th-percentile task overlap — yet about 800 openings a year (-21.2% projected, BLS) . What exposure means →
AI & job outlook
What today's research says about this occupation's exposure to AI, how AI is actually being used in it, and where employment is headed. These are positions within published studies — measures of exposure and usage, not predictions that this job will disappear.
Exposure to current AI
Each study uses its own scale, so the raw scores are not comparable across rows — the percentile (this job's rank among all U.S. occupations with data) is the comparable figure, and sizes the bars.
| Measure | Rank vs all occupations | Percentile | Score |
|---|---|---|---|
| Overall AI exposure (Felten et al.) Low | 13th | -1.1 | |
| LLM task exposure, γ (OpenAI / Eloundou) Low | 6th | 0.0 | |
| AI assistant applicability (Microsoft) Low | 24th | 0.1 |
OpenAI's exposure study scores tasks three ways: with a language model alone (α 0.0), with simple added tooling (β 0.0), and including AI-powered software (γ 0.0). Higher means more of the job's tasks could be done at least twice as fast — not that they will be automated away.
This job mostly cannot be done remotely (Dingel–Neiman) — its hands-on tasks sit outside what software-based AI reaches.
Mixed signals. Today's AI/LLM studies show relatively low exposure for this job, but the older (2013) Frey–Osborne work rated it higher for computerization and robotics. Different eras, different technologies — the AI measures above reflect the current state.
Historical automation estimate (2013)
A pre-LLM (2013) estimate of how automatable this job is by computerization and robotics. Shown for historical context only — it is not part of any current AI ranking.
Frey–Osborne probability 1.0 · 94th percentile among occupations · High
Job outlook
Independent U.S. Bureau of Labor Statistics employment projection for 2024–2034 — a labor-market forecast, not an AI-impact forecast.
| Outlook | Declining · -21.2% by 2034 |
| Projected annual openings | 800 |
| Employment 2024 → 2034 | 11,800 → 9,300 |
“Annual openings” counts new jobs plus replacements for workers who leave the occupation, so it can be large even when growth is modest.
Where this work sits on the global GenAI gradient
The ILO's 2025 global study scores generative-AI exposure on the international ISCO-08 occupation system, not US SOC. Bridged through the published (and approximate, many-to-many) IBS O*NET-SOC ↔ ISCO-08 crosswalk, this US occupation corresponds to the international 2 occupations below. Exposure here means how much of the work's tasks today's AI can attempt — task overlap, not automation, adoption, or jobs lost.
Grinding and Polishing Workers, Hand sits at the 27th percentile of 427
occupations on the global GenAI task-exposure gradient
— exposure eased from 2023 to 2025. Each dot is one occupation; the
ringed one is this work. Exposure is task overlap, not automation or jobs lost.
18% mean task exposure (2025)
27th percentile of 427 placed occupations
−2 pts shift 2023 → 2025
| International occupation (ISCO-08) | Task exposure (2025) | Most tasks fall in |
|---|---|---|
| Glass Makers, Cutters, Grinders and Finishers · 7315 | 19% | Not exposed |
| Metal Polishers, Wheel Grinders and Tool Sharpeners · 7224 | 17% | Not exposed |
Read the whole six-band gradient on the GenAI exposure gradient page. The crosswalk is approximate: a US occupation can map to several international ones, and the ILO scores describe the international occupation, not this exact US role.
Tasks
All 20 tasks O*NET lists for this occupation, ordered by importance. Each links to its own page with AI-exposure and observed-use detail.
- Verify quality of finished workpieces by inspecting them, comparing them to templates, measuring their dimensions, or testing them in working machinery. Core · importance 4.6
- Grind, sand, clean, or polish objects or parts to correct defects or to prepare surfaces for further finishing, using hand tools and power tools. Core · importance 4.5
- Measure and mark equipment, objects, or parts to ensure grinding and polishing standards are met. Core · importance 4.5
- Trim, scrape, or deburr objects or parts, using chisels, scrapers, and other hand tools and equipment. Core · importance 4.4
- Mark defects, such as knotholes, cracks, and splits, for repair. Supplemental · importance 4.4
- Study blueprints or layouts to determine how to lay out workpieces or saw out templates. Supplemental · importance 4.4
- Move controls to adjust, start, or stop equipment during grinding and polishing processes. Core · importance 4.2
- Remove completed workpieces from equipment or work tables, using hand tools, and place workpieces in containers. Core · importance 4.2
- Load and adjust workpieces onto equipment or work tables, using hand tools. Supplemental · importance 4.2
- Repair and maintain equipment, objects, or parts, using hand tools. Core · importance 4.1
- 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. Supplemental · importance 4.0
- Record product and processing data on specified forms. Supplemental · importance 3.9
- 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. Supplemental · importance 3.7
- Apply solutions and chemicals to equipment, objects, or parts, using hand tools. Supplemental · importance 3.6
- Sharpen abrasive grinding tools, using machines and hand tools. Supplemental · importance 3.5
- Transfer equipment, objects, or parts to specified work areas, using moving devices. Core · importance 3.4
- Clean brass particles from files by drawing file cards through file grooves. Supplemental · importance 1.6
- Fill cracks or imperfections in marble with wax that matches the stone color. Supplemental
- Spread emery powder or other polishing compounds on stone, or wet stone surfaces with hoses, and guide buffing wheels over stone to polish surfaces. Supplemental
- Wash grit from stone, using hoses. Supplemental
Work activities
- Clean workpieces or finished products.
