Often handed to AI
Task areas most often handled directively in observed AI conversations — candidates to delegate with light review.
- Answer questions regarding the store and its merchandise. · 1.7%
- Prepare merchandise for purchase or rental. · 0.4%
Retail Salespersons
Occupation · SOC 41-2031.00
Sell merchandise, such as furniture, motor vehicles, appliances, or apparel to consumers.
Also called: Sales Associate · Sales Clerk · Sales Consultant · Sales Person · Car Salesman · Customer Assistant · Retail Salesperson · Sales Representative · Salesman · Art Dealer · Art Objects Salesperson · Auto Dealer
Job family: Sales and Related Occupations
Take this to your AI
A source-stamped Markdown brief of this occupation — paste it into an agent, or fetch
/roles/role-41-2031-00/context.md directly.
AI work map
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.
Use as a copilot
Task areas where people work with AI — iterating, learning, or checking — staying in the loop rather than handing the task off.
- Recommend, select, and help locate or obtain merchandise based on customer needs and desires. · 11.0%
- Describe merchandise and explain use, operation, and care of merchandise to customers. · 3.7%
Keep a human in the loop
Task areas where a human was still judged necessary in a large share of observed conversations — not a safety ruling, an observed-need signal.
- Describe merchandise and explain use, operation, and care of merchandise to customers. · 100.0% need a human
- Answer questions regarding the store and its merchandise. · 100.0% need a human
- Recommend, select, and help locate or obtain merchandise based on customer needs and desires. · 99.9% need a human
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 →Market signal
Independent published positions, read together — not a forecast.
- Declining employment outlook (-0.5% by 2034)
- 555,800 openings/yr
- High AI exposure
- Observed AI use leans augmentation
- Median pay $34,580/yr
- Work is mostly on-site (not teleworkable)
- Both the 2013 computerization estimate and today's AI exposure rank this high
62nd-percentile task overlap — yet about 555,800 openings a year (-0.5% projected, BLS), and observed AI use leans 3139% copilot, not hand-off (AEI) . What exposure means →
AI & job outlook
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.
Exposure to current AI
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.) Moderate | 50th | 0.1 | |
| LLM task exposure, γ (OpenAI / Eloundou) Moderate | 50th | 0.6 | |
| AI assistant applicability (Microsoft) High | 89th | 0.3 |
OpenAI's exposure study scores tasks three ways: with a language model alone (α 0.1), with simple added tooling (β 0.3), and including AI-powered software (γ 0.6). 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.
Historical automation estimate (2013)
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 · 82nd percentile among occupations · High
How AI is actually used in this job
Among measured AI assistant conversations mapped to this occupation (Anthropic Economic Index, 2026-01-15), these task types came up most. These are shares of observed AI conversations — not shares of the job, of worker time, or of what could be automated.
| Answer questions regarding the store and its merchandise. | 5.1% | |
| Greet customers and ascertain what each customer wants or needs. | 4.2% | |
| Recommend, select, and help locate or obtain merchandise based on customer needs and desires. | 2.0% | |
| Describe merchandise and explain use, operation, and care of merchandise to customers. | 0.8% |
Job outlook
Independent U.S. Bureau of Labor Statistics employment projection for 2024–2034 — a labor-market forecast, not an AI-impact forecast.
| Outlook | Declining · -0.5% by 2034 |
| Projected annual openings | 555,800 |
| Employment 2024 → 2034 | 3,936,700 → 3,917,100 |
“Annual openings” counts new jobs plus replacements for workers who leave the occupation, so it can be large even when growth is modest.
Where this work sits on the global GenAI gradient
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.
Retail Salespersons sits at the 74th percentile of 427
occupations on the global GenAI task-exposure gradient
— exposure eased from 2023 to 2025. Each dot is one occupation; the
ringed one is this work. Exposure is task overlap, not automation or jobs lost.
