AI exposure: Food Cooking Machine Operators and Tenders
Operate or tend cooking equipment, such as steam cooking vats, deep fry cookers, pressure cookers, kettles, and boilers, to prepare food products.
Reading this score
computedAt 19.0% of weighted task load, Food Cooking Machine Operators and Tenders sits at the 33th percentile, below the point where a job's centre of gravity has moved. 71.2% of what this role does is untouched, meaning current systems cannot produce that work at all, whatever the commercial incentive.
What holds the line here is embodiment. Across this occupation's 17 tasks it averages 2.51 out of 3, the highest of the five friction dimensions. In plain terms, the work has to happen in physical space. A language model cannot move matter. Until the robotics to do this work is both good enough and cheap enough to deploy widely, capability in software does not reach it.
The most exposed thing this job does is Record production and test data, at 73.3%. The least is Place products on conveyors or carts, and monitor product flow, at 0.0%. A gap of 73.3% between two parts of the same job is the reason this index publishes at task level. An occupation-wide number would have hidden both.
Within production occupations, this one is more exposed than most. The median across the 107 roles in the group is 16.1%, and only 36 of them score higher than this. Occupational families are not uniform, and the spread inside them is often wider than the gap between them.
What would move this score. Of 17 tasks, 6 are currently banded exposed, 0 assisted and 11 untouched. For that distribution to shift materially would take robotics cheap and reliable enough to deploy at scale, not a better language model. The score is re-computed every quarter against a fresh capability reference, and the change is published rather than quietly applied.
Where the score comes from
judgedEvery task is scored through the standardised work activities it maps to. These are this occupation’s averages on the six rubric dimensions. Capability is what AI can do; the other five are what stands in the way.
| Dimension | Mean | Scale |
|---|---|---|
| Capability | 1.13 | 0-4 |
| Embodiment | 2.51 | 0-3 |
| Presence | 0.59 | 0-3 |
| Accountability | 0.48 | 0-3 |
| Context | 0.96 | 0-3 |
| Verification cost | 0.97 | 0-3 |
Task by task
17 tasks, O*NET 31.0| Task | Exposed | Assisted | Untouched | Importance | Band |
|---|---|---|---|---|---|
| Record production and test data, such as processing steps, temperature and steam readings, cooking time, batches processed, and test results. | 73.3% | 26.7% | 0.0% | 4.45 | exposed |
| Read work orders, recipes, or formulas to determine cooking times and temperatures, and ingredient specifications. | 41.7% | 20.8% | 37.5% | 4.61 | exposed |
| Observe gauges, dials, and product characteristics, and adjust controls to maintain appropriate temperature, pressure, and flow of ingredients. | 39.6% | 22.9% | 37.5% | 4.56 | exposed |
| Set temperature, pressure, and time controls, and start conveyers, machines, or pumps. | 33.3% | 16.7% | 50.0% | 4.41 | exposed |
| Turn valves or start pumps to add ingredients or drain products from equipment and to transfer products for storage, cooling, or further processing. | 33.3% | 16.7% | 50.0% | 4.23 | exposed |
| Admit required amounts of water, steam, cooking oils, or compressed air into equipment, such as by opening water valves to cool mixtures to the desired consistency. | 33.3% | 16.7% | 50.0% | 4.21 | exposed |
| Listen for malfunction alarms, and shut down equipment and notify supervisors when necessary. | 23.2% | 18.5% | 58.3% | 4.27 | untouched |
| Activate agitators and paddles to mix or stir ingredients, stopping machines when ingredients are thoroughly mixed. | 16.7% | 8.3% | 75.0% | 4.38 | untouched |
| Operate auxiliary machines and equipment, such as grinders, canners, and molding presses, to prepare or further process products. | 15.0% | 10.0% | 75.0% | 4.33 | untouched |
| Collect and examine product samples during production to test them for quality, color, content, consistency, viscosity, acidity, or specific gravity. | 5.4% | 7.1% | 87.5% | 4.35 | untouched |
| Clean, wash, and sterilize equipment and cooking area, using water hoses, cleaning or sterilizing solutions, or rinses. | 0.0% | 0.0% | 100.0% | 4.65 | untouched |
| Measure or weigh ingredients, using scales or measuring containers. | 0.0% | 0.0% | 100.0% | 4.52 | untouched |
| Tend or operate and control equipment, such as kettles, cookers, vats and tanks, and boilers, to cook ingredients or prepare products for further processing. | 0.0% | 0.0% | 100.0% | 4.48 | untouched |
| Remove cooked material or products from equipment. | 0.0% | 0.0% | 100.0% | 4.37 | untouched |
| Pour, dump, or load prescribed quantities of ingredients or products into cooking equipment, manually or using a hoist. | 0.0% | 0.0% | 100.0% | 4.32 | untouched |
| Notify or signal other workers to operate equipment or when processing is complete. | 0.0% | 0.0% | 100.0% | 4.24 | untouched |
| Place products on conveyors or carts, and monitor product flow. | 0.0% | 0.0% | 100.0% | 4.23 | untouched |
Task text and importance ratings sourced from O*NET 31.0. Shares computed. The occupation score is the importance-weighted mean.
Occupations either side of this one
The four closest scores in the same occupational family, then the four closest anywhere in the index.
Read this carefully. Exposure is not displacement. A high score means current AI systems can produce this work, not that anyone will stop paying a person to do it. Adoption depends on economics, regulation and inertia that this index deliberately does not model. How the score is built.
What this means in practice
Most of this work is not reachable by current systems, so the immediate pressure is on the administrative edges of the role rather than its core: the scheduling, the reporting, the written records. That is where time is recovered.