- Polish materials, workpieces, or finished products.
- Smooth metal surfaces or edges.
- Mark products, workpieces, or equipment with identifying information.
- Operate grinding equipment.
- Select production equipment according to product specifications.
- Measure materials to mark reference points, cutting lines, or other indicators.
- Compare physical characteristics of materials or products to specifications or standards.
- Measure dimensions of completed products or workpieces to verify conformance to specifications.
- Record operational or production data.
- Trim excess material from workpieces.
- Remove products or workpieces from production equipment.
- Load materials into production equipment.
- Mount materials or workpieces onto production equipment.
- Move products, materials, or equipment between work areas.
- Review blueprints or other instructions to determine operational methods or sequences.
- Apply solutions to production equipment.
- Repair production equipment or tools.
- Maintain production or processing equipment.
- Sharpen cutting or grinding tools.
- Reshape metal workpieces to established specifications.
- Clean production equipment.
Knowledge, skills & abilities
O*NET importance rating, from 1 (not important) to 5 (extremely important).
Abilities
| Arm-Hand Steadiness | 4.0 | |
| Finger Dexterity | 3.8 | |
| Control Precision | 3.8 | |
| Near Vision | 3.8 | |
| Manual Dexterity | 3.6 | |
| Multilimb Coordination | 3.3 | |
| Oral Comprehension | 3.1 | |
| Problem Sensitivity | 3.1 | |
| Information Ordering | 3.1 | |
| Selective Attention | 3.1 | |
| Speech Recognition | 3.1 | |
| Speech Clarity | 3.1 | |
| Oral Expression | 3.0 | |
| Category Flexibility | 3.0 | |
| Flexibility of Closure | 3.0 | |
| Perceptual Speed | 3.0 | |
| Visualization | 3.0 | |
| Rate Control | 3.0 | |
| Trunk Strength | 3.0 | |
| Visual Color Discrimination | 3.0 | |
| Deductive Reasoning | 2.9 | |
| Reaction Time | 2.9 | |
| Static Strength | 2.9 | |
| Extent Flexibility | 2.9 | |
| Auditory Attention | 2.9 |
Knowledge
| Production and Processing | 3.6 | |
| Mechanical | 3.6 | |
| English Language | 3.1 | |
| Mathematics | 2.8 |
Transferable skills
| Quality Control Analysis | 3.4 | |
| Operations Monitoring | 3.3 | |
| Operation and Control | 3.1 | |
| Equipment Maintenance | 3.1 | |
| Repairing | 3.0 | |
| Troubleshooting | 2.9 |
Essential skills
| Active Listening | 2.9 | |
| Speaking | 2.9 | |
| Critical Thinking | 2.9 | |
| Reading Comprehension | 2.8 | |
| Monitoring | 2.8 |
Skills in demand
Skills employers ask for in job postings for this occupation (Lightcast), with whether each is a common or specialized skill.
Tools & technology
| Example | Category | |
|---|---|---|
| Microsoft Excel | Spreadsheet software | Hot technology |
| Microsoft Word | Word processing software | Hot technology |
Work context
How characteristic each condition is of the job, on O*NET's 1–5 context scale (higher = more present in day-to-day work). Each condition links to how it varies across all occupations.
How to get in
- Job zone
- Zone 2 — Job Zone 1-2: Very Little to Some Preparation Needed
- Education
- Usually requires a high school diploma or GED, though some occupations may not.
- Typical entry-level education
- No formal educational credential · BLS, the typical path — not a requirement
- Related experience
- Some occupations may need little or no previous experience; others require several months to a year of experience. For example, landscaping and groundskeeping workers might require very little training or previous experience, while agricultural equipment operators can benefit from on-the job training.
- Preparation level
- SVP (Below 6.0) — total schooling plus on-the-job experience.
