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 →Paperhangers
Occupation · SOC 47-2142.00
Cover interior walls or ceilings of rooms with decorative wallpaper or fabric, or attach advertising posters on surfaces such as walls and billboards. May remove old materials or prepare surfaces to be papered.
Also called: Bill Poster · Paper Hanger · Paperhanger · Wallpaper Hanger · Bill Board Poster · Hanger · Vinyl Hanger · Wall Covering Contractor · Wall Covering Installer · Wallpaper Installer · Advertising Installer · Advertising Poster
Job family: Construction and Extraction Occupations
Take this to your AI
A source-stamped Markdown brief of this occupation — paste it into an agent, or fetch
/roles/role-47-2142-00/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.
- About average employment outlook (+5.3% by 2034)
- 200 openings/yr
- Low AI exposure
- Median pay $48,260/yr
- Work is mostly on-site (not teleworkable)
- 2013 flagged this for computerization (74th); today's AI task-overlap is comparatively low (6th)
6th-percentile task overlap — yet about 200 openings a year (+5.3% 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 | 3rd | -1.7 | |
| LLM task exposure, γ (OpenAI / Eloundou) Low | 8th | 0.1 | |
| AI assistant applicability (Microsoft) Low | 19th | 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 | About average · +5.3% by 2034 |
| Projected annual openings | 200 |
| Employment 2024 → 2034 | 2,300 → 2,500 |
“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.
Paperhangers sits at the 9th 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.
13% mean task exposure (2025)
9th percentile of 427 placed occupations
+1 pts shift 2023 → 2025
| International occupation (ISCO-08) | Task exposure (2025) | Most tasks fall in |
|---|---|---|
| Painters and Related Workers · 7131 | 13% | 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.
- Smooth strips or sections of paper with brushes or rollers to remove wrinkles and bubbles and to smooth joints. Core · importance 4.5
- Trim rough edges from strips, using straightedges and trimming knives. Core · importance 4.4
- Trim excess material at ceilings or baseboards, using knives. Core · importance 4.4
- Check finished wallcoverings for proper alignment, pattern matching, and neatness of seams. Core · importance 4.4
- Mark vertical guidelines on walls to align strips, using plumb bobs and chalk lines. Core · importance 4.3
- Cover interior walls and ceilings of rooms with decorative wallpaper or fabric, using hand tools. Core · importance 4.3
- Apply adhesives to the backs of paper strips, using brushes, or dunk strips of prepasted wallcovering in water, wiping off any excess adhesive. Core · importance 4.3
- Measure and cut strips from rolls of wallpaper or fabric, using shears or razors. Core · importance 4.3
- Place strips or sections of paper on surfaces, aligning section edges and patterns. Core · importance 4.2
- Fill holes, cracks, and other surface imperfections preparatory to covering surfaces. Core · importance 4.2
- Measure surfaces or review work orders to estimate the quantities of materials needed. Core · importance 4.2
- Apply sizing to seal surfaces and maximize adhesion of coverings to surfaces. Core · importance 4.2
- Smooth rough spots on walls and ceilings, using sandpaper. Core · importance 4.0
- Set up equipment, such as pasteboards and scaffolds. Core · importance 3.9
- Remove old paper, using water, steam machines, or solvents and scrapers. Core · importance 3.8
- Staple or tack advertising posters onto fences, walls, billboards, or poles. Supplemental · importance 3.8
- Apply thinned glue to waterproof porous surfaces, using brushes, rollers, or pasting machines. Core · importance 3.8
- Mix paste, using paste powder and water, and brush paste onto surfaces. Core · importance 3.6
- Remove paint, varnish, dirt, and grease from surfaces, using paint remover and water soda solutions. Supplemental · importance 3.5
- Apply acetic acid to damp plaster to prevent lime from bleeding through paper. Supplemental · importance 3.4
Work activities
- Apply decorative or textured finishes or coverings.
- Trim excess material from installations.
- Inspect completed work to ensure proper installation.
- Mark reference points on construction materials.
- Apply adhesives to construction materials.
- Measure materials or objects for installation or assembly.
- Cut carpet, vinyl or other flexible materials.
- Apply material to fill gaps in surfaces.
- Review blueprints or specifications to determine work requirements.
- Measure work site dimensions.
- Estimate materials requirements for projects.
- Prepare surfaces for finishing.
- Smooth surfaces with abrasive materials or tools.
- Assemble temporary equipment or structures.
- Remove worn, damaged or outdated materials from work areas.
- Apply sealants or other protective coatings.
- Mix substances or compounds needed for work activities.
- Implement advertising or marketing initiatives.
- Clean surfaces in preparation for work activities.
Knowledge, skills & abilities
O*NET importance rating, from 1 (not important) to 5 (extremely important).
