Cooks, Fast Food
Food Preparation and Serving Related Occupations- O*NET-SOC code
- 35-2011.00
Prepare and cook food in a fast food restaurant with a limited menu. Duties of these cooks are limited to preparation of a few basic items and normally involve operating large-volume single-purpose cooking equipment.
- Data source: BLSPublished: 2026-08
Moderate· relative
LowFour relative bandsVery highGroup-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
- Data source: AnthropicPublished: 2026-03
0.000
0.000Range of values carried here0.745Scale, basis and source
Observed exposure index, 0–1 as published
Mapped onto O*NET tasks
Published per SOC 2018 occupation; every O*NET occupation with the same SOC 2018 code carries this value
- Data source: ILOPublished: 2025
0.18
0.09Range of values carried here0.70Group-level value
Scale, basis and source
Generative AI exposure index, 0–1 as published
Published per ISCO-08 unit group. Linked to this occupation, wholly or in part, by applying U.S. Bureau of Labor Statistics crosswalks (ISCO-08 to 2010 SOC, 2010 SOC to 2018 SOC) as published
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
Exposed tasks only19 rated tasks · 0 tasks with β ≥ 0.5 (0.0%)
β = direct exposure (E1) + 0.5 × exposure when tools are available (E2), per the source repository's definition.
- Source unit: O*NET 27.2 tasks → O*NET 31.0 occupation code
- All rated tasks are in the O*NET 31.0 task list.
- Source
- OpenAI "GPTs are GPTs" exposure rubric
- Release
- gh-main-0471612
- License
- MIT License, Copyright (c) 2024 OpenAI
| Task (O*NET 20.1) | Claude.aiRaw / share % |
|---|---|
Read food order slips or receive verbal instructions as to food required by patron, and prepare and cook food according to instructions.35-2011.00 | 0.028569.3 |
Prepare dough, following recipe.35-2011.00 | 0.006315.2 |
Measure ingredients required for specific food items being prepared.35-2011.00 | 0.00337.9 |
Mix ingredients such as pancake or waffle batters.35-2011.00 | 0.00317.6 |
| Not observed on any surface — 15 task(s) — These tasks have no row in the source for this release. The 0 in the share row is a display-stage composition ratio; absence is what the — in the raw row states. | |
Maintain sanitation, health, and safety standards in work areas. | —0 |
Clean food preparation areas, cooking surfaces, and utensils. | —0 |
Operate large-volume cooking equipment such as grills, deep-fat fryers, or griddles. | —0 |
Verify that prepared food meets requirements for quality and quantity. | —0 |
Take food and drink orders and receive payment from customers. | —0 |
Wash, cut, and prepare foods designated for cooking. | —0 |
Cook and package batches of food, such as hamburgers and fried chicken, which are prepared to order or kept warm until sold. | —0 |
Cook the exact number of items ordered by each customer, working on several different orders simultaneously. | —0 |
Serve orders to customers at windows, counters, or tables. | —0 |
Clean, stock, and restock workstations and display cases. | —0 |
Prepare specialty foods such as pizzas, fish and chips, sandwiches, and tacos, following specific methods that usually require short preparation time. | —0 |
Prepare and serve beverages such as coffee and fountain drinks. | —0 |
Pre-cook items such as bacon, to prepare them for later use. | —0 |
Schedule activities and equipment use with managers, using information about daily menus to help coordinate cooking times. | —0 |
Order and take delivery of supplies. | —0 |
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.
