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Parts Salespersons

Occupation · SOC 41-2022.00

Sell spare and replacement parts and equipment in repair shop or parts store.

Also called: Parts Consultant · Parts Counterperson · Parts Salesman · Parts Salesperson · Parts Advisor · Parts Counter Salesperson · Parts Counterman · Parts Person · Parts Specialist · Wholesale Parts Salesperson · Appliance Parts Counter Clerk · Automotive Parts Clerk (Auto Parts Clerk)

Job family: Sales and Related Occupations

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Download .md

A source-stamped Markdown brief of this occupation — paste it into an agent, or fetch /roles/role-41-2022-00/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.

  • Receive payment or obtain credit authorization. · 0.7%
See collaboration patterns →

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.

  • Receive payment or obtain credit authorization. · 100.0% need a human
  • Assist customers, such as responding to customer complaints and updating them about back-ordered parts. · 100.0% need a human
See the boundary tasks →

55th-percentile task overlap — yet about 30,200 openings a year (+3.1% projected, BLS), and observed AI use leans 2897% 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 46th -0.1
LLM task exposure, γ (OpenAI / Eloundou) Moderate 44th 0.5
AI assistant applicability (Microsoft) High 78th 0.2

OpenAI's exposure study scores tasks three ways: with a language model alone (α 0.2), with simple added tooling (β 0.3), and including AI-powered software (γ 0.5). 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 1.0 · 97th 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.

Receive payment or obtain credit authorization. 2.8%
Determine replacement parts required, according to inspections of old parts, customer requests, or customers' descriptions of malfunctions. 0.3%
Measure parts, using precision measuring instruments, to determine whether similar parts may be machined to required sizes. 0.2%

Job outlook

Independent U.S. Bureau of Labor Statistics employment projection for 2024–2034 — a labor-market forecast, not an AI-impact forecast.

Outlook About average · +3.1% by 2034
Projected annual openings 30,200
Employment 2024 → 2034 272,100 → 280,600

“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.

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 29.0% working with AI · 16.8% handed to AI
Most common way people use AI here Learning · you ask AI to explain or teach
Typical AI autonomy 3.0 / 5 · higher = AI acts more independently
Used for work (vs. personal / coursework) 41.1%

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
Receive payment or obtain credit authorization. Learning 0.7%
Assist customers, such as responding to customer complaints and updating them about back-ordered parts. — 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.

Receive payment or obtain credit authorization. 100.0%
Assist customers, such as responding to customer complaints and updating them about back-ordered parts. 100.0%

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 receive payment or obtain credit authorization.

    From: Receive payment or obtain credit authorization. · 0.7% of measured AI use · learning

  • Help me assist customers, such as responding to customer complaints and updating them about back-ordered parts.

    From: Assist customers, such as responding to customer complaints and updating them about back-ordered parts. · 0.4% of measured AI use

Tasks

All 19 tasks O*NET lists for this occupation, ordered by importance. Each links to its own page with AI-exposure and observed-use detail.

Work activities

Knowledge, skills & abilities

O*NET importance rating, from 1 (not important) to 5 (extremely important).

Knowledge

Customer and Personal Service 4.4
Sales and Marketing 4.1
Administration and Management 4.0
Administrative 3.9
Computers and Electronics 3.8
English Language 3.6
Economics and Accounting 3.5
Production and Processing 3.3
Personnel and Human Resources 3.3
Mathematics 3.2
Mechanical 3.1
Education and Training 2.9

Essential skills

Active Listening 4.0
Speaking 4.0
Reading Comprehension 3.6
Critical Thinking 3.3
Monitoring 3.1
Writing 3.0
Active Learning 2.9

Abilities

Oral Comprehension 4.0
Oral Expression 4.0
Near Vision 3.9
Written Comprehension 3.8
Speech Recognition 3.8
Speech Clarity 3.6
Information Ordering 3.5
Written Expression 3.4
Problem Sensitivity 3.3
Inductive Reasoning 3.3
Category Flexibility 3.1
Deductive Reasoning 3.0
Flexibility of Closure 3.0
Perceptual Speed 3.0
Selective Attention 3.0
Finger Dexterity 3.0

Transferable skills

Persuasion 3.8
Service Orientation 3.6
Social Perceptiveness 3.4
Judgment and Decision Making 3.0
Time Management 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.

