Masonry Contractors
National industry · NAICS 238140
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Masonry Contractors is a U.S. industry in the NAICS classification. The Bureau of Labor Statistics estimates about 143,600 workers across 77 detailed occupations in it. A typical worker earns around $58,947 a year (Singulariki estimate, see below).
This industry comprises establishments primarily engaged in masonry work, stone setting, bricklaying, and other stone work. The work performed may include new work, additions, alterations, maintenance, and repairs. Illustrative Examples: Block laying Marble, granite, and slate, exterior, contractors Bricklaying Masonry pointing, cleaning, or caulking Concrete block laying Stucco contractors Foundation (e.g., brick, block, stone), building, contractors Cross-References. Establishments primarily engaged in--
Employment is national May 2024 OEWS. "Typical pay" is Singulariki's own figure — the employment-weighted average of each occupation's national median wage — a rough center of the industry, not an official BLS number.
How exposed this industry is to AI
Weighting every occupation in this industry by its employment and its unified AI-exposure index (the OpenAI "GPTs are GPTs" human-rated task overlap folded with the Felten/Raj/Seamans AIOE index), this industry sits in the Low band — 5th percentile across all industries.
Exposure measures how much of the work overlaps with what today's AI can do, not a prediction of automation; high-exposure industries are where AI is most likely to reshape tasks. Employment-weighted across 66 occupations that carry an exposure score. Compare every industry on the AI exposure hub.
How AI is actually used in this industry
Among measured Claude.ai (Free and Pro) conversations mapped to O*NET task statements (Anthropic Economic Index, 2026-01-15), these patterns are most associated with the occupations in this industry, weighted by its employment mix. They are shares of observed AI conversations — not of worker time, revenue, or what could be automated — and reflect one AI assistant's consumer sample, not all AI.
| Signal coverage | 32.8% of employment · 38/71 occupations have AEI task data |
| Augmentation vs. automation | 42.9% working with AI · 36.8% handed to AI |
| Most common pattern | Directive · AI does it; you give the instruction |
| Typical AI autonomy | 3.4 / 5 · higher = AI acts more independently |
Tasks driving the signal
The task families that account for the most AI activity across this industry's occupations (employment × observed usage), each attributed to the occupation it comes from.
| Task | Occupation | How | Share of signal |
|---|---|---|---|
| Troubleshoot problems involving office equipment, such as computer hardware and software. | Office Clerks, General | Feedback loop | 61.4% |
| Use computers for various applications, such as database management or word processing. | Secretaries and Administrative Assistants, Except Legal, Medical, and Executive | Directive | 5.2% |
| Conduct searches to find needed information, using such sources as the Internet. | Secretaries and Administrative Assistants, Except Legal, Medical, and Executive | Directive | 4.8% |
| Develop or maintain internal or external company Web sites. | Secretaries and Administrative Assistants, Except Legal, Medical, and Executive | Directive | 3.6% |
| Process and prepare documents, such as business or government forms and expense reports. | Office Clerks, General | Directive | 2.5% |
| Participate in the work of subordinates to facilitate productivity or to overcome difficult aspects of work. | First-Line Supervisors of Office and Administrative Support Workers | Iteration | 1.6% |
| Complete work schedules, manage calendars, and arrange appointments. | Office Clerks, General | Directive | 1.5% |
| Monitor how the wind, heat, or cold affect the curing of the concrete throughout the entire process. | Cement Masons and Concrete Finishers | Learning | 1.4% |
| Operate office machines, such as photocopiers and scanners, facsimile machines, voice mail systems, and personal computers. | Office Clerks, General | Learning | 1.1% |
| Classify, record, and summarize numerical and financial data to compile and keep financial records, using journals and ledgers or computers. | Bookkeeping, Accounting, and Auditing Clerks | Directive | 0.9% |
| Review financial statements, sales or activity reports, or other performance data to measure productivity or goal achievement or to identify areas needing cost reduction or program improvement. | General and Operations Managers | Directive | 0.8% |
| Create, maintain, and enter information into databases. | Secretaries and Administrative Assistants, Except Legal, Medical, and Executive | Directive | 0.8% |
Occupations behind the signal
The occupations whose AI-touched tasks contribute most to this industry's signal, by employment here.
