Often handed to AI
Task areas most often handled directively in observed AI conversations — candidates to delegate with light review.
- Provide customers with information about local roads or highways. · 0.4%
Automotive and Watercraft Service Attendants
Occupation · SOC 53-6031.00
Service automobiles, buses, trucks, boats, and other automotive or marine vehicles with fuel, lubricants, and accessories. Collect payment for services and supplies. May lubricate vehicle, change motor oil, refill antifreeze, or replace lights or other accessories, such as windshield wiper blades or fan belts. May repair or replace tires.
Also called: Attendant · Fuel Dock Attendant · Gas Attendant · Service Station Attendant · Dock Attendant · Dock Hand · Fuel Attendant · Gas Pumper · Marine Fuel Dock Attendant · Auto Garage Attendant · Auto Self Service Station Attendant · Auto Service Station Attendant
Job family: Transportation and Material Moving Occupations
Take this to your AI
A source-stamped Markdown brief of this occupation — paste it into an agent, or fetch
/roles/role-53-6031-00/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.
- Test and charge batteries. · 0.5%
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.
- Provide customers with information about local roads or highways. · 100.0% need a human
- Check air pressure in vehicle tires; and levels of fuel, motor oil, transmission, radiator, battery, and other fluids; and add air, oil, water, or other fluids, as required. · 100.0% need a human
- Test and charge batteries. · 87.2% 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 (-1.0% by 2034)
- 14,400 openings/yr
- Low AI exposure
- Observed AI use leans augmentation
- Median pay $34,850/yr
- Work is mostly on-site (not teleworkable)
- 2013 flagged this for computerization (68th); today's AI task-overlap is comparatively low (8th)
8th-percentile task overlap — yet about 14,400 openings a year (-1% projected, BLS), and observed AI use leans 2231% 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.) Low | 10th | -1.2 | |
| LLM task exposure, γ (OpenAI / Eloundou) Low | 18th | 0.1 | |
| AI assistant applicability (Microsoft) Low | 9th | 0.0 |
OpenAI's exposure study scores tasks three ways: with a language model alone (α 0.1), with simple added tooling (β 0.1), and including AI-powered software (γ 0.1). 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.
Mixed signals. Today's AI/LLM studies show relatively low exposure for this job, but the older (2013) Frey–Osborne work rated it higher for computerization and robotics. Different eras, different technologies — the AI measures above reflect the current state.
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 0.8 · 68th 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.
| Test and charge batteries. | 1.0% |
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 · -1.0% by 2034 |
| Projected annual openings | 14,400 |
| Employment 2024 → 2034 | 100,000 → 99,000 |
“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.
Automotive and Watercraft Service Attendants sits at the 44th 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.
24% mean task exposure (2025)
44th percentile of 427 placed occupations
−3 pts shift 2023 → 2025
| International occupation (ISCO-08) | Task exposure (2025) | Most tasks fall in |
|---|---|---|
| Service Station Attendants · 5245 | 24% | Minimal |
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 | 22.3% working with AI · 15.4% 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 |
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 |
|---|---|---|
| Test and charge batteries. | Learning | 0.5% |
| Provide customers with information about local roads or highways. | Directive | 0.4% |
| Check air pressure in vehicle tires; and levels of fuel, motor oil, transmission, radiator, battery, and other fluids; and add air, oil, water, or other fluids, as required. | — | 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.
| Provide customers with information about local roads or highways. | 100.0% | |
| Check air pressure in vehicle tires; and levels of fuel, motor oil, transmission, radiator, battery, and other fluids; and add air, oil, water, or other fluids, as required. | 100.0% | |
| Test and charge batteries. | 87.2% |
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 test and charge batteries.From: Test and charge batteries. · 0.5% of measured AI use · learning
-
Help me provide customers with information about local roads or highways.From: Provide customers with information about local roads or highways. · 0.4% of measured AI use · directive
-
Help me check air pressure in vehicle tires; and levels of fuel, motor oil, transmission, radiator, battery, and other fluids; and add air, oil, water, or other fluids, as required.From: Check air pressure in vehicle tires; and levels of fuel, motor oil, transmission, radiator, battery, and other fluids; and add air, oil, water, or other fluids, as required. · 0.4% of measured AI use
Tasks
All 15 tasks O*NET lists for this occupation, ordered by importance. Each links to its own page with AI-exposure and observed-use detail.
