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 →Furniture Finishers
Occupation · SOC 51-7021.00
Shape, finish, and refinish damaged, worn, or used furniture or new high-grade furniture to specified color or finish.
Also called: Finisher · Furniture Finisher · Lacquer Sprayer · Sprayer · Finish Repair Worker · Hand Sander · Sander · Sealer Sander · Stain Sprayer · Stain Wiper · Antique Finisher · Antique Refinisher
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-51-7021-00/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 (-3.3% by 2034)
- 2,000 openings/yr
- Low AI exposure
- Median pay $42,530/yr
- Work is mostly on-site (not teleworkable)
- 2013 flagged this for computerization (74th); today's AI task-overlap is comparatively low (10th)
10th-percentile task overlap — yet about 2,000 openings a year (-3.3% 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 | 11th | -1.2 | |
| LLM task exposure, γ (OpenAI / Eloundou) Low | 8th | 0.1 | |
| AI assistant applicability (Microsoft) Low | 22nd | 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 0.1). 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 0.9 · 74th 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 · -3.3% by 2034 |
| Projected annual openings | 2,000 |
| Employment 2024 → 2034 | 20,500 → 19,800 |
“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 occupation below. Exposure here means how much of the work's tasks today's AI can attempt — task overlap, not automation, adoption, or jobs lost.
Furniture Finishers sits at the 20th percentile of 427
occupations on the global GenAI task-exposure gradient
— exposure rose from 2023 to 2025. Each dot is one occupation; the
ringed one is this work. Exposure is task overlap, not automation or jobs lost.
16% mean task exposure (2025)
20th percentile of 427 placed occupations
+2 pts shift 2023 → 2025
| International occupation (ISCO-08) | Task exposure (2025) | Most tasks fall in |
|---|---|---|
| Cabinet-makers and Related Workers · 7522 | 16% | 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 22 tasks O*NET lists for this occupation, ordered by importance. Each links to its own page with AI-exposure and observed-use detail.
- Confer with customers to determine furniture colors or finishes. Supplemental · importance 4.3
- Brush, spray, or hand-rub finishing ingredients, such as paint, oil, stain, or wax, onto and into wood grain and apply lacquer or other sealers. Core · importance 4.3
- Fill and smooth cracks or depressions, remove marks and imperfections, and repair broken parts, using plastic or wood putty, glue, nails, or screws. Core · importance 4.3
- Smooth, shape, and touch up surfaces to prepare them for finishing, using sandpaper, pumice stones, steel wool, chisels, sanders, or grinders. Core · importance 4.2
- Remove accessories prior to finishing, and mask areas that should not be exposed to finishing processes or substances. Core · importance 4.2
- Remove old finishes and damaged or deteriorated parts, using hand tools, stripping tools, sandpaper, steel wool, abrasives, solvents, or dip baths. Core · importance 4.2
- Recommend woods, colors, finishes, and furniture styles, using knowledge of wood products, fashions, and styles. Supplemental · importance 4.1
- Treat warped or stained surfaces to restore original contours and colors. Core · importance 4.1
- Select appropriate finishing ingredients such as paint, stain, lacquer, shellac, or varnish, depending on factors such as wood hardness and surface type. Core · importance 4.1
- Mix finish ingredients to obtain desired colors or shades. Core · importance 4.0
- Wash surfaces to prepare them for finish application. Supplemental · importance 4.0
- Remove excess solvent, using cloths soaked in paint thinner. Core · importance 4.0
- Follow blueprints to produce specific designs. Supplemental · importance 4.0
- Paint metal surfaces electrostatically, or by using a spray gun or other painting equipment. Supplemental · importance 4.0
- Examine furniture to determine the extent of damage or deterioration, and to decide on the best method for repair or restoration. Core · importance 3.9
- Distress surfaces with woodworking tools or abrasives before staining to create an antique appearance, or rub surfaces to bring out highlights and shadings. Core · importance 3.9
- Stencil, gild, emboss, mark, or paint designs or borders to reproduce the original appearance of restored pieces, or to decorate new pieces. Core · importance 3.9
- Disassemble items to prepare them for finishing, using hand tools. Core · importance 3.9
- Replace or refurbish upholstery of items, using tacks, adhesives, softeners, solvents, stains, or polish. Supplemental · importance 3.8
- Design, create, and decorate entire pieces or specific parts of furniture, such as draws for cabinets. Supplemental · importance 3.8
- Spread graining ink over metal portions of furniture to simulate wood-grain finish. Supplemental · importance 3.8
- Brush bleaching agents on wood surfaces to restore natural color. Supplemental · importance 3.6
Work activities
- Mix ingredients to create specific finishes.
