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.
- Read dials and gauges on panel control boards to ascertain temperatures, alkalinities, and densities of mixtures, and turn valves to obtain specified mixtures.70
- Weigh packages and adjust freezer air valves or switches on filler heads to obtain specified amounts of product in each container.70
- Start agitators to blend contents, or start beater, scraper, and expeller blades to mix contents with air and prevent sticking.70
- Stir material with spoons or paddles to mix ingredients or allow even cooling and prevent coagulation.70
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.
- Place or position containers into equipment, and remove containers after completion of cooling or freezing processes.01
- Sample and test product characteristics such as specific gravity, acidity, and sugar content, using hydrometers, pH meters, or refractometers.02
- Monitor pressure gauges, ammeters, flowmeters, thermometers, or products, and adjust controls to maintain specified conditions, such as feed rate, product consistency, temperature, air pressure, and machine speed.03
- Record temperatures, amounts of materials processed, or test results on report forms.04
- Measure or weigh specified amounts of ingredients or materials, and load them into tanks, vats, hoppers, or other equipment.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.
