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Transport & Logistics · Updated Aug 2026

Recycling and Reclamation Workers

Prepare and sort materials or products for recycling. Identify and remove hazardous substances. Dismantle components of products such as appliances.

JVS 2.0.0-phase4b
AI Exposure
53/100
Moderate

How much of this occupation’s work can be materially affected by current AI systems.

Replacement Risk
43/100
Moderate

How likely exposure is to translate into reduced human demand.

Includes provisional estimates for AI adoption pressure and labour-market resilience. How this is measured

Evidence quality
Confidence83/100
Task coverage89%

Confidence reflects task coverage, mapping and capability-evidence quality, and how much of the score rests on provisional inputs.

Task-level evidence

What is driving the score?

Occupation scores are built from the task mix—not a single prediction about a job title.

JVS 2.0.0-phase4b
TaskImportanceAI impactExposure
Collect and sort recyclable construction materials, such as concrete, drywall, plastics, or wood, into containers.High
73
Sort materials, such as metals, glass, wood, paper or plastics, into appropriate containers for recycling.High
68
Deposit recoverable materials into chutes or place materials on conveyor belts.High
68
Operate balers to compress recyclable materials into bundles or bales.High
66
Operate forklifts, pallet jacks, power lifts, or front-end loaders to load bales, bundles, or other heavy items onto trucks for shipping to smelters or other recycled materials processing facilities.High
65
Sort metals to separate high-grade metals, such as copper, brass, and aluminum, for recycling.Medium
68
Operate processing equipment, such as fiber-sorters and grinders, to sort, crush, or grind recyclable materials.Medium
63
Extract chemicals from discarded appliances, such as air conditioners or refrigerators, using specialized machinery, such as refrigerant recovery equipment.High
63
Clean, inspect, or lubricate recyclable collection equipment or perform routine maintenance or minor repairs on recycling equipment, such as star gears, finger sorters, destoners, belts, and grinders.Medium
33
Record logs of recycled materials or waste chemicals removed from products.Medium
24
Clean materials, such as metals, according to recycling requirements.High
19
Clean recycling yard by sweeping, raking, picking up broken glass and loose paper debris, or moving barrels and bins.High
19
Most exposed

Where AI can do more

Routine, digitized, and highly repeatable tasks face the greatest pressure.

  1. Collect and sort recyclable construction materials, such as concrete, drywall, plastics, or wood, into containers.73
  2. Sort materials, such as metals, glass, wood, paper or plastics, into appropriate containers for recycling.68
  3. Deposit recoverable materials into chutes or place materials on conveyor belts.68
  4. Sort metals to separate high-grade metals, such as copper, brass, and aluminum, for recycling.68
Hardest to automate

Where people still matter

These tasks score lowest on automation feasibility—physical presence, judgement, accountability and real-world variability all resist end-to-end automation.

  1. Clean materials, such as metals, according to recycling requirements.01
  2. Clean recycling yard by sweeping, raking, picking up broken glass and loose paper debris, or moving barrels and bins.02
  3. Record logs of recycled materials or waste chemicals removed from products.03
  4. Sort materials, such as metals, glass, wood, paper or plastics, into appropriate containers for recycling.04
  5. Deposit recoverable materials into chutes or place materials on conveyor belts.05
Where else this work leads

Related occupations

Occupations O*NET links to this one. Relatedness reflects shared work, not a claim that these roles are safer.

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AI risk 49

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Related work

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Beyond AI capability

Adoption and labour-market outlook

Structural factors are kept separate from raw capability so you can see what actually resists automation. Adoption pressure and labour-market resilience are still provisional models—25% of this occupation’s replacement-risk weight rests on them.

Human dependency60
Physical dependency64
Adoption pressure35
Labour-market resilience60
Methodology & sources

O*NET 30.3 occupational data interpreted through the JobsVsAI capability, automation and structural-constraint models.

Confidence83/100
CalculatedAug 21, 2026
Read methodology →