- Apply protective or decorative finishes to workpieces or products.
- Shape surfaces or edges of wood workpieces.
- Operate grinding equipment.
- Select production input materials.
- Fill cracks, imperfections, or holes in products or workpieces.
- Repair furniture or upholstery.
- Examine condition of property or products.
- Operate painting or coating equipment.
- Advise others on ways to improve processes or products.
- Read work orders or other instructions to determine product specifications or materials requirements.
- Disassemble equipment for maintenance or repair.
- Clean workpieces or finished products.
- Remove accessories, tools, or other parts from equipment.
- Confer with customers or designers to determine order specifications.
- Design furniture.
Knowledge, skills & abilities
O*NET importance rating, from 1 (not important) to 5 (extremely important).
Abilities
| Near Vision | 4.0 | |
| Visual Color Discrimination | 3.9 | |
| Arm-Hand Steadiness | 3.8 | |
| Manual Dexterity | 3.6 | |
| Control Precision | 3.5 | |
| Visualization | 3.4 | |
| Selective Attention | 3.3 | |
| Static Strength | 3.3 | |
| Trunk Strength | 3.3 | |
| Oral Comprehension | 3.1 | |
| Oral Expression | 3.1 | |
| Problem Sensitivity | 3.1 | |
| Inductive Reasoning | 3.1 | |
| Category Flexibility | 3.1 | |
| Flexibility of Closure | 3.1 | |
| Finger Dexterity | 3.1 | |
| Multilimb Coordination | 3.1 | |
| Dynamic Strength | 3.1 | |
| Written Comprehension | 3.0 | |
| Deductive Reasoning | 3.0 | |
| Information Ordering | 3.0 | |
| Perceptual Speed | 3.0 | |
| Far Vision | 3.0 | |
| Speech Recognition | 3.0 | |
| Originality | 2.9 | |
| Stamina | 2.9 |
Knowledge
| Production and Processing | 3.3 | |
| Mechanical | 3.0 | |
| Design | 2.9 |
Essential skills
| Active Listening | 3.1 | |
| Critical Thinking | 3.1 | |
| Monitoring | 3.1 | |
| Speaking | 3.0 |
Transferable skills
| Operations Monitoring | 3.0 | |
| Judgment and Decision Making | 3.0 | |
| Time Management | 3.0 | |
| Coordination | 2.9 | |
| Service Orientation | 2.9 | |
| Complex Problem Solving | 2.9 | |
| Quality Control Analysis | 2.9 |
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 | |
|---|---|---|
| Intuit QuickBooks | Accounting software | Hot technology |
| Microsoft Office software | Office suite software | Hot technology |
| DuPont ColorNet | Data base user interface and query software | |
| DuPont Spies Hecker Wizard | Data base user interface and query software | |
| Web browser software | Internet browser software |
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
- High school diploma or equivalent · 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.
What to study: Precision Production . Fields of study crosswalked to this occupation (NCES CIP–SOC), not a requirement.
Education of current workers
Share of people in this occupation at each level of education.
| High School Diploma | 61.2% | |
| Less than a High School Diploma | 35.5% | |
| Post-Secondary Certificate | 3.3% |
Interests & work styles
The interests and personal qualities O*NET associates with people who do this work.
