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Insurance Agencies and Brokerages

National industry · NAICS 524210

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Insurance Agencies and Brokerages is a U.S. industry in the NAICS classification. The Bureau of Labor Statistics estimates about 990,240 workers across 145 detailed occupations in it. A typical worker earns around $70,355 a year (Singulariki estimate, see below).

This industry comprises establishments primarily engaged in acting as agents (i.e., brokers) in selling annuities and insurance policies. 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 High band — 99th 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 119 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 94.7% of employment · 92/127 occupations have AEI task data
Augmentation vs. automation 49.3% working with AI · 33.1% handed to AI
Most common pattern Directive · AI does it; you give the instruction
Typical AI autonomy 3.2 / 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 28.9%
Use computers for various applications, such as database management or word processing. Secretaries and Administrative Assistants, Except Legal, Medical, and Executive Directive 4.0%
Conduct searches to find needed information, using such sources as the Internet. Secretaries and Administrative Assistants, Except Legal, Medical, and Executive Directive 3.6%
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 3.0%
Keep records of customer interactions or transactions, recording details of inquiries, complaints, or comments, as well as actions taken. Customer Service Representatives Directive 2.9%
Develop or maintain internal or external company Web sites. Secretaries and Administrative Assistants, Except Legal, Medical, and Executive Directive 2.7%
Interview prospective clients to obtain data about their financial resources and needs, the physical condition of the person or property to be insured, and to discuss any existing coverage. Insurance Sales Agents Directive 2.6%
Confer with customers by telephone or in person to provide information about products or services, take or enter orders, cancel accounts, or obtain details of complaints. Customer Service Representatives Directive 2.5%
Compose business correspondence for supervisors, managers, and professionals. Insurance Claims and Policy Processing Clerks Iteration 2.5%
Customize insurance programs to suit individual customers, often covering a variety of risks. Insurance Sales Agents Iteration 2.4%
Explain necessary bookkeeping requirements for customer to implement and provide group insurance program. Insurance Sales Agents Learning 2.2%
Confer with clients to obtain and provide information when claims are made on a policy. Insurance Sales Agents Learning 2.1%

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
Insurance Sales Agents 353,250 35.7% Learning
Customer Service Representatives 125,640 12.7% Directive
Insurance Claims and Policy Processing Clerks 66,730 6.7% Iteration
General and Operations Managers 41,860 4.2% Iteration
Claims Adjusters, Examiners, and Investigators 40,880 4.1% Learning
Office Clerks, General 32,770 3.3% Feedback loop
Insurance Underwriters 31,670 3.2% none
First-Line Supervisors of Office and Administrative Support Workers 21,440 2.2% Iteration
Secretaries and Administrative Assistants, Except Legal, Medical, and Executive 19,920 2.0% Directive
Market Research Analysts and Marketing Specialists 16,220 1.6% Directive
Financial Managers 14,900 1.5% Directive
Bookkeeping, Accounting, and Auditing Clerks 13,730 1.4% Directive

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 98.4% of this industry's employment that maps to a detailed occupation with an O*NET skill profile.

Skills

Skill Employment reach Workers
Active Listening 98.3% 973,770
Reading Comprehension 98.2% 972,630
Speaking 98.2% 971,960
Critical Thinking 98.0% 970,490
Writing 98.0% 970,250
Social Perceptiveness 94.3% 934,060
Time Management 93.7% 927,910
Service Orientation 91.3% 904,180
Coordination 81.8% 809,900
Judgment and Decision Making 78.5% 777,590
Negotiation 71.5% 707,970
Active Learning 69.9% 692,500

Knowledge areas

Knowledge area Employment reach Workers
English Language 98.2% 972,680
Customer and Personal Service 97.1% 961,970
Administration and Management 81.7% 809,290
Mathematics 76.7% 759,390
Sales and Marketing 58.3% 576,870
Law and Government 48.5% 480,370
Computers and Electronics 48.3% 478,630
Administrative 47.8% 473,280
Education and Training 44.5% 440,580
Communications and Media 42.9% 425,060
Transportation 35.7% 353,830
Economics and Accounting 21.3% 211,310

Abilities

Abilitie Employment reach Workers
Oral Comprehension 98.4% 974,150
Oral Expression 98.4% 974,150
Near Vision 98.3% 973,270
Speech Clarity 98.2% 972,170
Speech Recognition 98.2% 972,500
Written Comprehension 98.2% 972,630
Written Expression 98.1% 971,290
Information Ordering 97.0% 960,930
Problem Sensitivity 97.0% 961,010
Inductive Reasoning 96.7% 957,670
Deductive Reasoning 96.6% 956,270
Category Flexibility 83.8% 829,430

Tool categories

Tool category Employment reach Workers
Electronic mail software 99.5% 984,810
Office suite software 99.5% 984,900
Spreadsheet software 99.5% 984,920
Presentation software 99.3% 983,400
Data base user interface and query software 99.2% 982,510
Word processing software 99.2% 982,090
Document management software 97.3% 963,870
Internet browser software 94.2% 932,720
Operating system software 90.2% 893,610
Enterprise resource planning ERP software 90.0% 891,320
Financial analysis software 89.2% 882,890
Medical software 83.9% 831,000
Customer relationship management CRM software 82.0% 811,780
Web page creation and editing software 74.8% 740,400
Instant messaging software 73.0% 723,080