Education of current workers
Share of people in this occupation at each level of education.
| High School Diploma | 37.3% | |
| Less than a High School Diploma | 26.7% | |
| Some College Courses | 11.9% |
Interests & work styles
The interests and personal qualities O*NET associates with people who do this work.
Career interests (Holland / RIASEC)
| Realistic | 7.0 | |
| Conventional | 3.3 | |
| Artistic | 2.0 | |
| Investigative | 1.5 | |
| Social | 1.1 |
Interest areas
| Physical/Manual Labor | 6.0 | |
| Construction/Woodwork | 3.8 | |
| Mechanics/Electronics | 2.0 | |
| Engineering | 1.7 | |
| Applied Arts and Design | 1.4 | |
| Transportation/Machine Operation | 1.3 | |
| Visual Arts | 1.2 | |
| Physical Science | 1.1 |
Work styles
| Attention to Detail | 2.4 | |
| Dependability | 2.0 | |
| Cautiousness | 1.4 |
Wages & employment
U.S. · annual wages (BLS OEWS)
| 10th percentile | $32,120 |
| 25th percentile | $36,660 |
| Median (50th) | $41,690 |
| 75th percentile | $48,410 |
| 90th percentile | $57,250 |
| People employed | 11,850 |
Industries that employ this occupation
Where these workers are employed, by number of jobs (national, BLS OEWS). Pay shown is the occupation's national median, not industry-specific.
| Industry | Workers | National median pay |
|---|---|---|
| Manufacturing · Sector | 10,010 | $41,710 |
| Jewelry and Silverware Manufacturing · National industry | 940 | $39,420 |
| Machine Shops · National industry | 750 | $46,020 |
| Other Services (except Public Administration) · Sector | 470 | $45,160 |
| Administrative and Support and Waste Management and Remediation Services · Sector | 440 | $36,920 |
| Temporary Help Services · National industry | 360 | $36,510 |
| Wholesale Trade · Sector | 350 | $41,480 |
| Construction · Sector | 250 | $46,640 |
| Retail Trade · Sector | 90 | $39,870 |
| Masonry Contractors · National industry | 50 | $35,210 |
| Management of Companies and Enterprises · Sector | — | $44,070 |
Where this work is most concentrated
Industries where this occupation is far more common than in the economy as a whole. The location quotient is how many times more concentrated it is here (a value of 5 means five times its economy-wide share).
| Industry | Concentration | Workers |
|---|---|---|
| Jewelry and Silverware Manufacturing · National industry | 614× | 940 |
| Machine Shops · National industry | 37.57× | 750 |
| Manufacturing · Sector | 10.21× | 10,010 |
| Temporary Help Services · National industry | 1.77× | 360 |
| Other Services (except Public Administration) · Sector | 1.38× | 470 |
| Wholesale Trade · Sector | 0.75× | 350 |
| Administrative and Support and Waste Management and Remediation Services · Sector | 0.63× | 440 |
| Construction · Sector | 0.4× | 250 |
Related occupations
Part of the Advanced Manufacturing career cluster.
- Grinding, Lapping, Polishing, and Buffing Machine Tool Setters, Operators, and Tenders, Metal and Plastic · 51-4033.00 Compare →
- Tool Grinders, Filers, and Sharpeners · 51-4194.00 Compare →
- Woodworking Machine Setters, Operators, and Tenders, Except Sawing · 51-7042.00 Compare →
- Cutting and Slicing Machine Setters, Operators, and Tenders · 51-9032.00 Compare →
- Molders, Shapers, and Casters, Except Metal and Plastic · 51-9195.00 Compare →
- Cutting, Punching, and Press Machine Setters, Operators, and Tenders, Metal and Plastic · 51-4031.00 Compare →
- Lathe and Turning Machine Tool Setters, Operators, and Tenders, Metal and Plastic · 51-4034.00 Compare →
- Tool and Die Makers · 51-4111.00 Compare →
- Milling and Planing Machine Setters, Operators, and Tenders, Metal and Plastic · 51-4035.00 Compare →
- Crushing, Grinding, and Polishing Machine Setters, Operators, and Tenders · 51-9021.00 Compare →
- Machine Feeders and Offbearers · 53-7063.00 Compare →
- Rolling Machine Setters, Operators, and Tenders, Metal and Plastic · 51-4023.00 Compare →
Side-by-side comparisons place two occupations’ pay, preparation, skills, and AI exposure on the same page — same data, same scale, no forecast.
What you can do with this
Options the data surfaces for Grinding and Polishing Workers, Hand — not advice or a forecast. Each is a real cross-link you can follow into the evidence.
Skills that travel
Capabilities this work builds that are used across many other occupations.
Adjacent roles
Occupations O*NET rates as related — the nearby moves on the map.