Career interests (Holland / RIASEC)
| Realistic | 7.0 | |
| Artistic | 2.9 | |
| Conventional | 2.9 | |
| Investigative | 1.4 | |
| Social | 1.3 |
Interest areas
| Construction/Woodwork | 6.8 | |
| Physical/Manual Labor | 5.3 | |
| Applied Arts and Design | 3.2 | |
| Visual Arts | 2.9 | |
| Mechanics/Electronics | 1.4 | |
| Engineering | 1.3 | |
| Transportation/Machine Operation | 1.2 |
Work styles
| Attention to Detail | 2.5 | |
| Dependability | 2.0 | |
| Cautiousness | 1.4 | |
| Perseverance | 1.2 |
Wages & employment
U.S. · annual wages (BLS OEWS)
| 10th percentile | $31,200 |
| 25th percentile | $36,770 |
| Median (50th) | $42,530 |
| 75th percentile | $49,020 |
| 90th percentile | $59,820 |
| People employed | 14,230 |
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 | 10,150 | $40,880 |
| Other Services (except Public Administration) · Sector | 1,600 | $44,310 |
| Transportation and Warehousing · Sector | 1,040 | $46,730 |
| Retail Trade · Sector | 880 | $45,260 |
| Construction · Sector | 150 | $46,230 |
| Administrative and Support and Waste Management and Remediation Services · Sector | 150 | $45,870 |
| Wholesale Trade · Sector | 140 | $37,630 |
| Temporary Help Services · National industry | 110 | $45,840 |
| Real Estate and Rental and Leasing · Sector | — | $35,790 |
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 |
|---|---|---|
| Manufacturing · Sector | 8.62× | 10,150 |
| Other Services (except Public Administration) · Sector | 3.92× | 1,600 |
| Transportation and Warehousing · Sector | 1.52× | 1,040 |
| Retail Trade · Sector | 0.61× | 880 |
| Temporary Help Services · National industry | 0.45× | 110 |
| Wholesale Trade · Sector | 0.25× | 140 |
| Construction · Sector | 0.2× | 150 |
| Administrative and Support and Waste Management and Remediation Services · Sector | 0.18× | 150 |
Related occupations
Part of the Advanced Manufacturing and Construction career clusters.
- Upholsterers · 51-6093.00 Compare →
- Painting, Coating, and Decorating Workers · 51-9123.00 Compare →
- Cabinetmakers and Bench Carpenters · 51-7011.00 Compare →
- Grinding and Polishing Workers, Hand · 51-9022.00 Compare →
- Molders, Shapers, and Casters, Except Metal and Plastic · 51-9195.00 Compare →
- Floor Sanders and Finishers · 47-2043.00 Compare →
- Coating, Painting, and Spraying Machine Setters, Operators, and Tenders · 51-9124.00 Compare →
- Floor Layers, Except Carpet, Wood, and Hard Tiles · 47-2042.00 Compare →
- Stone Cutters and Carvers, Manufacturing · 51-9195.03 Compare →
- Woodworking Machine Setters, Operators, and Tenders, Except Sawing · 51-7042.00 Compare →
- Terrazzo Workers and Finishers · 47-2053.00 Compare →
- Tile and Stone Setters · 47-2044.00 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 Furniture Finishers — 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.
Paths in
How people typically prepare for this work.
- High school diploma or equivalent · typical entry level
- Job zone 2 — Job Zone 1-2: Very Little to Some Preparation Needed · preparation tier
- Precision Production · field of study
Zoom out
On the global GenAI exposure gradient this work sits around the 20th percentile of 427 international occupations.
Write a report on thisheadline · factoids · citation
Furniture Finishers show 10th-percentile AI task overlap — and about 2,000 annual U.S. openings
- Furniture Finishers 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 2,000 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 (-3.3%) from 2024 to 2034.BLS Employment Projections 2024–34
- Median annual pay is $42,530, across about 14,230 U.S. workers.BLS OEWS (May 2024)
Copy the whole kit
Furniture Finishers show 10th-percentile AI task overlap — and about 2,000 annual U.S. openings • Furniture Finishers 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 2,000 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 (-3.3%) from 2024 to 2034. (BLS Employment Projections 2024–34) • Median annual pay is $42,530, across about 14,230 U.S. workers. (BLS OEWS (May 2024)) Source: Singulariki — "Furniture Finishers". https://singulariki.com/roles/role-51-7021-00 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. "Furniture Finishers." 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-51-7021-00
APA
Singulariki. (2026). Furniture Finishers. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-51-7021-00
BibTeX
@misc{singulariki-role-51-7021-00,
title = {Furniture Finishers},
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-51-7021-00}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.