- Collect cash payments from customers, and make change or charge purchases to customers' credit cards, providing customers with receipts. Core · importance 4.7
- Check tire pressure and levels of fuel, motor oil, transmission, radiator, battery, or other fluids, adding air or fluids as required. Core · importance 4.2
- Prepare daily reports of fuel, oil, and accessory sales. Supplemental · importance 4.2
- Clean windshields. Supplemental · importance 4.2
- Perform minor repairs, such as adjusting brakes, replacing spark plugs, or changing engine oil or filters. Core · importance 4.2
- Clean parking areas, offices, restrooms, or equipment, and remove trash. Core · importance 4.1
- Order stock, and price and shelve incoming goods. Core · importance 4.0
- Activate fuel pumps and fill fuel tanks of vehicles with gasoline or diesel fuel to specified levels. Supplemental · importance 4.0
- Sell and install accessories, such as batteries, windshield wiper blades, fan belts, bulbs, or headlamps. Core · importance 3.9
- Grease and lubricate vehicles or specified units, such as springs, universal joints, or steering knuckles, using grease guns or spray lubricants. Core · importance 3.9
- Test and charge batteries. Supplemental · importance 3.8
- Rotate, test, and repair or replace tires. Core · importance 3.8
- Maintain customer records and follow up periodically with telephone, mail, or personal reminders of services due. Supplemental · importance 3.7
- Provide customers with information about local roads or highways. Supplemental · importance 2.4
- Operate car washes. Supplemental
Work activities
- Collect fares or payment from customers.
- Control pumps or pumping equipment.
- Record sales or transactions data.
- Clean facilities or work areas.
- Clean machinery or equipment.
- Provide transportation information to passengers or customers.
- Maintain vehicles in good working condition.
- Acquire supplies or equipment.
- Maintain watercraft engines or machinery.
- Install parts, assemblies, or attachments in transportation or material handling equipment.
- Sell products or services.
- Inspect motor vehicles.
- Measure the level or depth of water or other liquids.
- Clean vehicles or vehicle components.
Knowledge, skills & abilities
O*NET importance rating, from 1 (not important) to 5 (extremely important).
Knowledge
| Customer and Personal Service | 4.6 | |
| Mechanical | 4.4 | |
| Sales and Marketing | 4.0 | |
| Administration and Management | 3.8 | |
| Mathematics | 3.3 | |
| Administrative | 3.0 | |
| Engineering and Technology | 3.0 | |
| Education and Training | 3.0 | |
| Chemistry | 2.9 | |
| Computers and Electronics | 2.9 |
Abilities
| Oral Comprehension | 3.4 | |
| Oral Expression | 3.4 | |
| Manual Dexterity | 3.3 | |
| Finger Dexterity | 3.3 | |
| Control Precision | 3.3 | |
| Trunk Strength | 3.3 | |
| Near Vision | 3.3 | |
| Deductive Reasoning | 3.1 | |
| Information Ordering | 3.1 | |
| Arm-Hand Steadiness | 3.1 | |
| Multilimb Coordination | 3.1 | |
| Static Strength | 3.1 | |
| Stamina | 3.1 | |
| Extent Flexibility | 3.1 | |
| Speech Recognition | 3.1 | |
| Problem Sensitivity | 3.0 | |
| Visualization | 3.0 | |
| Far Vision | 3.0 | |
| Speech Clarity | 3.0 |
Essential skills
| Active Listening | 3.1 | |
| Speaking | 3.1 | |
| Critical Thinking | 3.0 |
Transferable skills
| Service Orientation | 3.1 | |
| Operation and Control | 3.1 | |
| Time Management | 3.1 | |
| Coordination | 3.0 | |
| Complex Problem Solving | 3.0 | |
| Equipment Maintenance | 3.0 | |
| Repairing | 3.0 | |
| Judgment and Decision Making | 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 | |
|---|---|---|
| Apple Safari | Internet browser software | Hot technology In demand |
| Microsoft Edge | Internet browser software | Hot technology In demand |
| Mozilla Firefox | Internet browser software | Hot technology In demand |
| Microsoft Excel | Spreadsheet software | Hot technology |
| Microsoft Outlook | Electronic mail software | Hot technology |
| Microsoft Windows | Operating system software | Hot technology |
| Web browser software | Internet browser software | In demand |
| Inventory management systems | Inventory management software | |
| Software libraries | Development environment software | |
| Timekeeping software | Time accounting 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.
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 | 58.6% | |
| Post-Secondary Certificate | 22.6% | |
| Less than a High School Diploma | 16.3% | |
| Some College Courses | 2.4% |
Interests & work styles
The interests and personal qualities O*NET associates with people who do this work.
