Cleaners of vehicles and equipment
SOC Code: 53-7061
Cleaners of vehicles and equipment carries a 20% AI exposure score (Medium automation risk), with a median annual wage of $35,270 and +3.9% projected employment growth from 2024 to 2034 (BLS), affecting approximately 410,100 workers. Full task breakdown, skills, and employer data are below.
Proportion of tasks susceptible to AI automation (O*NET analysis)
At 20% AI exposure, Cleaners of vehicles and equipment sits 17 points below the 37.2% average across 832 U.S. occupations - more exposed than 6% of them. It ranks among the more AI-resilient roles in the dataset.
Career outlook score
53/100
Cleaners of vehicles and equipment, weighted across 3 of 3 tracked dimensions
A weighted composite of median wage, projected growth, and AI-automation security (inverted exposure), each benchmarked against every other tracked occupation. It describes this occupation's standing across those three dimensions, not a guarantee of future outcomes.
- Median wage F $35,270
Annual median wage, percentile rank vs all tracked occupations
- Projected growth B- +3.9%
Projected employment change, 2024-2034, BLS Employment Projections
- AI exposure (inverted) A+ 20% exposure
Lower O*NET task-automability scores lower risk; this dimension scores security, not exposure
Home health and personal care aides is #1 of 832 occupations by employment (4.3M, AI exposure rank #392 at 35%) vs. Bookkeeping, accounting, and auditing clerks #1 by AI task exposure (95%, employment rank #17 at 1.6M).
Automation-risk inventory
Exclusive cut of 832 occupations by PlainWorkforce automation-risk band. Orthogonal to the continuous AI-exposure distribution chart below and to this occupation's single risk badge, this is the corpus band mix, with Cleaners of vehicles and equipment in the Medium band.
Credential × growth standing
Open entry with non-declining BLS pace
Cleaners of vehicles and equipment keeps an No credential bar (109 of 832) and sits in Average (378 of 832). Lower formal gates with a non-shrinking employment line - skill and AI desks matter more than credentials here.
Where Cleaners of vehicles and equipment sits among all occupations
AI-exposure score distribution across 832 U.S. occupations (O*NET task analysis). This occupation is marked in rose.
Where Cleaners of vehicles and equipment sits by AI exposure
AI-exposure score distribution across U.S. occupations (O*NET task analysis)
20% Among the lowest lower than 94% of 832 occupations
Occupations, banded by AI-exposure score
Each bar is a band; taller bars hold more occupations. The dashed line + filled bar mark this entry. Hover or tap any bar for its full count and share, and where it sits relative to this entry.
Source O*NET task data (U.S. Department of Labor) · BLS 2024–2034
Source: O*NET task data (U.S. Department of Labor); AI-exposure scores are PlainWorkforce's analysis. As of BLS 2024–2034.
Cleaners of vehicles and equipment vs. its occupational neighbors
AI exposure (horizontal) vs projected 2024–2034 growth (vertical) for occupations in the same SOC group. Cleaners of vehicles and equipment is marked in rose; the top-left corner is the most future-proof.
Source: BLS Employment Projections 2024–2034 (growth) and O*NET (AI-exposure analysis by PlainWorkforce).
Employment Projections
Where This Score Comes From
Cleaners of vehicles and equipment's Medium automation-risk tier is computed from O*NET Database 30.0 task-level analysis, where each documented task the occupation performs is evaluated against current generative AI, robotic process automation, and machine-learning capabilities. A score below 40% reflects tasks anchored in physical dexterity, unstructured environments, or high-touch human interaction that current AI cannot reliably replicate.
The employment, wage, and education figures above come from a second, separate federal source: BLS Employment Projections 2024–2034, matched to the O*NET task data by Standard Occupational Classification (SOC 53-7061) code, with the wage figure cross-validated against the BLS Occupational Employment and Wage Statistics (OEWS) May 2024 survey. BLS figures are presented exactly as published, with no adjustment on our part; the SOC-code match is what lets Cleaners of vehicles and equipment be compared directly against every other tracked occupation on the same basis, not just roles that happen to share a job title.
For career planners, this profile should be read alongside the task, skill, and knowledge breakdowns below and the list of employers whose workforce composition includes Cleaners of vehicles and equipment. Adjacent occupations shown further down offer lateral moves that preserve industry knowledge while potentially reducing exposure.
Education & Entry Requirements
Top Tasks (O*NET)
- 1. Rinse objects and place them on drying racks or use cloth, squeegees, or air compressors to dry surfaces.
- 2. Apply paints, dyes, polishes, reconditioners, waxes, or masking materials to vehicles to preserve, protect, or restore color or condition.