Tools & technology

Example Category
Microsoft Excel Spreadsheet software Hot technology In demand
Microsoft Office software Office suite software Hot technology In demand
Microsoft Word Word processing software Hot technology In demand
Adobe Acrobat Document management software Hot technology
Microsoft Outlook Electronic mail software Hot technology
Microsoft PowerPoint Presentation software Hot technology
SAP software Enterprise resource planning ERP software Hot technology
Inventory control system software Inventory management software In demand
Inventory management systems Inventory management software In demand
Customer information databases Customer relationship management CRM software
Inventory tracking software Inventory management software
SmugMug Flickr Graphics or photo imaging software
Web browser software Internet browser software

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.

Contact With Others 5.0
Work With or Contribute to a Work Group or Team 4.9
Deal With External Customers or the Public in General 4.8
Telephone Conversations 4.8
Freedom to Make Decisions 4.5
E-Mail 4.5
Indoors, Not Environmentally Controlled 4.4
Exposed to Sounds, Noise Levels that are Distracting or Uncomfortable 4.3
Face-to-Face Discussions with Individuals and Within Teams 4.2
Indoors, Environmentally Controlled 4.2
Work Outcomes and Results of Other Workers 4.2
Determine Tasks, Priorities and Goals 4.1
Impact of Decisions on Co-workers or Company Results 4.1
Time Pressure 4.1
Importance of Being Exact or Accurate 4.0
Importance of Repeating Same Tasks 4.0
Dealing With Unpleasant, Angry, or Discourteous People 4.0
Frequency of Decision Making 4.0
Coordinate or Lead Others in Accomplishing Work Activities 4.0
Physical Proximity 4.0
Exposed to Contaminants 3.9
Spend Time Standing 3.8
Exposed to Very Hot or Cold Temperatures 3.8
Conflict Situations 3.7
Spend Time Walking or Running 3.4
Health and Safety of Other Workers 3.3
Outdoors, Exposed to All Weather Conditions 3.3
Exposed to Extremely Bright or Inadequate Lighting Conditions 3.1
Spend Time Making Repetitive Motions 3.1
Written Letters and Memos 2.9
Wear Common Protective or Safety Equipment such as Safety Shoes, Glasses, Gloves, Hearing Protection, Hard Hats, or Life Jackets 2.9
Exposed to Cramped Work Space, Awkward Positions 2.9
In an Open Vehicle or Operating Equipment 2.8
Spend Time Bending or Twisting Your Body 2.6
Spend Time Sitting 2.6
Level of Competition 2.6
Exposed to Hazardous Equipment 2.6
Consequence of Error 2.5
In an Enclosed Vehicle or Operate Enclosed Equipment 2.5
Spend Time Using Your Hands to Handle, Control, or Feel Objects, Tools, or Controls 2.5

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.

What to study: Business, Management, Marketing, and Related Support Services . Fields of study crosswalked to this occupation (NCES CIP–SOC), not a requirement.

Education of current workers

Share of people in this occupation at each level of education.

High School Diploma 46.9%
Some College Courses 25.2%
Bachelor's Degree 13.6%
Associate's Degree (or other 2-year degree) 9.3%
Post-Secondary Certificate 5.0%

Interests & work styles

The interests and personal qualities O*NET associates with people who do this work.

