Skip to content
Singulariki

Sporting Goods Retailers

National industry · NAICS 459110

Take this to your AI
Download .md

A source-stamped Markdown brief of this occupation — paste it into an agent, or fetch /industries/459110/context.md directly.

Sporting Goods Retailers is a U.S. industry in the NAICS classification. The Bureau of Labor Statistics estimates about 297,700 workers across 124 detailed occupations in it. A typical worker earns around $39,410 a year (Singulariki estimate, see below).

This industry comprises establishments primarily engaged in retailing new sporting goods, such as bicycles and bicycle parts; camping equipment; exercise and fitness equipment; athletic uniforms; specialty sports footwear; and other sporting goods, equipment, and accessories. Illustrative Examples: Athletic uniform supply retailers Fishing supply retailers Bicycle (except motorized) retailers Golf pro shops Bowling equipment and supply retailers Tack shops Diving equipment retailers Sporting goods (e.g., scuba, skiing, ball sports) retailers Exercise equipment retailers Sporting gun and hunting equipment retailers Camping and hiking equipment retailers 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 — 72nd 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 104 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 85.3% of employment · 71/111 occupations have AEI task data
Augmentation vs. automation 37.4% working with AI · 31.0% 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
Recommend, select, and help locate or obtain merchandise based on customer needs and desires. Retail Salespersons Iteration 24.3%
Greet customers and ascertain what each customer wants or needs. Retail Salespersons none 23.5%
Answer customers' questions, and provide information on procedures or policies. Cashiers Directive 16.9%
Describe merchandise and explain use, operation, and care of merchandise to customers. Retail Salespersons Learning 8.2%
Troubleshoot problems involving office equipment, such as computer hardware and software. Office Clerks, General Feedback loop 6.3%
Answer questions regarding the store and its merchandise. Retail Salespersons Directive 3.9%
Assist customers by providing information and resolving their complaints. Cashiers Iteration 2.3%
Provide customer service by greeting and assisting customers and responding to customer inquiries and complaints. First-Line Supervisors of Retail Sales Workers Directive 0.9%
Prepare merchandise for purchase or rental. Retail Salespersons Directive 0.9%
Greet customers entering establishments. Cashiers none 0.8%
Conduct classes, workshops, and demonstrations, and provide individual instruction to teach topics and skills such as cooking, dancing, writing, physical fitness, photography, personal finance, and flying. Self-Enrichment Teachers Learning 0.7%
Confer with company officials to develop methods and procedures to increase sales, expand markets, and promote business. First-Line Supervisors of Retail Sales Workers Iteration 0.6%

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
Retail Salespersons 145,500 48.9% none
First-Line Supervisors of Retail Sales Workers 23,290 7.8% Iteration
Cashiers 21,140 7.1% Directive
General and Operations Managers 12,690 4.3% Iteration
Customer Service Representatives 8,670 2.9% Directive
Shipping, Receiving, and Inventory Clerks 7,650 2.6% Iteration
Office Clerks, General 3,630 1.2% Feedback loop
Bookkeeping, Accounting, and Auditing Clerks 2,690 0.9% Directive
Sales Managers 2,490 0.8% Iteration
Merchandise Displayers and Window Trimmers 1,940 0.7% Iteration
Self-Enrichment Teachers 1,890 0.6% Learning
Sales Representatives, Wholesale and Manufacturing, Except Technical and Scientific Products 1,740 0.6% 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 97.4% of this industry's employment that maps to a detailed occupation with an O*NET skill profile.