Career interests (Holland / RIASEC)
| Realistic | 6.4 | |
| Conventional | 4.4 | |
| Enterprising | 2.1 | |
| Social | 2.0 |
Interest areas
| Physical/Manual Labor | 4.8 | |
| Mechanics/Electronics | 4.5 | |
| Transportation/Machine Operation | 2.8 | |
| Engineering | 2.2 | |
| Sales | 2.2 | |
| Personal Service | 1.9 | |
| Accounting | 1.7 | |
| Construction/Woodwork | 1.4 |
Work styles
| Dependability | 2.1 | |
| Attention to Detail | 1.7 | |
| Cautiousness | 1.4 | |
| Integrity | 1.4 |
Wages & employment
U.S. · annual wages (BLS OEWS)
| 10th percentile | $27,870 |
| 25th percentile | $30,600 |
| Median (50th) | $34,850 |
| 75th percentile | $38,430 |
| 90th percentile | $45,240 |
| People employed | 98,270 |
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 | 49,550 | $34,980 |
| Other Services (except Public Administration) · Sector | 39,810 | $34,450 |
| Arts, Entertainment, and Recreation · Sector | 2,080 | $36,830 |
| Real Estate and Rental and Leasing · Sector | 1,760 | $31,740 |
| Transportation and Warehousing · Sector | 1,280 | $40,080 |
| Wholesale Trade · Sector | 940 | $34,500 |
| Administrative and Support and Waste Management and Remediation Services · Sector | 920 | $36,770 |
| Temporary Help Services · National industry | 250 | $32,510 |
| Construction · Sector | 170 | $53,810 |
| Accommodation and Food Services · Sector | 110 | $31,790 |
| Educational Services · Sector | 70 | $47,410 |
| Management of Companies and Enterprises · Sector | 50 | $36,260 |
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 |
|---|---|---|
| Other Services (except Public Administration) · Sector | 14.11× | 39,810 |
| Retail Trade · Sector | 4.99× | 49,550 |
| Arts, Entertainment, and Recreation · Sector | 1.24× | 2,080 |
| Real Estate and Rental and Leasing · Sector | 1.17× | 1,760 |
| Transportation and Warehousing · Sector | 0.27× | 1,280 |
| Wholesale Trade · Sector | 0.24× | 940 |
| Administrative and Support and Waste Management and Remediation Services · Sector | 0.16× | 920 |
| Temporary Help Services · National industry | 0.15× | 250 |
Related occupations
Part of the Supply Chain & Transportation career cluster.
- Automotive Service Technicians and Mechanics · 49-3023.00 Compare →
- Pump Operators, Except Wellhead Pumpers · 53-7072.00 Compare →
- Maintenance Workers, Machinery · 49-9043.00 Compare →
- Cleaners of Vehicles and Equipment · 53-7061.00 Compare →
- Home Appliance Repairers · 49-9031.00 Compare →
- Bus and Truck Mechanics and Diesel Engine Specialists · 49-3031.00 Compare →
- Rail Car Repairers · 49-3043.00 Compare →
- Aircraft Service Attendants · 53-6032.00 Compare →
- Control and Valve Installers and Repairers, Except Mechanical Door · 49-9012.00 Compare →
- Stationary Engineers and Boiler Operators · 51-8021.00 Compare →
- Roustabouts, Oil and Gas · 47-5071.00 Compare →
- Tire Repairers and Changers · 49-3093.00 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 Automotive and Watercraft Service Attendants — 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 44th percentile of 427 international occupations.
Write a report on thisheadline · factoids · citation
Automotive and Watercraft Service Attendants show 8th-percentile AI task overlap — and about 14,400 annual U.S. openings
- Automotive and Watercraft Service Attendants rank in the 8th percentile (Low 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 14,400 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 (-1%) from 2024 to 2034.BLS Employment Projections 2024–34
- Median annual pay is $34,850, across about 98,270 U.S. workers.BLS OEWS (May 2024)
- Of the AI use actually observed for this work, 22% 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
Automotive and Watercraft Service Attendants show 8th-percentile AI task overlap — and about 14,400 annual U.S. openings • Automotive and Watercraft Service Attendants rank in the 8th percentile (Low 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 14,400 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 (-1%) from 2024 to 2034. (BLS Employment Projections 2024–34) • Median annual pay is $34,850, across about 98,270 U.S. workers. (BLS OEWS (May 2024)) • Of the AI use actually observed for this work, 22% 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 — "Automotive and Watercraft Service Attendants". https://singulariki.com/roles/role-53-6031-00 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. "Automotive and Watercraft Service Attendants." 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-53-6031-00
APA
Singulariki. (2026). Automotive and Watercraft Service Attendants. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-53-6031-00
BibTeX
@misc{singulariki-role-53-6031-00,
title = {Automotive and Watercraft Service Attendants},
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-53-6031-00}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.