Skip to content
Singulariki

Nuclear Electric Power Generation

National industry · NAICS 221113

Take this to your AI
Download .md

A source-stamped Markdown brief of this occupation — paste it into an agent, or fetch /industries/221113/context.md directly.

Nuclear Electric Power Generation is a U.S. industry in the NAICS classification. The Bureau of Labor Statistics estimates about 37,140 workers across 97 detailed occupations in it. A typical worker earns around $119,194 a year (Singulariki estimate, see below).

This U.S. industry comprises establishments primarily engaged in operating nuclear electric power generation facilities. These facilities use nuclear power to produce electric energy. The electric energy produced in these establishments is provided to electric power transmission systems or to electric power distribution systems.

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 Moderate band — 63rd 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 93 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 47.5% of employment · 59/96 occupations have AEI task data
Augmentation vs. automation 41.5% working with AI · 34.1% handed to AI
Most common pattern Directive · AI does it; you give the instruction
Typical AI autonomy 3.8 / 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 14.4%
Edit, standardize, or make changes to material prepared by other writers or establishment personnel. Technical Writers Iteration 7.9%
Compose descriptions of merchandise for posting to online storefront, auction sites, or other shopping Web sites. Business Operations Specialists, All Other Directive 3.7%
Use computers for various applications, such as database management or word processing. Secretaries and Administrative Assistants, Except Legal, Medical, and Executive Directive 2.9%
Conduct searches to find needed information, using such sources as the Internet. Secretaries and Administrative Assistants, Except Legal, Medical, and Executive Directive 2.7%
Present investment information, such as product risks, fees, or fund performance statistics. Managers, All Other Learning 2.6%
Compose images of products, using video or still cameras, lighting equipment, props, or photo or video editing software. Business Operations Specialists, All Other Iteration 2.3%
Identify, investigate, or resolve security breaches. Managers, All Other Feedback loop 2.1%
Develop or maintain internal or external company Web sites. Secretaries and Administrative Assistants, Except Legal, Medical, and Executive Directive 2.0%
Enter codes and instructions to program computer-controlled machinery. Industrial Machinery Mechanics Directive 2.0%
Present and explain proposals, reports, or findings to clients. Architectural and Engineering Managers Iteration 1.9%
Analyze organic or inorganic compounds to determine chemical or physical properties, composition, structure, relationships, or reactions, using chromatography, spectroscopy, or spectrophotometry techniques. Chemists Learning 1.9%

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
Nuclear Engineers 3,040 8.2% Iteration
Electrical Engineers 1,690 4.5% Iteration
Business Operations Specialists, All Other 1,160 3.1% Directive
Industrial Machinery Mechanics 1,130 3.0% Directive
First-Line Supervisors of Mechanics, Installers, and Repairers 1,020 2.8% Directive
Training and Development Specialists 880 2.4% Directive
General and Operations Managers 790 2.1% Iteration
Architectural and Engineering Managers 690 1.9% Iteration
Electricians 670 1.8% Feedback loop
Managers, All Other 410 1.1% Directive
Industrial Production Managers 390 1.1% Directive
Office Clerks, General 290 0.8% Feedback loop

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 96.4% of this industry's employment that maps to a detailed occupation with an O*NET skill profile.

Skills

Skill Employment reach Workers
Active Listening 96.2% 35,740
Critical Thinking 95.3% 35,380
Monitoring 94.3% 35,030
Speaking 94.2% 34,990
Judgment and Decision Making 93.0% 34,550
Reading Comprehension 92.4% 34,320
Coordination 89.3% 33,170
Time Management 82.2% 30,530
Complex Problem Solving 80.9% 30,030
Active Learning 75.4% 28,010
Writing 74.5% 27,680
Social Perceptiveness 69.5% 25,830

Knowledge areas

Knowledge area Employment reach Workers
English Language 82.5% 30,630
Computers and Electronics 70.8% 26,290
Mathematics 70.4% 26,160
Public Safety and Security 63.1% 23,420
Mechanical 61.6% 22,870
Administration and Management 57.2% 21,230
Education and Training 54.7% 20,330
Customer and Personal Service 48.9% 18,150
Engineering and Technology 48.5% 18,010
Physics 45.8% 17,000
Design 43.1% 15,990
Chemistry 37.3% 13,870