| Task (O*NET 27.2) | βE1 + 0.5 × E2 |
|---|---|
Maintain sanitation, health, and safety standards in work areas.O*NET Task ID 5053 | 0.0 |
Clean food preparation areas, cooking surfaces, and utensils.O*NET Task ID 5054 | 0.0 |
Operate large-volume cooking equipment, such as grills, deep-fat fryers, or griddles.O*NET Task ID 5055 | 0.0 |
Verify that prepared food meets requirements for quality and quantity.O*NET Task ID 5056 | 0.0 |
Take food and drink orders and receive payment from customers.O*NET Task ID 5057 | 0.0 |
Read food order slips or receive verbal instructions as to food required by patron, and prepare and cook food according to instructions.O*NET Task ID 5058 | 0.0 |
Wash, cut, and prepare foods designated for cooking.O*NET Task ID 5059 | 0.0 |
Measure ingredients required for specific food items.O*NET Task ID 5060 | 0.0 |
Cook and package batches of food, such as hamburgers or fried chicken, prepared to order or kept warm until sold.O*NET Task ID 5061 | 0.0 |
Cook the exact number of items ordered by each customer, working on several different orders simultaneously.O*NET Task ID 5062 | 0.0 |
Serve orders to customers at windows, counters, or tables.O*NET Task ID 5063 | 0.0 |
Clean, stock, and restock workstations and display cases.O*NET Task ID 5064 | 0.0 |
Prepare specialty foods, such as pizzas, fish and chips, sandwiches, or tacos, following specific methods that usually require short preparation time.O*NET Task ID 5065 | 0.0 |
Prepare dough, following recipe.O*NET Task ID 5066 | 0.0 |
Schedule activities and equipment use with managers, using information about daily menus to help coordinate cooking times.O*NET Task ID 5067 | 0.0 |
Prepare and serve beverages, such as coffee or fountain drinks.O*NET Task ID 5068 | 0.0 |
Mix ingredients, such as pancake or waffle batters.O*NET Task ID 5069 | 0.0 |
Order and take delivery of supplies.O*NET Task ID 5070 | 0.0 |
Pre-cook items, such as bacon, to prepare them for later use.O*NET Task ID 5071 | 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®, Anthropic Economic Index, Eloundou et al. (2023): see full notices on the Credits page
All O*NET 31.0 task statements (20)
All O*NET 31.0 task statements for this occupation (English, as published; task type core or supplemental). Exposure values are not listed here; they are in the table above, next to each task statement as worded in the O*NET version each source used.
| Task (O*NET 31.0) | Type |
|---|---|
| Maintain sanitation, health, and safety standards in work areas. | Core |
| Clean food preparation areas, cooking surfaces, and utensils. | Core |
| Operate large-volume cooking equipment, such as grills, deep-fat fryers, or griddles. | Core |
| Verify that prepared food meets requirements for quality and quantity. | Core |
| Take food and drink orders and receive payment from customers. | Core |
| Read food order slips or receive verbal instructions as to food required by patron, and prepare and cook food according to instructions. | Core |
| Wash, cut, and prepare foods designated for cooking. | Core |
| Measure ingredients required for specific food items. | Core |
| Cook and package batches of food, such as hamburgers or fried chicken, prepared to order or kept warm until sold. | Core |
| Cook the exact number of items ordered by each customer, working on several different orders simultaneously. | Core |
| Serve orders to customers at windows, counters, or tables. | Core |
| Clean, stock, and restock workstations and display cases. | Core |
| Prepare specialty foods, such as pizzas, fish and chips, sandwiches, or tacos, following specific methods that usually require short preparation time. | Core |
| Pre-cook items, such as bacon, to prepare them for later use. | Core |
| Take out garbage. | Core |
| Prepare dough, following recipe. | Supplemental |
| Schedule activities and equipment use with managers, using information about daily menus to help coordinate cooking times. | Supplemental |
| Prepare and serve beverages, such as coffee or fountain drinks. | Supplemental |
| Mix ingredients, such as pancake or waffle batters. | Supplemental |
| Order and take delivery of supplies. | Supplemental |
1.21/ 3· Robot exposure index
Scale, basis and source
Each physical task is graded 0–3 by the setting in which robots that have been deployed, sold or demonstrated could do it (0 none · 1 purpose-built robot settings such as a fenced machine cell or a bottling line · 2 structured facilities such as a hospital pharmacy or a container port · 3 unstructured settings such as a private home or a construction site), and the grades are averaged by share of working time
Physical tasks among this occupation's O*NET 29.3 tasks
Anthropic estimated the grades and time shares with Claude Opus 5 using web search, as of 2026.