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 39 occupations in Insurance Agencies and Brokerages. Overlap measures shared tasks with AI, not automation. Lower overlap · higher pay Higher overlap · higher pay Higher overlap · lower pay Lower overlap · lower pay Administrative Services Managers Managers, All Other Compliance Officers Office Clerks, General Business Operations Specialists, All Other Receptionists and Information Clerks Computer User Support Specialists First-Line Supervisors of Office and Administrative Support Workers Project Management Specialists Secretaries and Administrative Assistants, Except Legal, Medical, and Executive Executive Secretaries and Executive Administrative Assistants Bookkeeping, Accounting, and Auditing Clerks Data Scientists 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
Insurance Sales Agents 353,250 35.7% $59,580
Customer Service Representatives 125,640 12.7% $45,260
Insurance Claims and Policy Processing Clerks 66,730 6.7% $48,950
General and Operations Managers 41,860 4.2% $124,580
Claims Adjusters, Examiners, and Investigators 40,880 4.1% $77,330
Office Clerks, General 32,770 3.3% $40,360
Insurance Underwriters 31,670 3.2% $79,200
First-Line Supervisors of Office and Administrative Support Workers 21,440 2.2% $74,050
Secretaries and Administrative Assistants, Except Legal, Medical, and Executive 19,920 2.0% $42,110
Market Research Analysts and Marketing Specialists 16,220 1.6% $71,250
Financial Managers 14,900 1.5% $170,950
Bookkeeping, Accounting, and Auditing Clerks 13,730 1.4% $48,500
Sales Managers 12,650 1.3% $156,130
Accountants and Auditors 12,020 1.2% $78,530
Software Developers 11,070 1.1% $130,540
Receptionists and Information Clerks 10,070 1.0% $36,820
First-Line Supervisors of Non-Retail Sales Workers 9,490 1.0% $83,350
Management Analysts 9,260 0.9% $98,900
Business Operations Specialists, All Other 7,900 0.8% $79,420
Human Resources Specialists 6,940 0.7% $77,810
Computer and Information Systems Managers 6,480 0.7% $177,330
Compensation, Benefits, and Job Analysis Specialists 6,470 0.7% $76,380
Securities, Commodities, and Financial Services Sales Agents 5,450 0.6% $80,010
Computer Systems Analysts 4,820 0.5% $100,510
Marketing Managers 4,680 0.5% $167,740
Training and Development Specialists 4,380 0.4% $79,940
Financial and Investment Analysts 4,320 0.4% $82,840
Managers, All Other 4,240 0.4% $160,730
Executive Secretaries and Executive Administrative Assistants 4,210 0.4% $73,860
Compliance Officers 3,910 0.4% $73,430
Lawyers 3,790 0.4% $166,060
Actuaries 3,590 0.4% $138,260
Computer User Support Specialists 3,580 0.4% $59,850
Personal Financial Advisors 3,360 0.3% $85,920
Financial Risk Specialists 3,050 0.3% $103,740
Project Management Specialists 2,940 0.3% $105,180
Administrative Services Managers 2,920 0.3% $131,690
Data Scientists 2,790 0.3% $116,020
Network and Computer Systems Administrators 2,750 0.3% $99,910
Sales and Related Workers, All Other 2,530 0.3% $58,330

Showing the top 40 of 145 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
Insurance Sales Agents 117.16× 353,250
Insurance Underwriters 45.74× 31,670
Insurance Claims and Policy Processing Clerks 45.36× 66,730
Insurance Appraisers, Auto Damage 29.98× 1,500
Claims Adjusters, Examiners, and Investigators 20.87× 40,880
Actuaries 19.72× 3,590
Compensation, Benefits, and Job Analysis Specialists 9.84× 6,470
Financial Risk Specialists 8.43× 3,050
Compensation and Benefits Managers 7.99× 1,030
Customer Service Representatives 7.18× 125,640
First-Line Supervisors of Non-Retail Sales Workers 6.75× 9,490
Brokerage Clerks 6.72× 1,730
Sales and Related Workers, All Other 3.98× 2,530
Statistical Assistants 3.43× 130
Sales Managers 3.26× 12,650
Market Research Analysts and Marketing Specialists 2.93× 16,220
Financial Managers 2.83× 14,900
Title Examiners, Abstractors, and Searchers 2.59× 800
File Clerks 2.5× 1,270
Data Entry Keyers 2.46× 2,140
Write a report on thisheadline · factoids · citation

The Insurance Agencies and Brokerages workforce sits at the 99th percentile of AI task overlap — 990,240 U.S. workers

  • Weighting every occupation by its real share of Insurance Agencies and Brokerages employment, the industry's workforce ranks in the 99th percentile (High 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 990,240 U.S. workers across 145 occupations.BLS OEWS (May 2024)
  • Employment-weighted typical annual pay is about $70,355.BLS OEWS (May 2024)
  • Of AI use observed across this industry's occupations, 49% looks like augmentation rather than automation — from a Claude.ai sample, not a census.Anthropic Economic Index
Copy the whole kit
The Insurance Agencies and Brokerages workforce sits at the 99th percentile of AI task overlap — 990,240 U.S. workers

• Weighting every occupation by its real share of Insurance Agencies and Brokerages employment, the industry's workforce ranks in the 99th percentile (High 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 990,240 U.S. workers across 145 occupations. (BLS OEWS (May 2024))
• Employment-weighted typical annual pay is about $70,355. (BLS OEWS (May 2024))
• Of AI use observed across this industry's occupations, 49% looks like augmentation rather than automation — from a Claude.ai sample, not a census. (Anthropic Economic Index)

Source: Singulariki — "Insurance Agencies and Brokerages". https://singulariki.com/industries/524210
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. "Insurance Agencies and Brokerages." 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/524210

APA

Singulariki. (2026). Insurance Agencies and Brokerages. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/industries/524210

BibTeX 
@misc{singulariki-524210,
  title  = {Insurance Agencies and Brokerages},
  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/524210}
}

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