| Occupation | Workers | Share | How they use AI |
|---|---|---|---|
| Cement Masons and Concrete Finishers | 12,240 | 8.5% | Learning |
| First-Line Supervisors of Construction Trades and Extraction Workers | 11,380 | 7.9% | Directive |
| Office Clerks, General | 4,240 | 2.9% | Feedback loop |
| General and Operations Managers | 3,610 | 2.5% | Iteration |
| Construction Managers | 2,860 | 2.0% | Iteration |
| Cost Estimators | 1,850 | 1.3% | Iteration |
| Bookkeeping, Accounting, and Auditing Clerks | 1,660 | 1.2% | Directive |
| Drywall and Ceiling Tile Installers | 1,650 | 1.1% | Directive |
| Secretaries and Administrative Assistants, Except Legal, Medical, and Executive | 1,580 | 1.1% | Directive |
| Heavy and Tractor-Trailer Truck Drivers | 1,410 | 1.0% | Directive |
| First-Line Supervisors of Office and Administrative Support Workers | 670 | 0.5% | Iteration |
| Landscaping and Groundskeeping Workers | 570 | 0.4% | Learning |
This rollup is only as complete as the occupation-task matches available for the industry; the coverage figure above is shown so sparse industries do not look falsely precise. AI exposure is not the same as replacement.
Skill & tool metabolism
What this industry's work actually runs on. Each figure is the share of the industry's workers in occupations that significantly rely on a skill, knowledge area, or ability (O*NET importance ≥ 3 of 5), or that use a tool category — its employment reach. This is a measure of how widespread a requirement is across the workforce, not how intensively any one worker uses it. Shares are independent and need not add to 100%.
Based on 97.8% of this industry's employment that maps to a detailed occupation with an O*NET skill profile.
Skills
| Skill | Employment reach | Workers |
|---|---|---|
| Coordination | 87.7% | 125,940 |
| Active Listening | 86.5% | 124,260 |
| Speaking | 82.5% | 118,500 |
| Time Management | 78.1% | 112,140 |
| Critical Thinking | 74.7% | 107,240 |
| Monitoring | 70.4% | 101,130 |
| Quality Control Analysis | 53.0% | 76,050 |
| Operations Monitoring | 51.2% | 73,570 |
| Judgment and Decision Making | 31.0% | 44,570 |
| Complex Problem Solving | 30.8% | 44,210 |
| Operation and Control | 28.2% | 40,520 |
| Reading Comprehension | 28.1% | 40,360 |
Knowledge areas
| Knowledge area | Employment reach | Workers |
|---|---|---|
| Building and Construction | 83.7% | 120,160 |
| Mechanical | 70.7% | 101,470 |
| Public Safety and Security | 69.6% | 99,880 |
| Mathematics | 68.8% | 98,860 |
| English Language | 67.9% | 97,560 |
| Administration and Management | 58.6% | 84,160 |
| Design | 56.8% | 81,580 |
| Production and Processing | 33.8% | 48,520 |
| Customer and Personal Service | 33.1% | 47,580 |
| Administrative | 11.7% | 16,730 |
| Economics and Accounting | 8.2% | 11,770 |
| Computers and Electronics | 8.1% | 11,690 |
Abilities
| Abilitie | Employment reach | Workers |
|---|---|---|
| Near Vision | 97.7% | 140,360 |
| Oral Comprehension | 97.4% | 139,920 |
| Information Ordering | 96.5% | 138,590 |
| Deductive Reasoning | 92.8% | 133,300 |
| Oral Expression | 89.6% | 128,610 |
| Problem Sensitivity | 89.2% | 128,140 |
| Manual Dexterity | 84.5% | 121,410 |
| Arm-Hand Steadiness | 84.4% | 121,220 |
| Control Precision | 83.9% | 120,460 |
| Category Flexibility | 82.0% | 117,790 |
| Far Vision | 81.8% | 117,510 |
| Selective Attention | 81.3% | 116,780 |
Tool categories
| Tool category | Employment reach | Workers |
|---|---|---|
| Project management software | 94.8% | 136,090 |
| Office suite software | 90.8% | 130,350 |
| Spreadsheet software | 89.8% | 128,890 |
| Computer aided design CAD software | 78.9% | 113,350 |
| Operating system software | 74.4% | 106,830 |
| Accounting software | 68.6% | 98,480 |
| Analytical or scientific software | 66.8% | 95,970 |
| Word processing software | 61.5% | 88,250 |
| Electronic mail software | 44.8% | 64,390 |
