How much of this occupation’s work can be materially affected by current AI systems.
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
Confidence reflects task coverage, mapping and capability-evidence quality, and how much of the score rests on provisional inputs.
What is driving the score?
Occupation scores are built from the task mix—not a single prediction about a job title.
Where AI can do more
Routine, digitized, and highly repeatable tasks face the greatest pressure.
- Load, unload, or adjust materials or products on conveyors by hand, by using lifts, hoists, and scoops, or by opening gates, chutes, or hoppers.69
- Position deflector bars, gates, chutes, or spouts to divert flow of materials from one conveyor onto another conveyor.69
- Record production data such as weights, types, quantities, and storage locations of materials, as well as equipment performance problems and downtime.68
- Weigh or measure materials and products, using scales or other measuring instruments, or read scales on conveyors that continually weigh products, to verify specified tonnages and prevent overloads.68
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.
- Observe packages moving along conveyors to identify packages, detect defective packaging, and perform quality control.01
- Observe conveyor operations and monitor lights, dials, and gauges to maintain specified operating levels and to detect equipment malfunctions.02
- Stop equipment or machinery and clear jams, using poles, bars, and hand tools, or remove damaged materials from conveyors.03
- Load, unload, or adjust materials or products on conveyors by hand, by using lifts, hoists, and scoops, or by opening gates, chutes, or hoppers.04
- Record production data such as weights, types, quantities, and storage locations of materials, as well as equipment performance problems and downtime.05
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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Compare these careers →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.
O*NET 30.3 occupational data interpreted through the JobsVsAI capability, automation and structural-constraint models.
