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Counter and Rental Clerks

Occupation · SOC 41-2021.00

Receive orders, generally in person, for repairs, rentals, and services. May describe available options, compute cost, and accept payment.

Also called: Counter Clerk · Rental Agent · Rental Sales Representative · Video Clerk · Counter Service Representative · Leasing Consultant · Rental Assistant · Rental Associate · Rental Clerk · Rental Counter Clerk · Airplane Charter Clerk · Apartment Rental 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-41-2021-00/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.

Often handed to AI

Task areas most often handled directively in observed AI conversations — candidates to delegate with light review.

  • Provide information about rental items, such as availability, operation, or description. · 1.5%
See how AI is used here →

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 and provide advice on a wide variety of products and services. · 6.2%
  • Explain rental fees, policies, and procedures. · 2.6%
  • Advise customers on use and care of merchandise. · 1.0%
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.

  • Advise customers on use and care of merchandise. · 100.0% need a human
  • Recommend and provide advice on a wide variety of products and services. · 99.7% need a human
  • Provide information about rental items, such as availability, operation, or description. · 99.4% need a human
See the boundary tasks →

71st-percentile task overlap — yet about 45,900 openings a year (+3.2% projected, BLS), and observed AI use leans 5547% 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 66th 0.8
AI assistant applicability (Microsoft) High 96th 0.3

OpenAI's exposure study scores tasks three ways: with a language model alone (α 0.3), with simple added tooling (β 0.5), and including AI-powered software (γ 0.8). 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 · 94th 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.

Recommend and provide advice on a wide variety of products and services. 13.0%
Provide information about rental items, such as availability, operation, or description. 2.2%
Explain rental fees, policies, and procedures. 0.7%
Advise customers on use and care of merchandise. 0.4%

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 · +3.2% by 2034
Projected annual openings 45,900
Employment 2024 → 2034 408,200 → 421,300

“Annual openings” counts new jobs plus replacements for workers who leave the occupation, so it can be large even when growth is modest.

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 55.5% working with AI · 39.2% handed to AI
Most common way people use AI here Directive · AI does it; you give the instruction
Typical AI autonomy 3.5 / 5 · higher = AI acts more independently
Used for work (vs. personal / coursework) 12.6%

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 and provide advice on a wide variety of products and services. Iteration 6.2%
Explain rental fees, policies, and procedures. Learning 2.6%
Provide information about rental items, such as availability, operation, or description. Directive 1.5%
Advise customers on use and care of merchandise. Learning 1.0%

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.

Advise customers on use and care of merchandise. 100.0%
Recommend and provide advice on a wide variety of products and services. 99.7%
Provide information about rental items, such as availability, operation, or description. 99.4%
Explain rental fees, policies, and procedures. 96.1%

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 and provide advice on a wide variety of products and services.

    From: Recommend and provide advice on a wide variety of products and services. · 6.2% of measured AI use · task iteration

  • Help me explain rental fees, policies, and procedures.

    From: Explain rental fees, policies, and procedures. · 2.6% of measured AI use · learning

  • Help me provide information about rental items, such as availability, operation, or description.

    From: Provide information about rental items, such as availability, operation, or description. · 1.5% of measured AI use · directive

  • Help me advise customers on use and care of merchandise.

    From: Advise customers on use and care of merchandise. · 1.0% of measured AI use · learning

Tasks

All 16 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 4.5
English Language 3.7
Administrative 3.5
Sales and Marketing 3.4
Administration and Management 3.0
Mathematics 3.0
Transportation 2.7
Computers and Electronics 2.6

Abilities

Oral Comprehension 4.0
Oral Expression 3.9
Speech Recognition 3.6
Speech Clarity 3.6
Near Vision 3.4
Written Comprehension 3.3
Problem Sensitivity 3.1
Information Ordering 3.1
Written Expression 3.0
Selective Attention 3.0
Deductive Reasoning 2.9
Inductive Reasoning 2.9
Number Facility 2.9
Far Vision 2.9
Category Flexibility 2.8
Flexibility of Closure 2.8
Perceptual Speed 2.8