38% mean task exposure (2025)
74th percentile of 427 placed occupations
−6 pts shift 2023 → 2025
| International occupation (ISCO-08) | Task exposure (2025) | Most tasks fall in |
|---|---|---|
| Shop Sales Assistants · 5223 | 38% | Gradient 1 |
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.
Working with AI in this job
How people actually apply AI to this occupation's tasks, from Claude.ai (Free and Pro) conversations in the Anthropic Economic Index, 2026-01-15. This is one AI assistant's consumer sample — not all AI, not the whole workforce. Autonomy and the collaboration mix are model-rated estimates; figures below the sample floor are hidden.
| Augmentation vs. automation | 31.4% working with AI · 26.5% handed to AI |
| Most common way people use AI here | none · |
| Typical AI autonomy | 4.0 / 5 · higher = AI acts more independently |
| Used for work (vs. personal / coursework) | 2.5% |
What people delegate to AI
The role's most common tasks in AI conversations, each tagged with how people work with the AI on it. “Usage” is the share of observed conversations, not of the job.
| Task | How | Usage |
|---|---|---|
| Recommend, select, and help locate or obtain merchandise based on customer needs and desires. | Iteration | 11.0% |
| Greet customers and ascertain what each customer wants or needs. | none | 10.6% |
| Describe merchandise and explain use, operation, and care of merchandise to customers. | Learning | 3.7% |
| Answer questions regarding the store and its merchandise. | Directive | 1.7% |
| Prepare merchandise for purchase or rental. | Directive | 0.4% |
Where a human is still needed
Tasks where the model most often judged that a person remained necessary — a useful read on the current boundary, not a guarantee.
| Describe merchandise and explain use, operation, and care of merchandise to customers. | 100.0% | |
| Answer questions regarding the store and its merchandise. | 100.0% | |
| Recommend, select, and help locate or obtain merchandise based on customer needs and desires. | 99.9% | |
| Greet customers and ascertain what each customer wants or needs. | 99.7% | |
| Prepare merchandise for purchase or rental. | 95.0% |
What people most often hand AI here
Example prompts phrased from the tasks people most often delegate to AI in this occupation (Anthropic Economic Index). Each shows the underlying measured task and its share of observed AI use. They are suggested phrasings of real tasks — starting points, not endorsed instructions.
-
Help me recommend, select, and help locate or obtain merchandise based on customer needs and desires.From: Recommend, select, and help locate or obtain merchandise based on customer needs and desires. · 11.0% of measured AI use · task iteration
-
Help me greet customers and ascertain what each customer wants or needs.From: Greet customers and ascertain what each customer wants or needs. · 10.6% of measured AI use · none
-
Help me describe merchandise and explain use, operation, and care of merchandise to customers.From: Describe merchandise and explain use, operation, and care of merchandise to customers. · 3.7% of measured AI use · learning
-
Help me answer questions regarding the store and its merchandise.From: Answer questions regarding the store and its merchandise. · 1.7% of measured AI use · directive
Tasks
All 24 tasks O*NET lists for this occupation, ordered by importance. Each links to its own page with AI-exposure and observed-use detail.
