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.
- Notify or signal other workers to operate equipment or when processing is complete.70
- Read work orders, recipes, or formulas to determine cooking times and temperatures, and ingredient specifications.69
- Measure or weigh ingredients, using scales or measuring containers.69
- Record production and test data, such as processing steps, temperature and steam readings, cooking time, batches processed, and test results.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.
- Clean, wash, and sterilize equipment and cooking area, using water hoses, cleaning or sterilizing solutions, or rinses.01
- Collect and examine product samples during production to test them for quality, color, content, consistency, viscosity, acidity, or specific gravity.02
- Observe gauges, dials, and product characteristics, and adjust controls to maintain appropriate temperature, pressure, and flow of ingredients.03
- Place products on conveyors or carts, and monitor product flow.04
- Read work orders, recipes, or formulas to determine cooking times and temperatures, and ingredient specifications.05
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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.