Skills

Skill Employment reach Workers
Active Listening 96.3% 286,700
Speaking 91.6% 272,780
Reading Comprehension 86.8% 258,530
Social Perceptiveness 85.3% 254,020
Service Orientation 83.6% 249,000
Critical Thinking 83.5% 248,580
Monitoring 78.8% 234,620
Time Management 77.6% 231,090
Writing 74.9% 223,120
Coordination 73.2% 217,860
Active Learning 69.0% 205,530
Persuasion 69.0% 205,540

Knowledge areas

Knowledge area Employment reach Workers
English Language 95.9% 285,570
Customer and Personal Service 91.8% 273,240
Administration and Management 78.1% 232,420
Mathematics 76.2% 226,930
Administrative 74.6% 221,940
Sales and Marketing 74.6% 221,960
Computers and Electronics 21.6% 64,270
Economics and Accounting 15.3% 45,530
Personnel and Human Resources 15.3% 45,540
Production and Processing 14.7% 43,890
Education and Training 13.5% 40,120
Mechanical 6.2% 18,600

Abilities

Abilitie Employment reach Workers
Near Vision 97.4% 290,080
Oral Comprehension 96.8% 288,290
Oral Expression 96.5% 287,190
Information Ordering 95.9% 285,610
Speech Recognition 95.2% 283,510
Speech Clarity 95.0% 282,820
Written Comprehension 93.9% 279,660
Problem Sensitivity 92.2% 274,360
Written Expression 78.7% 234,360
Deductive Reasoning 34.6% 103,000
Inductive Reasoning 33.9% 100,880
Category Flexibility 31.5% 93,920

Tool categories

Tool category Employment reach Workers
Spreadsheet software 97.6% 290,700
Data base user interface and query software 94.0% 279,870
Office suite software 94.0% 279,880
Internet browser software 92.4% 275,050
Word processing software 90.0% 268,040
Electronic mail software 89.9% 267,610
Operating system software 86.5% 257,490
Enterprise resource planning ERP software 81.9% 243,890
Accounting software 81.1% 241,430
Presentation software 78.4% 233,350
Document management software 77.3% 230,020
Desktop publishing software 74.0% 220,380
Graphics or photo imaging software 72.3% 215,240
Web page creation and editing software 72.2% 214,930
Customer relationship management CRM software 71.7% 213,560

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 36 occupations in Sporting Goods Retailers. 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 Packers and Packagers, Hand Maintenance and Repair Workers, General Light Truck Drivers Security Guards Fast Food and Counter Workers First-Line Supervisors of Mechanics, Installers, and Repairers First-Line Supervisors of Retail Sales Workers Self-Enrichment Teachers First-Line Supervisors of Production and Operating Workers General and Operations Managers Retail Salespersons Counter and Rental Clerks Sales Managers Business Operations Specialists, All Other First-Line Supervisors of Office and Administrative Support Workers Graphic Designers Bookkeeping, Accounting, and Auditing Clerks 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
Retail Salespersons 145,500 48.9% $34,710
First-Line Supervisors of Retail Sales Workers 23,290 7.8% $47,610
Cashiers 21,140 7.1% $30,940
General and Operations Managers 12,690 4.3% $71,320
Stockers and Order Fillers 10,480 3.5% $34,930
Bicycle Repairers 10,310 3.5% $39,660
Customer Service Representatives 8,670 2.9% $35,990
Shipping, Receiving, and Inventory Clerks 7,650 2.6% $37,250
Office Clerks, General 3,630 1.2% $39,780
Laborers and Freight, Stock, and Material Movers, Hand 3,390 1.1% $36,680
Bookkeeping, Accounting, and Auditing Clerks 2,690 0.9% $45,320
Installation, Maintenance, and Repair Workers, All Other 2,630 0.9% $44,570
Sales Managers 2,490 0.8% $76,340
Buyers and Purchasing Agents 2,010 0.7% $53,470
Merchandise Displayers and Window Trimmers 1,940 0.7% $36,360
Self-Enrichment Teachers 1,890 0.6% $37,820
Sales Representatives, Wholesale and Manufacturing, Except Technical and Scientific Products 1,740 0.6% $54,030
First-Line Supervisors of Office and Administrative Support Workers 1,610 0.5% $58,140
Sales Representatives of Services, Except Advertising, Insurance, Financial Services, and Travel 1,420 0.5% $35,730
Maintenance and Repair Workers, General 1,390 0.5% $39,640
Amusement and Recreation Attendants 1,380 0.5% $31,190
First-Line Supervisors of Mechanics, Installers, and Repairers 1,360 0.5% $53,970
Secretaries and Administrative Assistants, Except Legal, Medical, and Executive 1,290 0.4% $43,680
Counter and Rental Clerks 1,280 0.4% $37,630
Sewing Machine Operators 1,270 0.4% $35,480
Market Research Analysts and Marketing Specialists 1,260 0.4% $54,530
Miscellaneous Assemblers and Fabricators 1,110 0.4% $38,550
Security Guards 1,090 0.4% $30,380
Sales and Related Workers, All Other 1,040 0.3% $38,470
Printing Press Operators 950 0.3% $36,870
First-Line Supervisors of Transportation and Material Moving Workers, Except Aircraft Cargo Handling Supervisors 940 0.3% $58,940
Order Clerks 870 0.3% $34,710
Fast Food and Counter Workers 770 0.3% $26,560
Light Truck Drivers 740 0.2% $38,370
Packers and Packagers, Hand 690 0.2% $34,810
Accountants and Auditors 660 0.2% $77,410
Graphic Designers 640 0.2% $46,160
Business Operations Specialists, All Other 620 0.2% $44,460
Janitors and Cleaners, Except Maids and Housekeeping Cleaners 600 0.2% $29,990
First-Line Supervisors of Production and Operating Workers 480 0.2% $57,150