Abilities

Abilitie Employment reach Workers
Near Vision 96.4% 35,800
Oral Expression 96.2% 35,740
Information Ordering 96.1% 35,700
Oral Comprehension 96.1% 35,680
Problem Sensitivity 95.5% 35,480
Deductive Reasoning 95.4% 35,440
Inductive Reasoning 95.1% 35,320
Written Comprehension 94.4% 35,070
Speech Recognition 90.6% 33,660
Speech Clarity 87.6% 32,530
Selective Attention 86.0% 31,950
Category Flexibility 83.4% 30,990

Tool categories

Tool category Employment reach Workers
Office suite software 98.6% 36,620
Spreadsheet software 98.6% 36,620
Word processing software 86.6% 32,160
Data base user interface and query software 81.5% 30,270
Presentation software 78.6% 29,210
Electronic mail software 77.8% 28,880
Analytical or scientific software 62.9% 23,350
Document management software 61.4% 22,820
Development environment software 60.4% 22,440
Enterprise resource planning ERP software 60.4% 22,440
Operating system software 59.6% 22,120
Industrial control software 57.9% 21,520
Computer aided design CAD software 49.8% 18,490
Object or component oriented development software 43.9% 16,310
Project management software 43.8% 16,280

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

Exposure quadrant: AI task-overlap percentile vs Median pay AI task-overlap (horizontal) versus median pay (vertical), each as a percentile across all scored occupations, for 38 occupations in Nuclear Electric Power Generation. Overlap measures shared tasks with AI, not automation. Lower overlap · higher pay Higher overlap · higher pay Higher overlap · lower pay Lower overlap · lower pay Laborers and Freight, Stock, and Material Movers, Hand Hazardous Materials Removal Workers Electrical Power-Line Installers and Repairers Industrial Machinery Mechanics Power Plant Operators Facilities Managers Security Guards First-Line Supervisors of Security Workers Nuclear Power Reactor Operators Occupational Health and Safety Specialists First-Line Supervisors of Mechanics, Installers, and Repairers First-Line Supervisors of Production and Operating Workers Electrical Engineers General and Operations Managers Architectural and Engineering Managers Office Clerks, General Nuclear Engineers Secretaries and Administrative Assistants, Except Legal, Medical, and Executive Training and Development Specialists AI task-overlap percentile → ↑ Median pay
The largest occupations in this industry with both an AI task-overlap score and a wage, plotted by task-overlap percentile (horizontal) and median-pay percentile (vertical). Overlap measures shared tasks with AI, not automation.

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).

Occupation Workers Share National median pay
Nuclear Power Reactor Operators 4,310 11.6% $122,810
Security Guards 4,100 11.0% $68,100
Nuclear Technicians 3,460 9.3% $105,300
Nuclear Engineers 3,040 8.2% $135,760
First-Line Supervisors of Production and Operating Workers 1,780 4.8% $160,640
Electrical and Electronics Repairers, Powerhouse, Substation, and Relay 1,720 4.6% $105,490
Electrical Engineers 1,690 4.6% $125,580
Business Operations Specialists, All Other 1,160 3.1% $125,490
Industrial Machinery Mechanics 1,130 3.0% $112,430
First-Line Supervisors of Mechanics, Installers, and Repairers 1,020 2.7% $134,720
Training and Development Specialists 880 2.4% $135,320
General and Operations Managers 790 2.1% $161,660
Project Management Specialists 720 1.9% $152,420
Architectural and Engineering Managers 690 1.9% $171,430
Electricians 670 1.8% $108,300
Managers, All Other 410 1.1% $164,550
Industrial Production Managers 390 1.1% $188,710
Electrical Power-Line Installers and Repairers 310 0.8% $105,400
Office Clerks, General 290 0.8% $71,750
Buyers and Purchasing Agents 270 0.7% $108,530
Management Analysts 270 0.7% $127,580
Chemical Technicians 270 0.7% $118,820
Chemists 260 0.7% $122,650
Secretaries and Administrative Assistants, Except Legal, Medical, and Executive 260 0.7% $63,540
First-Line Supervisors of Security Workers 240 0.6% $121,560
Power Plant Operators 240 0.6% $107,190
Facilities Managers 220 0.6% $163,200
Production, Planning, and Expediting Clerks 210 0.6% $110,000
Laborers and Freight, Stock, and Material Movers, Hand 200 0.5% $101,410
Health and Safety Engineers, Except Mining Safety Engineers and Inspectors 190 0.5% $146,250
Engineers, All Other 190 0.5% $141,970
Electrical and Electronic Engineering Technologists and Technicians 170 0.5% $132,760
Technical Writers 170 0.5% $120,260
Executive Secretaries and Executive Administrative Assistants 170 0.5% $76,940
Maintenance and Repair Workers, General 170 0.5% $110,590
Training and Development Managers 160 0.4% $169,610
First-Line Supervisors of Protective Service Workers, All Other 160 0.4% $101,130
Hazardous Materials Removal Workers 160 0.4% $110,210
Computer Systems Analysts 150 0.4% $122,360
Occupational Health and Safety Specialists 150 0.4% $110,780

