Medium AI Risk Slow Growth

Refuse and recyclable material collectors

SOC Code: 53-7081

Refuse and recyclable material collectors carries a 38% AI exposure score (Medium automation risk), with a median annual wage of $48,350 and +0.9% projected employment growth from 2024 to 2034 (BLS), affecting approximately 147,900 workers. Full task breakdown, skills, and employer data are below.

AI Exposure Score
38% Medium

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

Projected Growth
+0.9%
2024–2034 (BLS)
+1,300 jobs
Median Annual Wage
$48,350
BLS May 2024
How wage figures are sourced →
The verdict

At 38% AI exposure, Refuse and recyclable material collectors sits 1 points above the 37.2% average across 832 U.S. occupations - more exposed than 63% of them. Most of its core tasks still require human judgment.

38%
AI exposure
Top 37%
most exposed
+0.9%
Job growth 2024–34
$48,350
Median wage

Where Refuse and recyclable material collectors 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 - Refuse and recyclable material collectors 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 37% by AI exposure Higher AI exposure than 63% of all 832 occupations.

Refuse and recyclable material collectors has ai exposure of 38%. 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.

Refuse and recyclable material collectors vs. its occupational neighbors

AI exposure (horizontal) vs projected 2024–2034 growth (vertical) for occupations in the same SOC group. Refuse and recyclable material collectors 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 (%) →RefuseLaborersStockersHeavyLight 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

147,900
Employment 2024
149,200
Projected 2034
+0.9%
Change (%)
+1,300
Change (jobs)

Occupation Insight

Refuse and recyclable material collectors (SOC 53-7081) carries an AI exposure score of 38%, 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 147,900 workers in this occupation in 2024, and projects a +0.9% change through 2034 - modest growth that keeps the occupation viable even as tasks evolve. Median annual compensation stands at $48,350, 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 Refuse and recyclable material collectors. 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. Inspect trucks prior to beginning routes to ensure safe operating condition.
  2. 2. Drive trucks, following established routes, through residential streets or alleys or through business or industrial areas.
  3. 3. Refuel trucks or add other fluids, such as oil or brake fluid.
  4. 4. Dump refuse or recyclable materials at disposal sites.
  5. 5. Fill out defective equipment reports.
  6. 6. Operate automated or semi-automated hoisting devices that raise refuse bins and dump contents into openings in truck bodies.
  7. 7. Dismount garbage trucks to collect garbage and remount trucks to ride to the next collection point.
  8. 8. Operate equipment that compresses collected refuse.
  9. 9. Communicate with dispatchers concerning delays, unsafe sites, accidents, equipment breakdowns, or other maintenance problems.
  10. 10. Check road or weather conditions to determine how routes will be affected.

Key Skills Required

  • Operations Monitoring
  • Operation and Control
  • Active Listening
  • Speaking
  • Critical Thinking
  • Equipment Maintenance
  • Reading Comprehension
  • Coordination
  • Writing
  • Monitoring

Knowledge Areas

  • Mechanical
  • English Language
  • Transportation
  • Customer and Personal Service
  • Public Safety and Security
  • Administration and Management
  • Telecommunications
  • Computers and Electronics
  • Mathematics
  • Education and Training

Frequently Asked Questions

Will AI replace Refuse and recyclable material collectors?

Refuse and recyclable material collectors has an AI exposure score of 38%, 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 Refuse and recyclable material collectors?

According to BLS Employment Projections 2024-2034, Refuse and recyclable material collectors is projected to grow by 0.9% over the decade. Current employment stands at approximately 147,900 workers.

What skills are needed for Refuse and recyclable material collectors?

Key skills for Refuse and recyclable material collectors include Operations Monitoring, Operation and Control, Active Listening, and others. Typical entry-level education is No formal educational credential.

How much do Refuse and recyclable material collectors earn?

The median annual wage for Refuse and recyclable material collectors is $48,350, 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 Refuse and recyclable material collectors?

The typical entry-level education for Refuse and recyclable material collectors 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 Refuse and recyclable material collectors?

Refuse and recyclable material collectors 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

1.9
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.