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 →Occupation · SOC 47-2022.00
Build stone structures, such as piers, walls, and abutments. Lay walks, curbstones, or special types of masonry for vats, tanks, and floors.
Also called: Mason · Stone Derrickman · Stone Setter · Stonemason · Marble Installer · Marble Shop Worker · Mason Mechanic · Stone Installer · Stone Mason · Artificial Stone Applicator · Banker Mason · Composition Stone Applicator
Job family: Construction and Extraction Occupations
A source-stamped Markdown brief of this occupation — paste it into an agent, or fetch
/roles/role-47-2022-00/context.md directly.
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.
The capabilities O*NET rates most important for this occupation — the human ground the work is built on.
See all skills →Independent published positions, read together — not a forecast.
1st-percentile task overlap — yet about 800 openings a year (-3% projected, BLS) . What exposure means →
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.
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 | 3rd | 0.0 | |
| AI assistant applicability (Microsoft) Low | 5th | 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.
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.
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 · 76th percentile among occupations · High
Independent U.S. Bureau of Labor Statistics employment projection for 2024–2034 — a labor-market forecast, not an AI-impact forecast.
| Outlook | Declining · -3.0% by 2034 |
| Projected annual openings | 800 |
| Employment 2024 → 2034 | 12,100 → 11,800 |
“Annual openings” counts new jobs plus replacements for workers who leave the occupation, so it can be large even when growth is modest.
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.
| International occupation (ISCO-08) | Task exposure (2025) | Most tasks fall in |
|---|---|---|
| Stonemasons, Stone Cutters, Splitters and Carvers · 7113 | 11% | 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.
All 17 tasks O*NET lists for this occupation, ordered by importance. Each links to its own page with AI-exposure and observed-use detail.
O*NET importance rating, from 1 (not important) to 5 (extremely important).
| Building and Construction | 4.7 | |
| Design | 3.7 | |
| Mathematics | 3.7 | |
| Mechanical | 3.1 | |
| Customer and Personal Service | 3.0 | |
| Administration and Management | 3.0 | |
| English Language | 3.0 |
| Static Strength | 4.0 | |
| Arm-Hand Steadiness | 3.9 | |
| Trunk Strength | 3.9 | |
| Near Vision | 3.9 | |
| Manual Dexterity | 3.8 | |
| Problem Sensitivity | 3.6 | |
| Visualization | 3.6 | |
| Stamina | 3.6 | |
| Information Ordering | 3.4 | |
| Multilimb Coordination | 3.4 | |
| Extent Flexibility | 3.4 | |
| Far Vision | 3.4 | |
| Oral Comprehension | 3.3 | |
| Selective Attention | 3.3 | |
| Finger Dexterity | 3.3 | |
| Dynamic Strength | 3.3 | |
| Deductive Reasoning | 3.1 | |
| Category Flexibility | 3.1 | |
| Gross Body Equilibrium | 3.1 | |
| Oral Expression | 3.0 | |
| Control Precision | 3.0 | |
| Speech Recognition | 3.0 |
| Critical Thinking | 3.5 | |
| Reading Comprehension | 3.0 | |
| Active Listening | 3.0 | |
| Speaking | 3.0 | |
| Mathematics | 3.0 | |
| Monitoring | 3.0 |
| Complex Problem Solving | 3.3 | |
| Judgment and Decision Making | 3.3 | |
| Time Management | 3.3 | |
| Coordination | 3.1 | |
| Operations Monitoring | 3.1 |
Skills employers ask for in job postings for this occupation (Lightcast), with whether each is a common or specialized skill.
| Example | Category | |
|---|---|---|
| Intuit QuickBooks | Accounting software | Hot technology |
| Microsoft Active Server Pages ASP | Web platform development software | Hot technology |
| Microsoft Excel | Spreadsheet software | Hot technology |
| Microsoft Office software | Office suite software | Hot technology |
| Microsoft Word | Word processing software | Hot technology |
| SAP software | Enterprise resource planning ERP software | Hot technology |
| Citrix cloud computing software | Access software | |
| CPR Visual Estimator | Project management software | |
| Gregg Software Gregg Rock-It | Analytical or scientific software | |
| ProEst Software ProEst Estimating | Analytical or scientific software | |
| RISA Technologies RISA-3D | Computer aided design CAD software | |
| Tradesman's Software Master Estimator | Analytical or scientific software | |
| Virtual private networking VPN software | Network security or virtual private network VPN management software |
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.
