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 →Helpers--Roofers
Occupation · SOC 47-3016.00
Help roofers by performing duties requiring less skill. Duties include using, supplying, or holding materials or tools, and cleaning work area and equipment.
Also called: Roofer Helper · Commercial Roofing Helper · Commercial Roofing Laborer · Hot Tar Roofer Helper · Industrial Roofer Helper · Residential Roofer Helper · Roofer Apprentice · Roofer Assistant · Roofing Helper · Rooftop Loader · Shingles Roofer Helper · Slate Roofer Helper
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-47-3016-00/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 (+5.7% by 2034)
- 600 openings/yr
- Low AI exposure
- Median pay $40,590/yr
- Work is mostly on-site (not teleworkable)
- 2013 flagged this for computerization (59th); today's AI task-overlap is comparatively low (0th)
0th-percentile task overlap — yet about 600 openings a year (+5.7% 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 | 1st | -1.9 | |
| LLM task exposure, γ (OpenAI / Eloundou) Low | 3rd | 0.0 | |
| AI assistant applicability (Microsoft) Low | 2nd | 0.0 |
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.
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 0.7 · 59th percentile among occupations · Moderate
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 · +5.7% by 2034 |
| Projected annual openings | 600 |
| Employment 2024 → 2034 | 5,200 → 5,500 |
“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.
Helpers--Roofers sits at the 2nd 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.
9% mean task exposure (2025)
2nd percentile of 427 placed occupations
−1 pts shift 2023 → 2025
| International occupation (ISCO-08) | Task exposure (2025) | Most tasks fall in |
|---|---|---|
| Building Construction Labourers · 9313 | 9% | 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 18 tasks O*NET lists for this occupation, ordered by importance. Each links to its own page with AI-exposure and observed-use detail.
- Check to ensure that completed roofs are watertight. Core · importance 4.4
- Sweep and clean roofs to prepare them for the application of new roofing materials. Core · importance 4.3
- Locate worn or torn areas in roofs. Core · importance 4.2
- Clean work areas and equipment. Core · importance 4.2
- Maintain tools and equipment. Core · importance 4.2
- Cover roofs with layers of roofing felt or asphalt strips before installing tile, slate, or composition materials. Core · importance 4.2
- Remove old roofing materials. Core · importance 4.1
- Unload materials and tools from work trucks, and unroll roofing as directed. Core · importance 4.0
- Set ladders, scaffolds, and hoists in place for taking supplies to roofs. Core · importance 4.0
- Place tiles, nail them to roof boards, and cover nailheads with roofing cement. Core · importance 3.9
- Attach roofing paper and composition shingles, using nails. Core · importance 3.9
- Perform emergency leak repairs and general maintenance for a variety of roof types. Core · importance 3.9
- Provide assistance to skilled roofers installing and repairing roofs, flashings, and surfaces. Core · importance 3.9
- Attach sheets of metal to roof boards or building frameworks when installing metal roofs. Core · importance 3.9
- Hoist tar and roofing materials to roofs, using ropes and pulleys, or carry materials up ladders. Core · importance 3.8
- Apply shingles, gravel, or asphalt over the top layer of tar to protect the roofing material. Core · importance 3.6
- Chop tar into small pieces, and heat chopped tar in kettles. Core · importance 3.6
- Clear drains and downspouts and clean gutters. Core · importance 3.5
Work activities
- Inspect completed work to ensure proper installation.
- Clean surfaces in preparation for work activities.
- Locate equipment or materials in need of repair or replacement.
- Clean work sites.
- Clean equipment or facilities.
- Maintain construction tools or equipment.
- Install roofing materials.
- Remove worn, damaged or outdated materials from work areas.
- Load or unload materials used in construction or extraction.
- Assemble temporary equipment or structures.
- Apply sealants or other protective coatings.
- Assist skilled construction or extraction personnel.
- Move construction or extraction materials to locations where they are needed.
- Spread sand, dirt or other loose materials onto surfaces.
- Mix substances or compounds needed for work activities.
Knowledge, skills & abilities
O*NET importance rating, from 1 (not important) to 5 (extremely important).