Showing the top 40 of 97 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).

Occupation Concentration Workers
Nuclear Power Reactor Operators 3128.13× 4,310
Nuclear Technicians 2398.02× 3,460
Nuclear Engineers 856.21× 3,040
Electrical and Electronics Repairers, Powerhouse, Substation, and Relay 309.92× 1,720
Electrical Engineers 37.16× 1,690
Health and Safety Engineers, Except Mining Safety Engineers and Inspectors 33.97× 190
First-Line Supervisors of Protective Service Workers, All Other 32.47× 160
Power Plant Operators 32.43× 240
Chemical Engineers 22.46× 110
Chemical Technicians 20.15× 270
Physicists 19.45× 100
Training and Development Managers 14.77× 160
First-Line Supervisors of Security Workers 14.17× 240
Security Guards 13.71× 4,100
Architectural and Engineering Managers 13.62× 690
Hazardous Materials Removal Workers 13.14× 160
Chemists 12.97× 260
Technical Writers 12.71× 170
Environmental Science and Protection Technicians, Including Health 12.65× 120
Industrial Machinery Mechanics 11.12× 1,130
Write a report on thisheadline · factoids · citation

The Nuclear Electric Power Generation workforce sits at the 63rd percentile of AI task overlap — 37,140 U.S. workers

  • Weighting every occupation by its real share of Nuclear Electric Power Generation employment, the industry's workforce ranks in the 63rd percentile (Moderate 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 37,140 U.S. workers across 97 occupations.BLS OEWS (May 2024)
  • Employment-weighted typical annual pay is about $119,194.BLS OEWS (May 2024)
  • Of AI use observed across this industry's occupations, 41% looks like augmentation rather than automation — from a Claude.ai sample, not a census.Anthropic Economic Index
Copy the whole kit
The Nuclear Electric Power Generation workforce sits at the 63rd percentile of AI task overlap — 37,140 U.S. workers

• Weighting every occupation by its real share of Nuclear Electric Power Generation employment, the industry's workforce ranks in the 63rd percentile (Moderate 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 37,140 U.S. workers across 97 occupations. (BLS OEWS (May 2024))
• Employment-weighted typical annual pay is about $119,194. (BLS OEWS (May 2024))
• Of AI use observed across this industry's occupations, 41% looks like augmentation rather than automation — from a Claude.ai sample, not a census. (Anthropic Economic Index)

Source: Singulariki — "Nuclear Electric Power Generation". https://singulariki.com/industries/221113
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.

Data compiled June 3, 2026. Figures are estimates, not advice.

Cite this page
Plain

Singulariki. "Nuclear Electric Power Generation." 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/221113

APA

Singulariki. (2026). Nuclear Electric Power Generation. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/industries/221113

BibTeX 
@misc{singulariki-221113,
  title  = {Nuclear Electric Power Generation},
  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/221113}
}

Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.