What to study: Construction Trades . Fields of study crosswalked to this occupation (NCES CIP–SOC), not a requirement.
The interests and personal qualities O*NET associates with people who do this work.
| Realistic | 7.0 | |
| Conventional | 3.0 | |
| Artistic | 2.9 | |
| Investigative | 2.1 | |
| Social | 1.9 |
| Physical/Manual Labor | 6.6 | |
| Construction/Woodwork | 3.1 | |
| Transportation/Machine Operation | 2.1 | |
| Engineering | 2.1 | |
| Applied Arts and Design | 1.8 | |
| Visual Arts | 1.7 | |
| Mechanics/Electronics | 1.6 |
| Dependability | 2.3 | |
| Attention to Detail | 2.2 | |
| Perseverance | 1.6 | |
| Cautiousness | 1.6 |
U.S. · annual wages (BLS OEWS)
| 10th percentile | $37,420 |
| 25th percentile | $44,820 |
| Median (50th) | $51,990 |
| 75th percentile | $64,120 |
| 90th percentile | $83,200 |
| People employed | 8,750 |
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 | 6,930 | $52,400 |
| Masonry Contractors · National industry | 4,200 | $56,980 |
| Manufacturing · Sector | 820 | $46,170 |
| Administrative and Support and Waste Management and Remediation Services · Sector | 690 | $48,060 |
| Landscaping Services · National industry | 610 | $49,510 |
| Retail Trade · Sector | 170 | $42,930 |
| Temporary Help Services · National industry | 80 | $39,520 |
| Poured Concrete Foundation and Structure Contractors · National industry | — | $64,110 |
| Drywall and Insulation Contractors · National industry | — | $36,610 |
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 |
|---|---|---|
| Masonry Contractors · National industry | 515.39× | 4,200 |
| Construction · Sector | 15.04× | 6,930 |
| Landscaping Services · National industry | 11.75× | 610 |
| Administrative and Support and Waste Management and Remediation Services · Sector | 1.35× | 690 |
| Manufacturing · Sector | 1.13× | 820 |
| Retail Trade · Sector | 0.19× | 170 |
Part of the Construction career cluster.
Side-by-side comparisons place two occupations’ pay, preparation, skills, and AI exposure on the same page — same data, same scale, no forecast.
Options the data surfaces for Stonemasons — not advice or a forecast. Each is a real cross-link you can follow into the evidence.
Capabilities this work builds that are used across many other occupations.
Occupations O*NET rates as related — the nearby moves on the map.
How people typically prepare for this work.
On the global GenAI exposure gradient this work sits around the 4th percentile of 427 international occupations.
Stonemasons show 1st-percentile AI task overlap — and about 800 annual U.S. openings
Stonemasons show 1st-percentile AI task overlap — and about 800 annual U.S. openings • Stonemasons rank in the 1st 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 (-3%) from 2024 to 2034. (BLS Employment Projections 2024–34) • Median annual pay is $51,990, across about 8,750 U.S. workers. (BLS OEWS (May 2024)) Source: Singulariki — "Stonemasons". https://singulariki.com/roles/role-47-2022-00 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.
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.
Data compiled June 2, 2026. Figures are estimates, not advice.
Singulariki. "Stonemasons." 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-47-2022-00
Singulariki. (2026). Stonemasons. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-47-2022-00
@misc{singulariki-role-47-2022-00,
title = {Stonemasons},
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-47-2022-00}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.