Short Order Cooks

Food Preparation & Service

AI exposure

  • Data source: BLSPublished: 2026-08

    Low· relative

    LowFour relative bandsVery high

    Group-level value

    Scale, basis and source

    Four relative bands (Low / Moderate / High / Very high)

    831 detailed occupations in the BLS Employment Projections table. Assigned per National Employment Matrix (NEM) code, so occupations sharing a NEM code carry the same band

    Source dataset (XLSX download)

  • Data source: AnthropicPublished: 2026-03

    0.000

    0.000Range of values carried here0.745
    Scale, basis and source

    Observed exposure index, 0–1 as published

    Mapped onto O*NET tasks

    Source dataset

  • Data source: ILOPublished: 2025

    0.18

    0.09Range of values carried here0.70

    Group-level value

    Scale, basis and source

    Generative AI exposure index, 0–1 as published

    ISCO-08 unit group — every occupation sharing the code gets this value

    Computed by this site, not published by the ILO: of the 1,012 occupations this site links to the ILO dataset, 90% score at or above this value.

    Source dataset

What kind of figure this source publishes

The BLS category is a relative rank, not an absolute level, and it is not a first-hand measurement: it groups an occupation's percentile ranks across several published studies into four bands. It is not an employment or wage forecast, not a probability of adoption, and it does not separate automation from augmentation.

Task-level exposure

Values in this tab are predicted labels, not observations. Eloundou et al. (2023) published two rating regimes — human raters and GPT-4 — and the β shown here is derived from the GPT-4 rater basis alone; the same task can take a different value under the other regime. The unit and the meaning differ from the observed shares (%) in the other tabs, so do not place them on the same axis.

TaskβE1 + 0.5 × E2
Clean food preparation equipment, work areas, and counters or tables.

O*NET Task ID 2187

0.0
Plan work on orders so that items served together are finished at the same time.

O*NET Task ID 2188

0.0
Grill, cook, and fry foods such as french fries, eggs, and pancakes.

O*NET Task ID 2189

0.0
Take orders from customers and cook foods requiring short preparation times, according to customer requirements.

O*NET Task ID 2190

0.0
Grill and garnish hamburgers or other meats, such as steaks and chops.

O*NET Task ID 2191

0.0
Complete orders from steam tables, placing food on plates and serving customers at tables or counters.

O*NET Task ID 2192

0.0
Order supplies and stock them on shelves.

O*NET Task ID 2194

0.0
Accept payments, and make change or write charge slips as necessary.

O*NET Task ID 2195

0.0
Restock kitchen supplies, rotate food, and stamp the time and date on food in coolers.

O*NET Task ID 18725

0.0
Perform food preparation tasks, such as making sandwiches, carving meats, making soups or salads, baking breads or desserts, and brewing coffee or tea.

O*NET Task ID 18726

0.0
Perform general cleaning activities in kitchen and dining areas.

O*NET Task ID 18727

0.0

β = E1 + 0.5 × E2 · E1 = tasks where direct LLM access alone cuts time by at least 50%, E2 = tasks where software built on top of an LLM cuts time by at least 50%. Values take only 0 / 0.5 / 1.0.

Data sources & licenses — O*NET®, Eloundou et al. (2023): see full notices on the Credits page

Occupation information