| Data base user interface and query software | 38.2% | 54,870 |
| Presentation software | 31.8% | 45,710 |
| Enterprise resource planning ERP software | 31.7% | 45,530 |
| Document management software | 30.0% | 43,030 |
| Process mapping and design software | 25.3% | 36,300 |
| Customer relationship management CRM software | 25.0% | 35,840 |
Reach = share of industry employment in occupations where the requirement is significant; it is not a per-worker usage or proficiency measure. Skill, knowledge, and ability importance is from O*NET; tool use is reported presence of a technology category.
Largest occupations
The occupations that employ the most people in this industry, with their share of the industry's workforce and national median pay for the occupation (not industry-specific pay).
Showing the top 40 of 77 occupations by employment.
Most distinctive occupations
The occupations most unusually concentrated in this industry compared with the economy as a whole. The location quotient is how many times more common an occupation is here versus its economy-wide share (a value of 5 means five times as concentrated).
Write a report on thisheadline · factoids · citation
The Masonry Contractors workforce sits at the 5th percentile of AI task overlap — 143,600 U.S. workers
- Weighting every occupation by its real share of Masonry Contractors employment, the industry's workforce ranks in the 5th percentile (Low band) for AI task overlap — overlap with what AI can attempt, not a measure of jobs at risk.Eloundou et al. + Felten AIOE, weighted by BLS OEWS
- The industry employs about 143,600 U.S. workers across 77 occupations.BLS OEWS (May 2024)
- Employment-weighted typical annual pay is about $58,947.BLS OEWS (May 2024)
- Of AI use observed across this industry's occupations, 43% looks like augmentation rather than automation — from a Claude.ai sample, not a census.Anthropic Economic Index
The Masonry Contractors workforce sits at the 5th percentile of AI task overlap — 143,600 U.S. workers • Weighting every occupation by its real share of Masonry Contractors employment, the industry's workforce ranks in the 5th percentile (Low band) for AI task overlap — overlap with what AI can attempt, not a measure of jobs at risk. (Eloundou et al. + Felten AIOE, weighted by BLS OEWS) • The industry employs about 143,600 U.S. workers across 77 occupations. (BLS OEWS (May 2024)) • Employment-weighted typical annual pay is about $58,947. (BLS OEWS (May 2024)) • Of AI use observed across this industry's occupations, 43% looks like augmentation rather than automation — from a Claude.ai sample, not a census. (Anthropic Economic Index) Source: Singulariki — "Masonry Contractors". https://singulariki.com/industries/238140 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
- Census NAICS 2022 U.S. Census Bureau
- Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27) Anthropic
- “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130 OpenAI / academic
- AI Occupational Exposure (AIOE) Felten, Raj & Seamans academic
Data compiled June 3, 2026. Figures are estimates, not advice.
Cite this page
Singulariki. "Masonry Contractors." Singulariki: a source-backed encyclopedia of work. Built from O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; Census NAICS 2022; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans. Accessed June 7, 2026. https://singulariki.com/industries/238140
Singulariki. (2026). Masonry Contractors. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/industries/238140
@misc{singulariki-238140,
title = {Masonry Contractors},
author = {{Singulariki}},
year = {2026},
note = {O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; Census NAICS 2022; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans. Accessed June 7, 2026},
url = {https://singulariki.com/industries/238140}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.