- Greet customers and ascertain what each customer wants or needs. Core · importance 4.8
- Recommend, select, and help locate or obtain merchandise based on customer needs and desires. Core · importance 4.7
- Maintain records related to sales. Supplemental · importance 4.6
- Compute sales prices, total purchases, and receive and process cash or credit payment. Core · importance 4.6
- Prepare merchandise for purchase or rental. Core · importance 4.5
- Answer questions regarding the store and its merchandise. Core · importance 4.5
- Maintain knowledge of current sales and promotions, policies regarding payment and exchanges, and security practices. Core · importance 4.5
- Open and close cash registers, performing tasks such as counting money, separating charge slips, coupons, and vouchers, balancing cash drawers, and making deposits. Supplemental · importance 4.4
- Prepare sales slips or sales contracts. Supplemental · importance 4.3
- Demonstrate use or operation of merchandise. Core · importance 4.3
- Describe merchandise and explain use, operation, and care of merchandise to customers. Core · importance 4.3
- Ticket, arrange, and display merchandise to promote sales. Core · importance 4.3
- Inventory stock and requisition new stock. Core · importance 4.2
- Exchange merchandise for customers and accept returns. Core · importance 4.2
- Estimate and quote trade-in allowances. Supplemental · importance 4.2
- Bag or package purchases and wrap gifts. Supplemental · importance 4.1
- Help customers try on or fit merchandise. Supplemental · importance 4.1
- Watch for and recognize security risks and thefts and know how to prevent or handle these situations. Core · importance 4.1
- Sell or arrange for delivery, insurance, financing, or service contracts for merchandise. Supplemental · importance 4.0
- Estimate quantity and cost of merchandise required, such as paint or floor covering. Supplemental · importance 3.8
- Place special orders or call other stores to find desired items. Core · importance 3.7
- Clean shelves, counters, and tables. Core · importance 3.7
- Rent merchandise to customers. Supplemental · importance 3.3
- Estimate cost of repair or alteration of merchandise. Supplemental · importance 3.2
Work activities
- Gather customer or product information to determine customer needs.
- Greet customers, patrons, or visitors.
- Reconcile records of sales or other financial transactions.
- Review laws or regulations to maintain professional knowledge.
- Calculate costs of goods or services.
- Process sales or other transactions.
- Maintain records of sales or other business transactions.
- Monitor work areas to provide security.
- Recommend products or services to customers.
- Answer customer questions about goods or services.
- Explain technical product or service information to customers.
- Advise customers on the use of products or services.
- Set up merchandise displays.
- Prepare sales or other contracts.
- Demonstrate products to consumers.
- Clean work areas.
- Package materials or products.
- Assist customers with product selection.
- Purchase stocks of merchandise or supplies.
- Monitor inventories of products or materials.
- Sell products or services.
- Arrange delivery of goods or services.
- Estimate costs or terms of sales.
- Arrange services or reservations for patrons.
Knowledge, skills & abilities
O*NET importance rating, from 1 (not important) to 5 (extremely important).
Knowledge
| Sales and Marketing | 4.5 | |
| Customer and Personal Service | 4.3 | |
| English Language | 3.7 | |
| Administration and Management | 3.0 | |
| Mathematics | 3.0 | |
| Administrative | 3.0 | |
| Psychology | 2.9 | |
| Computers and Electronics | 2.8 |
Abilities
| Oral Expression | 4.0 | |
| Oral Comprehension | 3.9 | |
| Speech Recognition | 3.6 | |
| Speech Clarity | 3.6 | |
| Problem Sensitivity | 3.1 | |
| Written Comprehension | 3.0 | |
| Written Expression | 3.0 | |
| Information Ordering | 3.0 | |
| Near Vision | 3.0 | |
| Fluency of Ideas | 2.9 | |
| Originality | 2.9 | |
| Deductive Reasoning | 2.9 | |
| Inductive Reasoning | 2.9 | |
| Category Flexibility | 2.9 | |
| Selective Attention | 2.9 | |
| Memorization | 2.8 |
Transferable skills
| Persuasion | 3.9 | |
| Service Orientation | 3.8 | |
| Social Perceptiveness | 3.5 | |
| Negotiation | 3.5 | |
| Coordination | 3.0 | |
| Time Management | 3.0 | |
| Instructing | 2.9 | |
| Judgment and Decision Making | 2.9 | |
| Complex Problem Solving | 2.8 |
Essential skills
| Active Listening | 3.8 | |
| Speaking | 3.8 | |
| Critical Thinking | 3.1 | |
| Reading Comprehension | 3.0 | |
| Writing | 3.0 | |
| Active Learning | 3.0 | |
| Monitoring | 3.0 |
Skills in demand
Skills employers ask for in job postings for this occupation (Lightcast), with whether each is a common or specialized skill.
