As of August 2026,
Roofers has an AI-exposure score of 39/100
(Low exposure) on the AI-Safe Careers index. This is an estimate of task
exposure, not a prediction of job loss.
Score inputs for this role:
This role starts from O*NET 29.1 occupational descriptors and is empirically grounded by Penn/OpenAI GPTs are GPTs study, Anthropic Economic Index (June 26, 2026), Felten, Raj and Seamans AIOE index. BLS labor-market figures are separate context, not score inputs.
Roofers
More exposed than 7% of the roles we track. Median pay ~US$55,440. About 12,700 projected openings a year (BLS 2024–34 - growth plus replacement).
Pay & demand figures are US medians (BLS, in USD) - your local figures will differ. Your exposure score applies broadly.
Will AI replace Roofers?
No exposure score can predict whether AI will replace this role. The 39/100 score means our current model estimates low task exposure from the sources listed on this page. It does not predict an employer decision, headcount, or an individual outcome. The task map below shows the work assessed and where human judgment remains important.
Early-career context (study ages 22-25)
This role is in our Low exposure band, not our highest-exposure bands. The study's 16% finding should not be applied directly to this role.
The November 2025 revision reports a 16% relative employment decline for workers ages 22-25 in the most AI-exposed U.S. occupations, after firm-level controls, relative to workers in less-exposed fields and more experienced workers in the same occupations.
Use the task map to identify durable work and the skills worth building early.
Stanford Digital Economy Lab, Canaries in the Coal Mine - November 2025 revision
This is group-level U.S. payroll evidence, not a personal forecast. The authors do not claim that AI alone caused the change, and this context does not alter the exposure score.
How this role compares to similar Construction roles
What this role usually involves
Cover roofs of structures with shingles, slate, asphalt, aluminum, wood, or related materials. May spray roofs, sidings, and walls with material to bind, seal, insulate, or soundproof sections of structures.
Broad guidance for this preparation level; exact requirements vary by role and employer.
Source: O*NET 29.1 exact occupation - Roofers, SOC 47-2181.00. Context describes the role; the AI-exposure score remains a separate task-exposure estimate.
Roofers tasks, by AI exposure
No automatable tasks identified for this role - its individually-assessed tasks split 85% augmentable / 15% durable.
- Install partially overlapping layers of material over roof insulation surfaces, using chalk lines, gauges on shingling hatchets, or lines on shingles.
- Apply plastic coatings, membranes, fiberglass, or felt over sloped roofs before applying shingles.
- Estimate materials and labor required to complete roofing jobs.
- Cut felt, shingles, or strips of flashing to fit angles formed by walls, vents, or intersecting roof surfaces.
We analyzed all 20 Roofers tasks - 17 augmentable and 3 durable. The full task map - every task with exactly what to do about each - is in your Career Report.
Your report unlocks three concrete artifacts
Every task scored with what to automate, augment, or protect.
Related roles with exposure deltas, salary, demand, and reachability. Lower-exposure options appear only when the data supports them.
A keepable roadmap plus resume and LinkedIn repositioning.
Grounded in O*NET-linked or curated role data, with Penn, Anthropic Economic Index, and AIOE signals where matched. BLS labor-market context is separate - not generic advice.
Adjacent career paths
Relatedness shows how reachable a move may be. A path is labeled lower exposure only when its score is at least 6 points lower; every row shows the measured difference.
Install partially overlapping layers of material over roof insulation surfaces, using chalk lines, gauges on shingling hatchets, or lines on shingles.
Your AI-Safe Career Report
Every task scored with what to do about it; adjacent paths with honest exposure deltas, salary, demand, and reachability; a skill-gap map; a 30/60/90-day roadmap; Agent Reality Check; plus a résumé and LinkedIn rewrite and professional PDF.
Grounded in O*NET-linked or curated role data, with Penn, Anthropic Economic Index, and AIOE signals where matched. BLS labor-market context is separate.
Workers with AI skills earn a roughly 62% wage premium - adapting pays. - PwC Global AI Jobs Barometer, 2026
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Roofers - median pay by US state (BLS OEWS, USD)
Median annual wage, in USD. US national: US$55,440. More states are being added.