Knowledge
| Customer and Personal Service | 3.7 | |
| Building and Construction | 3.5 | |
| Mathematics | 3.3 | |
| Mechanical | 3.0 | |
| Administration and Management | 3.0 | |
| Public Safety and Security | 3.0 | |
| English Language | 3.0 | |
| Design | 2.9 | |
| Education and Training | 2.8 | |
| Sales and Marketing | 2.8 |
Abilities
| Manual Dexterity | 3.6 | |
| Near Vision | 3.6 | |
| Arm-Hand Steadiness | 3.5 | |
| Multilimb Coordination | 3.4 | |
| Extent Flexibility | 3.4 | |
| Finger Dexterity | 3.3 | |
| Trunk Strength | 3.3 | |
| Gross Body Equilibrium | 3.3 | |
| Information Ordering | 3.1 | |
| Control Precision | 3.1 | |
| Oral Comprehension | 3.0 | |
| Oral Expression | 2.9 | |
| Problem Sensitivity | 2.9 | |
| Deductive Reasoning | 2.9 | |
| Inductive Reasoning | 2.9 | |
| Visualization | 2.9 | |
| Gross Body Coordination | 2.9 | |
| Far Vision | 2.9 | |
| Speech Clarity | 2.9 | |
| Selective Attention | 2.8 | |
| Stamina | 2.8 | |
| Visual Color Discrimination | 2.8 |
Essential skills
| Active Listening | 3.0 | |
| Speaking | 3.0 | |
| Critical Thinking | 2.9 | |
| Monitoring | 2.8 |
Transferable skills
| Coordination | 3.0 | |
| Time Management | 2.9 | |
| Complex Problem Solving | 2.8 | |
| Judgment and Decision Making | 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
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.
What to study: Construction Trades . 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 | 54.1% | |
| Less than a High School Diploma | 24.1% | |
| Post-Secondary Certificate | 3.4% |
Interests & work styles
The interests and personal qualities O*NET associates with people who do this work.
Career interests (Holland / RIASEC)
| Realistic | 5.9 | |
| Conventional | 3.9 | |
| Artistic | 3.0 | |
| Social | 1.6 |
Interest areas
| Physical/Manual Labor | 5.4 | |
| Applied Arts and Design | 3.0 | |
| Construction/Woodwork | 2.6 | |
| Visual Arts | 2.3 | |
| Engineering | 1.5 | |
| Marketing/Advertising | 1.4 | |
| Mechanics/Electronics | 1.3 | |
| Personal Service | 1.2 | |
| Mathematics/Statistics | 1.2 | |
| Accounting | 1.2 |
Work styles
| Attention to Detail | 2.3 | |
| Dependability | 2.1 |
Wages & employment
U.S. · annual wages (BLS OEWS)
| 10th percentile | $35,020 |
| 25th percentile | $40,930 |
| Median (50th) | $48,260 |
| 75th percentile | $58,470 |
| 90th percentile | $69,470 |
| People employed | 1,520 |
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 |
|---|---|---|
| Professional, Scientific, and Technical Services · Sector | 900 | $46,910 |
| Construction · Sector | 470 | $51,510 |
| Painting and Wall Covering Contractors · National industry | 350 | $57,330 |
| Manufacturing · Sector | 90 | $57,740 |
| Administrative and Support and Waste Management and Remediation Services · Sector | 30 | — |
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 |
|---|---|---|
| Painting and Wall Covering Contractors · National industry | 171.75× | 350 |
| Professional, Scientific, and Technical Services · Sector | 8.48× | 900 |
| Construction · Sector | 5.87× | 470 |
Related occupations
Part of the Construction career cluster.
- Floor Layers, Except Carpet, Wood, and Hard Tiles · 47-2042.00 Compare →
- Carpet Installers · 47-2041.00 Compare →
- Drywall and Ceiling Tile Installers · 47-2081.00 Compare →
- Painters, Construction and Maintenance · 47-2141.00 Compare →
- Painting, Coating, and Decorating Workers · 51-9123.00 Compare →
- Tile and Stone Setters · 47-2044.00 Compare →
- Insulation Workers, Floor, Ceiling, and Wall · 47-2131.00 Compare →
- Helpers--Painters, Paperhangers, Plasterers, and Stucco Masons · 47-3014.00 Compare →
- Furniture Finishers · 51-7021.00 Compare →
- Sheet Metal Workers · 47-2211.00 Compare →
- Carpenters · 47-2031.00 Compare →
- Plasterers and Stucco Masons · 47-2161.00 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 Paperhangers — 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.
- No formal educational credential · typical entry level
- Job zone 2 — Job Zone 1-2: Very Little to Some Preparation Needed · preparation tier
- Construction Trades · field of study
Zoom out
On the global GenAI exposure gradient this work sits around the 9th percentile of 427 international occupations.
Write a report on thisheadline · factoids · citation
Paperhangers show 6th-percentile AI task overlap — and about 200 annual U.S. openings
- Paperhangers rank in the 6th 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 200 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 about average (+5.3%) from 2024 to 2034.BLS Employment Projections 2024–34
- Median annual pay is $48,260, across about 1,520 U.S. workers.BLS OEWS (May 2024)
Copy the whole kit
Paperhangers show 6th-percentile AI task overlap — and about 200 annual U.S. openings • Paperhangers rank in the 6th 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 200 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 about average (+5.3%) from 2024 to 2034. (BLS Employment Projections 2024–34) • Median annual pay is $48,260, across about 1,520 U.S. workers. (BLS OEWS (May 2024)) Source: Singulariki — "Paperhangers". https://singulariki.com/roles/role-47-2142-00 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. "Paperhangers." 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-47-2142-00
APA
Singulariki. (2026). Paperhangers. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-47-2142-00
BibTeX
@misc{singulariki-role-47-2142-00,
title = {Paperhangers},
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-47-2142-00}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.