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.
- Push racks or carts to transfer products to storage, cooling stations, or the next stage of processing.75
- Smooth out products in bins, pans, trays, or conveyors, using rakes or shovels.75
- Record production data, such as weight and amount of product processed, type of product, and time and temperature of processing.74
- Weigh or measure products, using scale hoppers or scale conveyors.74
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.
- Start conveyors to move roasted grain to cooling pans and agitate grain with rakes as blowers force air through perforated bottoms of pans.01
- Install equipment, such as spray units, cutting blades, or screens, using hand tools.02
- Open valves, gates, or chutes or use shovels to load or remove products from ovens or other equipment.03
- Fill or remove product from trays, carts, hoppers, or equipment, using scoops, peels, or shovels, or by hand.04
- Observe, feel, taste, or otherwise examine products during and after processing to ensure conformance to standards.05
Related occupations
Occupations O*NET links to this one. Relatedness reflects shared work, not a claim that these roles are safer.
Food Cooking Machine Operators and Tenders
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Compare these careers →Cooling and Freezing Equipment Operators and Tenders
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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.