Essential skills

Active Listening 3.8
Speaking 3.4
Reading Comprehension 3.3
Critical Thinking 3.1
Writing 3.0
Monitoring 3.0
Active Learning 2.8

Transferable skills

Service Orientation 3.4
Social Perceptiveness 3.1
Coordination 3.0
Time Management 3.0
Persuasion 2.9
Negotiation 2.9
Judgment and Decision Making 2.9
Complex Problem Solving 2.8

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 Outlook Electronic mail software Hot technology In demand
Microsoft PowerPoint Presentation software Hot technology
Microsoft Word Word processing software Hot technology
Oracle Database Data base user interface and query software Hot technology
Database software Data base user interface and query software
Inventory management systems Inventory management 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.

Telephone Conversations 5.0
Face-to-Face Discussions with Individuals and Within Teams 5.0
Contact With Others 4.9
Indoors, Environmentally Controlled 4.6
Work With or Contribute to a Work Group or Team 4.5
Deal With External Customers or the Public in General 4.4
Frequency of Decision Making 4.0
Dealing With Unpleasant, Angry, or Discourteous People 4.0
Importance of Being Exact or Accurate 4.0
E-Mail 4.0
Freedom to Make Decisions 3.9
Conflict Situations 3.8
Physical Proximity 3.7
Importance of Repeating Same Tasks 3.7
Exposed to Sounds, Noise Levels that are Distracting or Uncomfortable 3.6
Determine Tasks, Priorities and Goals 3.6
Coordinate or Lead Others in Accomplishing Work Activities 3.5
Exposed to Contaminants 3.4
Impact of Decisions on Co-workers or Company Results 3.4
Work Outcomes and Results of Other Workers 3.3
Time Pressure 3.3
Spend Time Standing 3.2
Spend Time Using Your Hands to Handle, Control, or Feel Objects, Tools, or Controls 3.1
Spend Time Sitting 3.1
In an Enclosed Vehicle or Operate Enclosed Equipment 2.9
Outdoors, Exposed to All Weather Conditions 2.8
Spend Time Making Repetitive Motions 2.8
Level of Competition 2.7
Health and Safety of Other Workers 2.6
Written Letters and Memos 2.5
Exposed to Very Hot or Cold Temperatures 2.5
Spend Time Walking or Running 2.4
Degree of Automation 2.1
Exposed to Minor Burns, Cuts, Bites, or Stings 2.1
Outdoors, Under Cover 2.0
Consequence of Error 1.9
Indoors, Not Environmentally Controlled 1.9
Wear Common Protective or Safety Equipment such as Safety Shoes, Glasses, Gloves, Hearing Protection, Hard Hats, or Life Jackets 1.7
Public Speaking 1.7
Spend Time Kneeling, Crouching, Stooping, or Crawling 1.6

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 55.9%
Bachelor's Degree 20.3%
Some College Courses 13.2%
Associate's Degree (or other 2-year degree) 9.5%
Less than a High School Diploma 0.8%
Post-Secondary Certificate 0.4%

Interests & work styles

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

Career interests (Holland / RIASEC)

Conventional 5.9
Enterprising 3.9
Social 3.3
Realistic 3.2

Interest areas

Personal Service 4.4
Sales 4.0
Office Work 3.6
Accounting 2.5
Marketing/Advertising 1.7
Management/Administration 1.7
Public Speaking 1.7
Human Resources 1.6

Work styles

Social Orientation 2.3
Dependability 2.1
Cooperation 1.9
Attention to Detail 1.8

Wages & employment

U.S. · annual wages (BLS OEWS)

$29k10th$34k25th$39kMedian$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.
408k2024421k2034 (proj.)+3.2% · 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 $28,580
25th percentile $34,200
Median (50th) $38,540
75th percentile $48,290
90th percentile $62,030
People employed 398,620