- Grinding, Lapping, Polishing, and Buffing Machine Tool Setters, Operators, and Tenders, Metal and Plastic Compare →
- Tool Grinders, Filers, and Sharpeners Compare →
- Woodworking Machine Setters, Operators, and Tenders, Except Sawing Compare →
- Cutting and Slicing Machine Setters, Operators, and Tenders Compare →
- Molders, Shapers, and Casters, Except Metal and Plastic Compare →
Paths in
How people typically prepare for this work.
- No formal educational credential · typical entry level
- Job zone 2 — Job Zone 1-2: Very Little to Some Preparation Needed · preparation tier
Zoom out
On the global GenAI exposure gradient this work sits around the 27th percentile of 427 international occupations.
Write a report on thisheadline · factoids · citation
Grinding and Polishing Workers, Hand show 10th-percentile AI task overlap — and about 800 annual U.S. openings
- Grinding and Polishing Workers, Hand rank in the 10th percentile (Low band) for AI task overlap across U.S. occupations — a measure of how much of the work today's AI can attempt, not how much is automated.Eloundou et al. (GPTs are GPTs) + Felten AIOE
- The occupation is projected to see about 800 U.S. job openings per year (2024–34), counting growth and replacement — a labor-demand projection made independently of AI.BLS Employment Projections 2024–34
- BLS projects employment to be declining (-21.2%) from 2024 to 2034.BLS Employment Projections 2024–34
- Median annual pay is $41,690, across about 11,850 U.S. workers.BLS OEWS (May 2024)
Copy the whole kit
Grinding and Polishing Workers, Hand show 10th-percentile AI task overlap — and about 800 annual U.S. openings • Grinding and Polishing Workers, Hand rank in the 10th percentile (Low band) for AI task overlap across U.S. occupations — a measure of how much of the work today's AI can attempt, not how much is automated. (Eloundou et al. (GPTs are GPTs) + Felten AIOE) • The occupation is projected to see about 800 U.S. job openings per year (2024–34), counting growth and replacement — a labor-demand projection made independently of AI. (BLS Employment Projections 2024–34) • BLS projects employment to be declining (-21.2%) from 2024 to 2034. (BLS Employment Projections 2024–34) • Median annual pay is $41,690, across about 11,850 U.S. workers. (BLS OEWS (May 2024)) Source: Singulariki — "Grinding and Polishing Workers, Hand". https://singulariki.com/roles/role-51-9022-00 Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.
AssetsShare imageMethodology & sourcesPress & newsroomThe newsroom
Every line is built only from figures this page already shows and cites. AI task overlap means what today's AI can attempt — not automation, job loss, or a forecast.
Sources for this page
Every figure above traces to a named public dataset and the exact release below — not hand-written opinion. See the full methodology for what each measure does and does not mean.
- O*NET 30.3 U.S. Department of Labor / National Center for O*NET Development
- BLS Occupational Employment and Wage Statistics (OEWS) May 2024 U.S. Bureau of Labor Statistics
- BLS Employment Projections 2024–2034 U.S. Bureau of Labor Statistics
- Microsoft “Working with AI” working-with-ai Microsoft Research
- “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130 OpenAI / academic
- AI Occupational Exposure (AIOE) Felten, Raj & Seamans academic
- ILO / Gmyrek et al. GenAI exposure gradient 2025 International Labour Organization
- IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022 Institute for Structural Research (IBS)
- Frey & Osborne (2013) frey-osborne-automation academic
- Dingel & Neiman (2020) dingel-neiman-workathome academic
Data compiled June 2, 2026. Figures are estimates, not advice.
Cite this page
Plain
Singulariki. "Grinding and Polishing Workers, Hand." Singulariki: a source-backed encyclopedia of work. Built from O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Microsoft “Working with AI” working-with-ai; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans; ILO / Gmyrek et al. GenAI exposure gradient 2025; IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022; Frey & Osborne (2013) frey-osborne-automation; Dingel & Neiman (2020) dingel-neiman-workathome. Accessed June 7, 2026. https://singulariki.com/roles/role-51-9022-00
APA
Singulariki. (2026). Grinding and Polishing Workers, Hand. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-51-9022-00
BibTeX
@misc{singulariki-role-51-9022-00,
title = {Grinding and Polishing Workers, Hand},
author = {{Singulariki}},
year = {2026},
note = {O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Microsoft “Working with AI” working-with-ai; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans; ILO / Gmyrek et al. GenAI exposure gradient 2025; IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022; Frey & Osborne (2013) frey-osborne-automation; Dingel & Neiman (2020) dingel-neiman-workathome. Accessed June 7, 2026},
url = {https://singulariki.com/roles/role-51-9022-00}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.