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.
- Inventory and record quantities of materials and finished products, requisitioning additional supplies as necessary.70
- Trim excess material from parts, using knives, and grind scrap plastic into powder for reuse.69
- Unload finished products from conveyor belts, pack them in containers, and place containers in warehouses.69
- Spray, smoke, or coat molds with compounds to lubricate or insulate molds, using acetylene torches or sprayers.69
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.
- Adjust equipment and workpiece holding fixtures, such as mold frames, tubs, and cutting tables, to ensure proper functioning.01
- Smooth and clean inner surfaces of molds, using brushes, scrapers, air hoses, or grinding wheels, and fill imperfections with refractory material.02
- Remove finished or cured products from dies or molds, using hand tools, air hoses, and other equipment, stamping identifying information on products when necessary.03
- Install dies onto machines or presses and coat dies with parting agents, according to work order specifications.04
- Obtain and move specified patterns to work stations, manually or using hoists, and secure patterns to machines, using wrenches.05
Related occupations
Occupations O*NET links to this one. Relatedness reflects shared work, not a claim that these roles are safer.
Extruding and Forming Machine Setters, Operators, and Tenders, Synthetic and Glass Fibers
Closely related work
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Closely related work
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Closely related work
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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.