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
Real Estate and Rental and Leasing · Sector 189,840 $38,200
Retail Trade · Sector 79,360 $43,470
Other Services (except Public Administration) · Sector 52,250 $36,570
Wholesale Trade · Sector 28,970 $48,180
Administrative and Support and Waste Management and Remediation Services · Sector 23,040 $37,220
Arts, Entertainment, and Recreation · Sector 11,910 $28,590
Temporary Help Services · National industry 3,040 $37,120
Transportation and Warehousing · Sector 2,600 $38,100
Accommodation and Food Services · Sector 2,300 $31,470
Fitness and Recreational Sports Centers · National industry 2,190 $27,650
Professional, Scientific, and Technical Services · Sector 1,590 $33,330
Manufacturing · Sector 1,530 $38,140

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
Real Estate and Rental and Leasing · Sector 31.01× 189,840
Farm and Garden Machinery and Equipment Merchant Wholesalers · National industry 4.82× 1,420
Other Services (except Public Administration) · Sector 4.57× 52,250
Retail Trade · Sector 1.97× 79,360
Wholesale Trade · Sector 1.86× 28,970
Arts, Entertainment, and Recreation · Sector 1.74× 11,910
Sporting Goods Retailers · National industry 1.66× 1,280
Fitness and Recreational Sports Centers · National industry 1.34× 2,190

Part of the Hospitality, Events, & Tourism career cluster.

Exposure quadrant: AI task-overlap percentile vs Median pay Counter and Rental Clerks sits at the 71st percentile of AI task-overlap and the 11th percentile of median pay, placed here against 12 adjacent occupations on the same two axes. Lower overlap · higher pay Higher overlap · higher pay Higher overlap · lower pay Lower overlap · lower pay Counter and Rental Clerks Stockers and Order Fillers Shipping, Receiving, and Inventory Clerks Cashiers Door-to-Door Sales Workers, News and Street Vendors, and Related Workers Sales Representatives, Wholesale and Manufacturing, Technical and Scientific Products Sales Representatives, Wholesale and Manufacturing, Except 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 Counter and Rental Clerks — 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

See where this work sits in the bigger picture.

Write a report on thisheadline · factoids · citation

Counter and Rental Clerks show 71st-percentile AI task overlap — and about 45,900 annual U.S. openings

  • Counter and Rental Clerks rank in the 71st percentile (High 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 45,900 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 (+3.2%) from 2024 to 2034.BLS Employment Projections 2024–34
  • Median annual pay is $38,540, across about 398,620 U.S. workers.BLS OEWS (May 2024)
  • Of the AI use actually observed for this work, 55% 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
Counter and Rental Clerks show 71st-percentile AI task overlap — and about 45,900 annual U.S. openings

• Counter and Rental Clerks rank in the 71st percentile (High 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 45,900 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 (+3.2%) from 2024 to 2034. (BLS Employment Projections 2024–34)
• Median annual pay is $38,540, across about 398,620 U.S. workers. (BLS OEWS (May 2024))
• Of the AI use actually observed for this work, 55% 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 — "Counter and Rental Clerks". https://singulariki.com/roles/role-41-2021-00
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. "Counter and Rental Clerks." 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; Frey & Osborne (2013) frey-osborne-automation; Dingel & Neiman (2020) dingel-neiman-workathome. Accessed June 7, 2026. https://singulariki.com/roles/role-41-2021-00

APA

Singulariki. (2026). Counter and Rental Clerks. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-41-2021-00

BibTeX 
@misc{singulariki-role-41-2021-00,
  title  = {Counter and Rental Clerks},
  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; Frey & Osborne (2013) frey-osborne-automation; Dingel & Neiman (2020) dingel-neiman-workathome. Accessed June 7, 2026},
  url    = {https://singulariki.com/roles/role-41-2021-00}
}

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

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