The robot exposure index is a different measure from the AI exposure figures on this site and cannot be added to or compared with them. It does not measure actual adoption or cost, and 0 also covers occupations with no physical tasks.
Tier of each physical task
Robot environment tiers (E0–E3)
E0 noneDetails
Rated not doable by robots that have been deployed, sold or demonstrated, even in a purpose-built setting
E1 purpose-built robot settingsDetails
Rated doable in a setting built around the machine, such as a fenced machine cell or a bottling line
E2 structured facilitiesDetails
Rated doable in a human work facility that an institution keeps to a working standard, such as a hospital pharmacy or a container port
E3 unstructured settingsDetails
Rated doable in a setting that no institution keeps to a working standard, such as a private home or a construction site
Only tasks classified as physical are listed; other tasks have no tier in the source.
| Task (O*NET 29.3) | Robot environment tier |
|---|---|
| Maintain sanitation, health, and safety standards in work areas. | E1 purpose-built robot settings |
| Clean food preparation areas, cooking surfaces, and utensils. | E1 purpose-built robot settings |
| Operate large-volume cooking equipment, such as grills, deep-fat fryers, or griddles. | E2 structured facilities |
| Read food order slips or receive verbal instructions as to food required by patron, and prepare and cook food according to instructions. | E1 purpose-built robot settings |
| Wash, cut, and prepare foods designated for cooking. | E1 purpose-built robot settings |
| Measure ingredients required for specific food items. | E2 structured facilities |
| Cook and package batches of food, such as hamburgers or fried chicken, prepared to order or kept warm until sold. | E2 structured facilities |
| Cook the exact number of items ordered by each customer, working on several different orders simultaneously. | E1 purpose-built robot settings |
| Serve orders to customers at windows, counters, or tables. | E2 structured facilities |
| Clean, stock, and restock workstations and display cases. | E1 purpose-built robot settings |
| Prepare specialty foods, such as pizzas, fish and chips, sandwiches, or tacos, following specific methods that usually require short preparation time. | E1 purpose-built robot settings |
| Prepare dough, following recipe. | E1 purpose-built robot settings |
| Prepare and serve beverages, such as coffee or fountain drinks. | E1 purpose-built robot settings |
| Mix ingredients, such as pancake or waffle batters. | E1 purpose-built robot settings |
| Order and take delivery of supplies. | E1 purpose-built robot settings |
| Pre-cook items, such as bacon, to prepare them for later use. | E1 purpose-built robot settings |
Occupation information
Employment outlook (BLS)
- Employment, 2025
- 641K
- Projected employment, 2035
- 644K
- Change (2025–35)
- +0.6%
- Median annual wage, 2025
- $30,890
- Typical education needed for entry
- No formal educational credential
Korea classification links (KSCO)
Links from the current release of the Korea Occupation Direct Crosswalk v1.1, made by AI Changing Work. Relation values are read from the O*NET-SOC occupation side.
| KSCO code | KSCO title | Relation | Status |
|---|---|---|---|
| 95210 | 패스트푸드 준비원 | Same scope | confirmed |
Relation and status definitions(kr-direct v1.1)
ILO occupational description
AI Changing Work links the ISCO-08 unit groups below to this occupation by applying the U.S. Bureau of Labor Statistics crosswalks (2018 SOC to 2010 SOC, 2010 SOC to ISCO-08) as published, without case-by-case selection; each link may be whole or partial.
- ISCO-08 9411Fast Food Preparers
Sources: ILO ISCO-08 — details: Credits
ESCO occupational vocabulary
Each entry below is matched to this occupation in the published ESCO-O*NET Crosswalk (version 1, 2022). The match types are that crosswalk's; the wording is AI Changing Work's.
- cookESCO 5120.1This occupation is narrower
cooks are culinary operatives who are able to prepare and present food, normally in domestic and institutional environments.