Showing the top 40 of 124 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
Bicycle Repairers 424.13× 10,310
Retail Salespersons 19.83× 145,500
First-Line Supervisors of Retail Sales Workers 10.84× 23,290
Shoe and Leather Workers and Repairers 10.17× 150
Installation, Maintenance, and Repair Workers, All Other 7.42× 2,630
Sewing Machine Operators 6× 1,270
Sales and Related Workers, All Other 5.44× 1,040
Order Clerks 5.4× 870
Merchandise Displayers and Window Trimmers 5.22× 1,940
Textile, Apparel, and Furnishings Workers, All Other 5.02× 140
Shipping, Receiving, and Inventory Clerks 4.62× 7,650
Tour and Travel Guides 4.02× 380
Cashiers 3.48× 21,140
Outdoor Power Equipment and Other Small Engine Mechanics 3.48× 230
Printing Press Operators 3.39× 950
Pressers, Textile, Garment, and Related Materials 3.28× 170
Self-Enrichment Teachers 3.17× 1,890
Private Detectives and Investigators 2.94× 220
Protective Service Workers, All Other 2.24× 360
Photographers 2.22× 220
Write a report on thisheadline · factoids · citation

The Sporting Goods Retailers workforce sits at the 72nd percentile of AI task overlap — 297,700 U.S. workers

  • Weighting every occupation by its real share of Sporting Goods Retailers employment, the industry's workforce ranks in the 72nd 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 297,700 U.S. workers across 124 occupations.BLS OEWS (May 2024)
  • Employment-weighted typical annual pay is about $39,410.BLS OEWS (May 2024)
  • Of AI use observed across this industry's occupations, 37% looks like augmentation rather than automation — from a Claude.ai sample, not a census.Anthropic Economic Index
Copy the whole kit
The Sporting Goods Retailers workforce sits at the 72nd percentile of AI task overlap — 297,700 U.S. workers

• Weighting every occupation by its real share of Sporting Goods Retailers employment, the industry's workforce ranks in the 72nd 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 297,700 U.S. workers across 124 occupations. (BLS OEWS (May 2024))
• Employment-weighted typical annual pay is about $39,410. (BLS OEWS (May 2024))
• Of AI use observed across this industry's occupations, 37% looks like augmentation rather than automation — from a Claude.ai sample, not a census. (Anthropic Economic Index)

Source: Singulariki — "Sporting Goods Retailers". https://singulariki.com/industries/459110
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. "Sporting Goods Retailers." 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/459110

APA

Singulariki. (2026). Sporting Goods Retailers. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/industries/459110

BibTeX 
@misc{singulariki-459110,
  title  = {Sporting Goods Retailers},
  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/459110}
}

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