Showing the top 40 of 53.
Tools & technology
Showing the top 40 of 80.
Work context
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.
How to get in
- Job zone
- Zone 2 — Job Zone 1-2: Very Little to Some Preparation Needed
- Education
- Usually requires a high school diploma or GED, though some occupations may not.
- Typical entry-level education
- No formal educational credential · BLS, the typical path — not a requirement
- Related experience
- Some occupations may need little or no previous experience; others require several months to a year of experience. For example, landscaping and groundskeeping workers might require very little training or previous experience, while agricultural equipment operators can benefit from on-the job training.
- Preparation level
- SVP (Below 6.0) — total schooling plus on-the-job experience.
Education of current workers
Share of people in this occupation at each level of education.
| High School Diploma | 63.5% | |
| Less than a High School Diploma | 19.3% | |
| Associate's Degree (or other 2-year degree) | 9.8% | |
| Bachelor's Degree | 4.0% | |
| Post-Secondary Certificate | 2.0% | |
| Some College Courses | 1.4% |
Interests & work styles
The interests and personal qualities O*NET associates with people who do this work.
Interest areas
| Sales | 6.8 | |
| Personal Service | 3.1 | |
| Marketing/Advertising | 2.5 | |
| Public Speaking | 2.2 | |
| Management/Administration | 2.0 | |
| Business Initiatives | 1.9 |
Career interests (Holland / RIASEC)
| Enterprising | 6.1 | |
| Conventional | 5.2 | |
| Realistic | 3.2 | |
| Social | 3.0 | |
| Artistic | 2.0 |
Work styles
| Social Orientation | 2.6 | |
| Optimism | 2.1 | |
| Dependability | 2.0 | |
| Cooperation | 1.9 | |
| Perseverance | 1.8 |
Wages & employment
U.S. · annual wages (BLS OEWS)
| 10th percentile | $25,600 |
| 25th percentile | $29,140 |
| Median (50th) | $34,580 |
| 75th percentile | $37,850 |
| 90th percentile | $47,930 |
| People employed | 3,800,250 |
Industries that employ this occupation
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 |
|---|---|---|
| Retail Trade · Sector | 3,445,820 | $34,550 |
| Sporting Goods Retailers · National industry | 145,500 | $34,710 |
| Wholesale Trade · Sector | 63,020 | $37,440 |
| Arts, Entertainment, and Recreation · Sector | 52,100 | $32,590 |
| Manufacturing · Sector | 44,090 | $34,560 |
| Administrative and Support and Waste Management and Remediation Services · Sector | 34,190 | $35,980 |
| Health Care and Social Assistance · Sector | 23,230 | $32,310 |
| Accommodation and Food Services · Sector | 21,110 | $31,740 |
| Other Services (except Public Administration) · Sector | 21,030 | $35,100 |
| Professional, Scientific, and Technical Services · Sector | 17,140 | $34,710 |
| Finance and Insurance · Sector | 15,290 | $35,440 |
| Pharmacies and Drug Retailers · National industry | 11,100 | $35,050 |
Where this work is most concentrated
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 |
|---|---|---|
| Sporting Goods Retailers · National industry | 19.83× | 145,500 |
| Retail Trade · Sector | 8.97× | 3,445,820 |
| Jewelry and Silverware Manufacturing · National industry | 2.04× | 1,000 |
| Arts, Entertainment, and Recreation · Sector | 0.8× | 52,100 |
| Farm and Garden Machinery and Equipment Merchant Wholesalers · National industry | 0.64× | 1,800 |
| Pharmacies and Drug Retailers · National industry | 0.64× | 11,100 |
| Offices of Optometrists · National industry | 0.51× | 1,930 |
| Wholesale Trade · Sector | 0.42× | 63,020 |
Related occupations
Part of the Marketing & Sales career cluster.