- 3. Clean and polish vehicle windows.
- 4. Drive vehicles to or from workshops or customers' workplaces or homes.
- 5. Scrub, scrape, or spray machine parts, equipment, or vehicles, using scrapers, brushes, clothes, cleaners, disinfectants, insecticides, acid, abrasives, vacuums, or hoses.
- 6. Clean the plastic work inside cars, using paintbrushes.
- 7. Inspect parts, equipment, or vehicles for cleanliness, damage, and compliance with standards or regulations.
- 8. Mix cleaning solutions, abrasive compositions, or other compounds, according to formulas.
- 9. Disassemble and reassemble machines or equipment or remove and reattach vehicle parts or trim, using hand tools.
- 10. Maintain inventories of supplies.
Key Skills Required
- Operation and Control
- Quality Control Analysis
- Operations Monitoring
- Monitoring
- Time Management
- Speaking
- Active Listening
- Service Orientation
- Reading Comprehension
- Critical Thinking
Knowledge Areas
- Customer and Personal Service
- English Language
- Transportation
- Administration and Management
- Public Safety and Security
- Production and Processing
- Mechanical
- Education and Training
- Mathematics
- Chemistry
Frequently Asked Questions
Will AI replace Cleaners of vehicles and equipment?
Cleaners of vehicles and equipment has an AI exposure score of 20%, indicating a medium level of automation risk. The majority of tasks in this role require human judgment, creativity, or physical presence that AI cannot easily replicate.
What is the job outlook for Cleaners of vehicles and equipment?
According to BLS Employment Projections 2024-2034, Cleaners of vehicles and equipment is projected to grow by 3.9% over the decade. Current employment stands at approximately 410,100 workers.
What skills are needed for Cleaners of vehicles and equipment?
Key skills for Cleaners of vehicles and equipment include Operation and Control, Quality Control Analysis, Operations Monitoring, and others. Typical entry-level education is No formal educational credential.
How much do Cleaners of vehicles and equipment earn?
The median annual wage for Cleaners of vehicles and equipment is $35,270, according to BLS Occupational Employment and Wage Statistics (May 2024). Actual earnings vary by location, experience, industry, and employer. The BLS publishes detailed wage percentiles by region in its Occupational Employment and Wage Statistics program.
What education is required for Cleaners of vehicles and equipment?
The typical entry-level education for Cleaners of vehicles and equipment is No formal educational credential. Employers generally expect None of related work experience. On-the-job training typically involves Short-term on-the-job training. Requirements can vary by employer and specialization.
Which companies employ Cleaners of vehicles and equipment?
Cleaners of vehicles and equipment roles exist across many industries and employers. Workforce composition is estimated from BLS industry-occupation employment distributions matched to SEC-registered public companies.
AI Exposure Rating
Medium automation risk based on 10 analyzed tasks. Most tasks require human judgment and are resistant to automation.
Nationwide occupations with similar workforce profiles
Two data-derived peer sets for Cleaners of vehicles and equipment: AI-exposure neighbors and BLS 2034 growth neighbors (distinct comparison neighborhoods, cross-occupation).
Similar AI exposure score
Nearest O*NET task-automability scores nationwide (20% here).
- Bicycle repairers · AI exposure 20%
- Lighting technicians · AI exposure 20%
- Maintenance and repair workers, general · AI exposure 20%
- Animal caretakers · AI exposure 19%
Similar projected growth (2024–2034)
Nearest BLS employment change rates nationwide (+3.9% here).
- Airline pilots, copilots, and flight engineers · growth +3.9%
- Animal control workers · growth +3.9%
- Architects, except landscape and naval · growth +3.9%
- Environmental engineers · growth +3.9%
Peers are nearest-neighbor matches on published BLS + O*NET metrics among occupations with ≥10,000 workers in 2024; corpus ranks above sort the full tracked set.
Related Occupations
Showing 6 of 28 occupations with a comparable automation-risk profile.
What to do with this
Use Cleaners of vehicles and equipment's numbers above to compare, not just read in isolation.
- Compare Cleaners of vehicles and equipment side by side against another occupation on wage, growth, and AI exposure. Workforce comparison tool
- Understand how the AI exposure score above is actually calculated before treating it as a verdict. Reading AI exposure scores
- See the full ranked list of occupations with the lowest automation exposure nationwide. Safest occupations from AI
AI exposure scores estimate task automatability from O*NET data; they are not a certainty of job loss, and BLS growth projections are estimates, not guarantees.
Data sources: Bureau of Labor Statistics Employment Projections 2024–2034 and O*NET Database 30.0. Employment figures are rounded. Wage data from BLS Occupational Employment Statistics (OES).