Career interests (Holland / RIASEC)

Realistic 5.6
Conventional 5.1
Enterprising 3.8
Social 2.0

Interest areas

Sales 5.0
Mechanics/Electronics 3.8
Physical/Manual Labor 2.5
Office Work 2.5
Management/Administration 2.2
Engineering 2.2
Personal Service 2.0
Accounting 1.9

Work styles

Dependability 3.0
Social Orientation 2.1
Attention to Detail 2.0
Cooperation 1.8

Wages & employment

U.S. · annual wages (BLS OEWS)

$28k10th$31k25th$37kMedian$48k75th$62k90th
Annual wages by percentile — U.S. (BLS OEWS). The light band spans the 10th–90th percentile; the darker band is the middle half (25th–75th); the line is the median.
272k2024281k2034 (proj.)+3.1% · About average
Projected U.S. employment, 2024–2034 (BLS Employment Projections). A labor-market forecast for the occupation, not an AI-impact forecast.
10th percentile $27,770
25th percentile $30,630
Median (50th) $37,440
75th percentile $48,410
90th percentile $61,750
People employed 265,060

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 196,260 $35,930
Wholesale Trade · Sector 50,070 $48,600
Other Services (except Public Administration) · Sector 11,690 $46,880
Farm and Garden Machinery and Equipment Merchant Wholesalers · National industry 10,190 $46,380
Manufacturing · Sector 2,200 $52,030
Real Estate and Rental and Leasing · Sector 1,490 $50,550
Transportation and Warehousing · Sector 930 $45,540
Management of Companies and Enterprises · Sector 720 $48,300
Administrative and Support and Waste Management and Remediation Services · Sector 670 $40,390
Construction · Sector 440 $49,590
Temporary Help Services · National industry 330 $36,480
Sporting Goods Retailers · National industry 240 $34,100

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
Farm and Garden Machinery and Equipment Merchant Wholesalers · National industry 51.96× 10,190
Retail Trade · Sector 7.32× 196,260
Wholesale Trade · Sector 4.83× 50,070
Other Services (except Public Administration) · Sector 1.54× 11,690
Sporting Goods Retailers · National industry 0.47× 240
Real Estate and Rental and Leasing · Sector 0.37× 1,490
Machine Shops · National industry 0.36× 160
Management of Companies and Enterprises · Sector 0.15× 720

Part of the Marketing & Sales career cluster.

Exposure quadrant: AI task-overlap percentile vs Median pay Parts Salespersons sits at the 55th percentile of AI task-overlap and the 8th percentile of median pay, placed here against 11 adjacent occupations on the same two axes. Lower overlap · higher pay Higher overlap · higher pay Higher overlap · lower pay Lower overlap · lower pay Parts Salespersons Laborers and Freight, Stock, and Material Movers, Hand Automotive and Watercraft Service Attendants Engine and Other Machine Assemblers Home Appliance Repairers Shipping, Receiving, and Inventory Clerks Retail Salespersons Sales Representatives, Wholesale and Manufacturing, Technical and Scientific Products AI task-overlap percentile → ↑ Median pay
AI task-overlap percentile (horizontal) vs. median-pay percentile (vertical), across all scored occupations. This occupation is highlighted; related occupations are plotted alongside it. Overlap measures shared tasks with AI, not automation.

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 Parts 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.

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

Parts Salespersons show 55th-percentile AI task overlap — and about 30,200 annual U.S. openings

  • Parts Salespersons rank in the 55th 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 30,200 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 about average (+3.1%) from 2024 to 2034.BLS Employment Projections 2024–34
  • Median annual pay is $37,440, across about 265,060 U.S. workers.BLS OEWS (May 2024)
  • Of the AI use actually observed for this work, 29% 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
Parts Salespersons show 55th-percentile AI task overlap — and about 30,200 annual U.S. openings

• Parts Salespersons rank in the 55th 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 30,200 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 about average (+3.1%) from 2024 to 2034. (BLS Employment Projections 2024–34)
• Median annual pay is $37,440, across about 265,060 U.S. workers. (BLS OEWS (May 2024))
• Of the AI use actually observed for this work, 29% 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 — "Parts Salespersons". https://singulariki.com/roles/role-41-2022-00
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.

Data compiled June 2, 2026. Figures are estimates, not advice.

Cite this page
Plain

Singulariki. "Parts 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-41-2022-00

APA

Singulariki. (2026). Parts Salespersons. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-41-2022-00

BibTeX 
@misc{singulariki-role-41-2022-00,
  title  = {Parts 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-41-2022-00}
}

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

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