AI exposure: Cooks, Institution and Cafeteria
Prepare and cook large quantities of food for institutions, such as schools, hospitals, or cafeterias.
Reading this score
computedAt 18.2% of weighted task load, Cooks, Institution and Cafeteria sits at the 31th percentile, below the point where a job's centre of gravity has moved. 71.6% 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 2.25 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 Requisition food supplies, kitchen equipment, and appliances, based on estimates of future needs, at 80.0%. The least is Bake breads, rolls, or other pastries, at 0.0%. A gap of 80.0% 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 food preparation and serving occupations, this one is more exposed than most. The median across the 16 roles in the group is 16.1%, and only 7 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, 4 are currently banded exposed, 1 assisted and 12 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 | 1.34 | 0-4 |
| Embodiment | 2.25 | 0-3 |
| Presence | 0.90 | 0-3 |
| Accountability | 0.66 | 0-3 |
| Context | 1.18 | 0-3 |
| Verification cost | 1.14 | 0-3 |
Task by task
17 tasks, O*NET 31.0| Task | Exposed | Assisted | Untouched | Importance | Band |
|---|---|---|---|---|---|
| Requisition food supplies, kitchen equipment, and appliances, based on estimates of future needs. | 80.0% | 20.0% | 0.0% | 4.15 | exposed |
| Plan menus that are varied, nutritionally balanced, and appetizing, taking advantage of foods in season and local availability. | 80.0% | 20.0% | 0.0% | 4.33 | exposed |
| Compile and maintain records of food use and expenditures. | 73.3% | 26.7% | 0.0% | 4.31 | exposed |
| Determine meal prices, based on calculations of ingredient prices. | 60.0% | 15.0% | 25.0% | 3.72 | exposed |
| Monitor and record food temperatures to ensure food safety. | 24.4% | 25.6% | 50.0% | 4.73 | assisted |
| Take inventory of supplies and equipment. | 15.0% | 10.0% | 75.0% | 4.23 | untouched |
| Direct activities of one or more workers who assist in preparing and serving meals. | 10.0% | 15.0% | 75.0% | 4.38 | untouched |
| Monitor use of government food commodities to ensure that proper procedures are followed. | 10.0% | 15.0% | 75.0% | 4.44 | untouched |
| Monitor menus and spending to ensure that meals are prepared economically. | 10.0% | 15.0% | 75.0% | 4.32 | untouched |
| Train new employees. | 8.3% | 16.7% | 75.0% | 4.25 | untouched |
| Rotate and store food supplies. | 5.6% | 2.8% | 91.7% | 4.60 | untouched |
| Clean and inspect galley equipment, kitchen appliances, and work areas to ensure cleanliness and functional operation. | 5.0% | 7.5% | 87.5% | 4.56 | untouched |
| Cook foodstuffs according to menus, special dietary or nutritional restrictions, or numbers of portions to be served. | 0.0% | 0.0% | 100.0% | 4.68 | untouched |
| Wash pots, pans, dishes, utensils, or other cooking equipment. | 0.0% | 0.0% | 100.0% | 4.59 | untouched |
| Apportion and serve food to facility residents, employees, or patrons. | 0.0% | 0.0% | 100.0% | 4.57 | untouched |
| Clean, cut, and cook meat, fish, or poultry. | 0.0% | 0.0% | 100.0% | 4.54 | untouched |
| Bake breads, rolls, or other pastries. | 0.0% | 0.0% | 100.0% | 3.76 | 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.