Medium AI Risk Average

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.

AI Exposure Score
20% Medium

Proportion of tasks susceptible to AI automation (O*NET analysis)

Projected Growth
+3.9%
2024–2034 (BLS)
+16,000 jobs
Median Annual Wage
$35,270
BLS May 2024
How wage figures are sourced →
The verdict

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.

20%
AI exposure
6th
percentile
+3.9%
Job growth 2024–34
$35,270
Median wage

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.

AI exposure distribution - Cleaners of vehicles and equipment marked 1 occupations at 0–10% 1 0 43 occupations at 10–20% 43 10 184 occupations at 20–30% 184 20 332 occupations at 30–40% 332 30 158 occupations at 40–50% 158 40 64 occupations at 50–60% 64 50 29 occupations at 60–70% 29 60 15 occupations at 70–80% 15 70 5 occupations at 80–90% 5 80 1 occupations at 90–100% 1 90 AI exposure (%) →
Top 94% by AI exposure Higher AI exposure than 6% of all 832 occupations.

Cleaners of vehicles and equipment has ai exposure of 20%. Distribution: 1 occupations at 0-10%; 43 occupations at 10-20%; 184 occupations at 20-30%; 332 occupations at 30-40%; 158 occupations at 40-50%; 64 occupations at 50-60%; 29 occupations at 60-70%; 15 occupations at 70-80%; 5 occupations at 80-90%; 1 occupations at 90-100%.

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.

Future-proofGrowing but exposedStable, lower-AIMost at risk18.9%25.2%31.5%37.8%44.1%-6.1%-2.2%1.7%5.6%9.5%AI exposure (%) →Projected growth (%) →LaborersStockersHeavyLight truck driversIndustrial truckFirst-line supervisoPackersDriver/sales workersCleaners of vehiclesBus driversShuttle drivers

Source: BLS Employment Projections 2024–2034 (growth) and O*NET (AI-exposure analysis by PlainWorkforce).

Employment Projections

410,100
Employment 2024
426,200
Projected 2034
+3.9%
Change (%)
+16,000
Change (jobs)

Occupation Insight

Cleaners of vehicles and equipment (SOC 53-7061) carries an AI exposure score of 20%, placing it in the Medium automation-risk tier. This score is computed from O*NET Database 30.0 task-level analysis, where each task an 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 economic context matters alongside the risk score. BLS counted approximately 410,100 workers in this occupation in 2024, and projects a +3.9% change through 2034 - modest growth that keeps the occupation viable even as tasks evolve. Median annual compensation stands at $35,270, reflecting both skill scarcity and the value employers place on the tasks that remain difficult to automate. Entry typically requires No formal educational credential, plus None of related experience.

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. Pair the AI exposure score with the BLS employment projection and wage percentiles above for a complete career assessment.

Education & Entry Requirements

Typical Education
No formal educational credential
Work Experience
None
On-the-Job Training
Short-term on-the-job training

Top Tasks (O*NET)

  1. 1. Rinse objects and place them on drying racks or use cloth, squeegees, or air compressors to dry surfaces.
  2. 2. Apply paints, dyes, polishes, reconditioners, waxes, or masking materials to vehicles to preserve, protect, or restore color or condition.
  3. 3. Clean and polish vehicle windows.
  4. 4. Drive vehicles to or from workshops or customers' workplaces or homes.
  5. 5. Scrub, scrape, or spray machine parts, equipment, or vehicles, using scrapers, brushes, clothes, cleaners, disinfectants, insecticides, acid, abrasives, vacuums, or hoses.
  6. 6. Clean the plastic work inside cars, using paintbrushes.
  7. 7. Inspect parts, equipment, or vehicles for cleanliness, damage, and compliance with standards or regulations.
  8. 8. Mix cleaning solutions, abrasive compositions, or other compounds, according to formulas.
  9. 9. Disassemble and reassemble machines or equipment or remove and reattach vehicle parts or trim, using hand tools.
  10. 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

1.0
out of 5.0

Medium automation risk based on 10 analyzed tasks. Most tasks require human judgment and are resistant to automation.

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).

Data sourced from official public datasets. See our methodology for details. Retrieved and formatted by PlainWorkforce Editorial

Every figure on PlainWorkforce is rendered directly from BLS/O*NET source data, no number is typed in by an editor. See our editorial standards & corrections policy, the methodology behind these figures, or report a data error. Data current as of BLS Employment Projections 2024-2034.