Knowledge
Abilities
| Trunk Strength | 3.8 | |
| Manual Dexterity | 3.5 | |
| Gross Body Equilibrium | 3.5 | |
| Multilimb Coordination | 3.4 | |
| Problem Sensitivity | 3.3 | |
| Visualization | 3.3 | |
| Arm-Hand Steadiness | 3.3 | |
| Speech Clarity | 3.3 | |
| Finger Dexterity | 3.1 | |
| Static Strength | 3.1 | |
| Extent Flexibility | 3.1 | |
| Depth Perception | 3.1 | |
| Speech Recognition | 3.1 | |
| Oral Comprehension | 3.0 | |
| Oral Expression | 3.0 | |
| Information Ordering | 3.0 | |
| Flexibility of Closure | 3.0 | |
| Stamina | 3.0 | |
| Gross Body Coordination | 3.0 | |
| Far Vision | 3.0 | |
| Deductive Reasoning | 2.9 | |
| Category Flexibility | 2.9 | |
| Perceptual Speed | 2.9 | |
| Selective Attention | 2.9 | |
| Reaction Time | 2.9 | |
| Speed of Limb Movement | 2.9 |
Transferable skills
| Coordination | 3.3 | |
| Quality Control Analysis | 2.9 |
Essential skills
| Active Listening | 3.0 | |
| Monitoring | 3.0 | |
| Speaking | 2.9 | |
| Critical Thinking | 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
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.
| Less than a High School Diploma | 32.7% | |
| Post-Doctoral Training | 16.0% | |
| Some College Courses | 7.9% |
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 | 3.6 | |
| Social | 2.0 | |
| Enterprising | 1.4 |
Interest areas
| Physical/Manual Labor | 6.5 | |
| Construction/Woodwork | 2.7 | |
| Transportation/Machine Operation | 2.2 | |
| Engineering | 1.5 | |
| Mechanics/Electronics | 1.4 | |
| Nature/Outdoors | 1.1 | |
| Mathematics/Statistics | 1.1 |
Work styles
| Dependability | 2.1 | |
| Attention to Detail | 1.6 | |
| Cautiousness | 1.6 | |
| Cooperation | 1.3 | |
| Stress Tolerance | 1.2 |
Wages & employment
U.S. · annual wages (BLS OEWS)
| 10th percentile | $27,780 |
| 25th percentile | $34,800 |
| Median (50th) | $40,590 |
| 75th percentile | $47,570 |
| 90th percentile | $55,310 |
| People employed | 5,170 |
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 |
|---|---|---|
| Construction · Sector | 5,080 | $40,590 |
| Roofing Contractors · National industry | 4,890 | $40,590 |
| Administrative and Support and Waste Management and Remediation Services · Sector | — | $42,670 |
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 |
|---|---|---|
| Roofing Contractors · National industry | 586.84× | 4,890 |
| Construction · Sector | 18.65× | 5,080 |
Related occupations
Part of the Construction career cluster.
- Roofers · 47-2181.00 Compare →
- Helpers--Painters, Paperhangers, Plasterers, and Stucco Masons · 47-3014.00 Compare →
- Helpers--Pipelayers, Plumbers, Pipefitters, and Steamfitters · 47-3015.00 Compare →
- Helpers--Brickmasons, Blockmasons, Stonemasons, and Tile and Marble Setters · 47-3011.00 Compare →
- Helpers--Carpenters · 47-3012.00 Compare →
- Plasterers and Stucco Masons · 47-2161.00 Compare →
- Insulation Workers, Floor, Ceiling, and Wall · 47-2131.00 Compare →
- Helpers--Electricians · 47-3013.00 Compare →
- Drywall and Ceiling Tile Installers · 47-2081.00 Compare →
- Carpenters · 47-2031.00 Compare →
- Painters, Construction and Maintenance · 47-2141.00 Compare →
- Helpers--Installation, Maintenance, and Repair Workers · 49-9098.00 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 Helpers--Roofers — 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
Zoom out
On the global GenAI exposure gradient this work sits around the 2nd percentile of 427 international occupations.
Write a report on thisheadline · factoids · citation
Helpers--Roofers show 0th-percentile AI task overlap — and about 600 annual U.S. openings
- Helpers--Roofers rank in the 0th 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 600 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 (+5.7%) from 2024 to 2034.BLS Employment Projections 2024–34
- Median annual pay is $40,590, across about 5,170 U.S. workers.BLS OEWS (May 2024)
Copy the whole kit
Helpers--Roofers show 0th-percentile AI task overlap — and about 600 annual U.S. openings • Helpers--Roofers rank in the 0th 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 600 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 (+5.7%) from 2024 to 2034. (BLS Employment Projections 2024–34) • Median annual pay is $40,590, across about 5,170 U.S. workers. (BLS OEWS (May 2024)) Source: Singulariki — "Helpers--Roofers". https://singulariki.com/roles/role-47-3016-00 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. "Helpers--Roofers." 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-47-3016-00
APA
Singulariki. (2026). Helpers--Roofers. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-47-3016-00
BibTeX
@misc{singulariki-role-47-3016-00,
title = {Helpers--Roofers},
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-47-3016-00}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.