- Counter and Rental Clerks · 41-2021.00 Compare →
- Door-to-Door Sales Workers, News and Street Vendors, and Related Workers · 41-9091.00 Compare →
- Stockers and Order Fillers · 53-7065.00 Compare →
- Demonstrators and Product Promoters · 41-9011.00 Compare →
- First-Line Supervisors of Retail Sales Workers · 41-1011.00 Compare →
- Cashiers · 41-2011.00 Compare →
- Parts Salespersons · 41-2022.00 Compare →
- Customer Service Representatives · 43-4051.00 Compare →
- Telemarketers · 41-9041.00 Compare →
- Order Clerks · 43-4151.00 Compare →
- Sales Representatives, Wholesale and Manufacturing, Except Technical and Scientific Products · 41-4012.00 Compare →
- Wholesale and Retail Buyers, Except Farm Products · 13-1022.00 Compare →
Side-by-side comparisons place two occupations’ pay, preparation, skills, and AI exposure on the same page — same data, same scale, no forecast.
What you can do with this
Options the data surfaces for Retail Salespersons — not advice or a forecast. Each is a real cross-link you can follow into the evidence.
Skills that travel
Capabilities this work builds that are used across many other occupations.
Adjacent roles
Occupations O*NET rates as related — the nearby moves on the map.
Paths in
How people typically prepare for this work.
- No formal educational credential · typical entry level
- Job zone 2 — Job Zone 1-2: Very Little to Some Preparation Needed · preparation tier
Zoom out
On the global GenAI exposure gradient this work sits around the 74th percentile of 427 international occupations.
Write a report on thisheadline · factoids · citation
Retail Salespersons show 62nd-percentile AI task overlap — and about 555,800 annual U.S. openings
- Retail Salespersons rank in the 62nd percentile (Moderate 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 555,800 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 (-0.5%) from 2024 to 2034.BLS Employment Projections 2024–34
- Median annual pay is $34,580, across about 3,800,250 U.S. workers.BLS OEWS (May 2024)
- Of the AI use actually observed for this work, 31% looks like augmentation (drafting, iterating, checking) rather than hands-off automation — from a Claude.ai usage sample, not a census.2026-01-15-v4-plus-2025-03-27-v2
Copy the whole kit
Retail Salespersons show 62nd-percentile AI task overlap — and about 555,800 annual U.S. openings • Retail Salespersons rank in the 62nd percentile (Moderate 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 555,800 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 (-0.5%) from 2024 to 2034. (BLS Employment Projections 2024–34) • Median annual pay is $34,580, across about 3,800,250 U.S. workers. (BLS OEWS (May 2024)) • Of the AI use actually observed for this work, 31% looks like augmentation (drafting, iterating, checking) rather than hands-off automation — from a Claude.ai usage sample, not a census. (2026-01-15-v4-plus-2025-03-27-v2) Source: Singulariki — "Retail Salespersons". https://singulariki.com/roles/role-41-2031-00 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.
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
- BLS Employment Projections 2024–2034 U.S. Bureau of Labor Statistics
- Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27) Anthropic
- Microsoft “Working with AI” working-with-ai Microsoft Research
- “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130 OpenAI / academic
- AI Occupational Exposure (AIOE) Felten, Raj & Seamans academic
- ILO / Gmyrek et al. GenAI exposure gradient 2025 International Labour Organization
- IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022 Institute for Structural Research (IBS)
- Frey & Osborne (2013) frey-osborne-automation academic
- Dingel & Neiman (2020) dingel-neiman-workathome academic
Data compiled June 2, 2026. Figures are estimates, not advice.
Cite this page
Plain
Singulariki. "Retail Salespersons." 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; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); 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-41-2031-00
APA
Singulariki. (2026). Retail Salespersons. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-41-2031-00
BibTeX
@misc{singulariki-role-41-2031-00,
title = {Retail Salespersons},
author = {{Singulariki}},
year = {2026},
note = {O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); 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-41-2031-00}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.