- quick service restaurant crew memberESCO 9411.2Overlapping, not the same
Quick service restaurant crew members prepare, cook and serve food and beverages in a quick service operation.
Source: European Commission, DG EMPL — ESCO API 2026-08-08 (bridge v1.2.1)
License: CC BY 4.0 (EU Reuse Notice)
ESCO reuse terms and the modification notice are in Credits.
France classification links (ROME)
AI Changing Work's links between this occupation and ROME 4.0 job profiles, judged with AI models. Relations are read from this occupation's side. Links marked “provisional” were adopted on the judgments of two judges from the same model family (Claude) alone, or by an operator rule applied to their judgments, so they rest on weaker evidence than confirmed links.
| ROME code | ROME title (French) | Relation |
|---|---|---|
| G1603 | Equipier polyvalent / Equipière polyvalente de restauration rapide | This occupation is narrowerprovisional |
| G1604 | Pizzaïolo / Pizzaïola | Related, not a matchprovisional |
Source: France Travail — Répertoire Opérationnel des Métiers et des Emplois (ROME 4.0), version 61, last updated 15 June 2026 (https://www.data.gouv.fr/datasets/repertoire-operationnel-des-metiers-et-des-emplois-rome). Licence Ouverte 2.0.
ROME codes and titles are reproduced unchanged; the links to O*NET-SOC occupations are AI Changing Work's own judgment and are not a France Travail correspondence.
(AI Changing Work link release: fr-direct v1)
Spain classification links (CNO-11)
AI Changing Work's links between this occupation and CNO-11 occupations, judged with AI models. Relations are read from this occupation's side.
| CNO-11 code | CNO-11 title (Spanish) | Relation |
|---|---|---|
| 9320 | Preparadores de comidas rápidas | This occupation is narrowerprovisional |
Source: Instituto Nacional de Estadística (INE), National Classification of Occupations 2011 (CNO-11, Royal Decree 1591/2010) — www.ine.es · Licensed CC BY 4.0. CNO-11 codes and Spanish titles are reproduced unchanged; the links to O*NET occupations are AI Changing Work's own judgment and are not an INE correspondence.
(AI Changing Work link release: es-direct v1)
Germany classification links (KldB)
AI Changing Work's links between this occupation and KldB occupations, judged with AI models. Relations are read from this occupation's side.
| KldB code | KldB title (German) | Relation |
|---|---|---|
| 63312 | Berufe in der Systemgastronomie - fachlich ausgerichtete Tätigkeiten | Overlapping, not the sameprovisional |
| 29301 | Köche/Köchinnen (ohne Spezialisierung) - Helfer-/Anlerntätigkeiten | Related, not a matchprovisional |
| 62301 | Berufe im Verkauf von Lebensmitteln (ohne Spezialisierung) - Helfer-/Anlerntätigkeiten | Related, not a matchprovisional |
Source: © Statistik der Bundesagentur für Arbeit — Klassifikation der Berufe 2010 – überarbeitete Fassung 2020, https://statistik.arbeitsagentur.de. KldB codes and titles are reproduced unchanged; the links to O*NET occupations are AI Changing Work's own mapping (eigene Zuordnung) and are not a Bundesagentur für Arbeit correspondence.
(AI Changing Work link release: de-direct v1)
Japan classification links (JSCO)
AI Changing Work's links between this occupation and JSCO occupations, judged with AI models. Relations are read from this occupation's side.
| JSCO code | JSCO title (Japanese) | Relation |
|---|---|---|
| 391 | 調理人 | This occupation is narrowerprovisional |
Source: Ministry of Internal Affairs and Communications (MIC), Japan Standard Occupational Classification (Dec. 2009, MIC Notification No. 555). JSCO codes and Japanese titles are reproduced unchanged; the links to O*NET occupations are AI Changing Work's own judgment and are not a MIC correspondence.
(AI Changing Work link release: jp-direct v1)
Sources, licenses and AI Changing Work's modification and translation notices for this page: Credits & sources