Skills it runs on
The capabilities O*NET rates most important for this occupation — the human ground the work is built on.
See all skills →Cooks, Institution and Cafeteria
Occupation · SOC 35-2012.00
Prepare and cook large quantities of food for institutions, such as schools, hospitals, or cafeterias.
Also called: Cafeteria Cook · Cook · Dietary Cook · School Cook · Dinner Cook · Food Service Specialist · Food Service Worker · Prep Cook (Preparatory Cook) · Sous Chef · Boarding House Cook · Camp Cook · Culinary Specialist
Job family: Food Preparation and Serving Related Occupations
Take this to your AI
A source-stamped Markdown brief of this occupation — paste it into an agent, or fetch
/roles/role-35-2012-00/context.md directly.
AI work map
A fast read on where AI already shows up in this occupation, where it stays a copilot, where humans remain in the loop, and what the labor market is doing. Built from observed Claude.ai conversations mapped to O*NET tasks and from published research — measures of usage and exposure, not advice or predictions that the job is going away.
Market signal
Independent published positions, read together — not a forecast.
- About average employment outlook (+2.0% by 2034)
- 69,700 openings/yr
- Low AI exposure
- Median pay $36,450/yr
- Work is mostly on-site (not teleworkable)
- 2013 flagged this for computerization (68th); today's AI task-overlap is comparatively low (22nd)
22nd-percentile task overlap — yet about 69,700 openings a year (+2% projected, BLS) . What exposure means →
AI & job outlook
What today's research says about this occupation's exposure to AI, how AI is actually being used in it, and where employment is headed. These are positions within published studies — measures of exposure and usage, not predictions that this job will disappear.
Exposure to current AI
Each study uses its own scale, so the raw scores are not comparable across rows — the percentile (this job's rank among all U.S. occupations with data) is the comparable figure, and sizes the bars.
| Measure | Rank vs all occupations | Percentile | Score |
|---|---|---|---|
| Overall AI exposure (Felten et al.) Low | 30th | -0.6 | |
| LLM task exposure, γ (OpenAI / Eloundou) Low | 25th | 0.2 | |
| AI assistant applicability (Microsoft) Low | 19th | 0.1 |
OpenAI's exposure study scores tasks three ways: with a language model alone (α 0.0), with simple added tooling (β 0.1), and including AI-powered software (γ 0.2). Higher means more of the job's tasks could be done at least twice as fast — not that they will be automated away.
This job mostly cannot be done remotely (Dingel–Neiman) — its hands-on tasks sit outside what software-based AI reaches.
Mixed signals. Today's AI/LLM studies show relatively low exposure for this job, but the older (2013) Frey–Osborne work rated it higher for computerization and robotics. Different eras, different technologies — the AI measures above reflect the current state.
Historical automation estimate (2013)
A pre-LLM (2013) estimate of how automatable this job is by computerization and robotics. Shown for historical context only — it is not part of any current AI ranking.
Frey–Osborne probability 0.8 · 68th percentile among occupations · High
How AI is actually used in this job
Among measured AI assistant conversations mapped to this occupation (Anthropic Economic Index, 2026-01-15), these task types came up most. These are shares of observed AI conversations — not shares of the job, of worker time, or of what could be automated.
| Clean, cut, and cook meat, fish, or poultry. | 0.2% | |
| Determine meal prices, based on calculations of ingredient prices. | 0.2% |
Job outlook
Independent U.S. Bureau of Labor Statistics employment projection for 2024–2034 — a labor-market forecast, not an AI-impact forecast.
| Outlook | About average · +2.0% by 2034 |
| Projected annual openings | 69,700 |
| Employment 2024 → 2034 | 466,100 → 475,400 |
“Annual openings” counts new jobs plus replacements for workers who leave the occupation, so it can be large even when growth is modest.
Where this work sits on the global GenAI gradient
The ILO's 2025 global study scores generative-AI exposure on the international ISCO-08 occupation system, not US SOC. Bridged through the published (and approximate, many-to-many) IBS O*NET-SOC ↔ ISCO-08 crosswalk, this US occupation corresponds to the international occupation below. Exposure here means how much of the work's tasks today's AI can attempt — task overlap, not automation, adoption, or jobs lost.
Cooks, Institution and Cafeteria sits at the 29th percentile of 427
occupations on the global GenAI task-exposure gradient
— exposure eased from 2023 to 2025. Each dot is one occupation; the
ringed one is this work. Exposure is task overlap, not automation or jobs lost.
18% mean task exposure (2025)
29th percentile of 427 placed occupations
−1 pts shift 2023 → 2025
| International occupation (ISCO-08) | Task exposure (2025) | Most tasks fall in |
|---|---|---|
| Cooks · 5120 | 18% | Not exposed |
Read the whole six-band gradient on the GenAI exposure gradient page. The crosswalk is approximate: a US occupation can map to several international ones, and the ILO scores describe the international occupation, not this exact US role.
Tasks
All 17 tasks O*NET lists for this occupation, ordered by importance. Each links to its own page with AI-exposure and observed-use detail.
- Monitor and record food temperatures to ensure food safety. Core · importance 4.7
- Cook foodstuffs according to menus, special dietary or nutritional restrictions, or numbers of portions to be served. Core · importance 4.7
- Rotate and store food supplies. Core · importance 4.6
- Wash pots, pans, dishes, utensils, or other cooking equipment. Core · importance 4.6
- Apportion and serve food to facility residents, employees, or patrons. Core · importance 4.6
- Clean and inspect galley equipment, kitchen appliances, and work areas to ensure cleanliness and functional operation. Core · importance 4.6
- Clean, cut, and cook meat, fish, or poultry. Core · importance 4.5
- Monitor use of government food commodities to ensure that proper procedures are followed. Supplemental · importance 4.4
- Direct activities of one or more workers who assist in preparing and serving meals. Core · importance 4.4
- Plan menus that are varied, nutritionally balanced, and appetizing, taking advantage of foods in season and local availability. Supplemental · importance 4.3
- Monitor menus and spending to ensure that meals are prepared economically. Supplemental · importance 4.3
- Compile and maintain records of food use and expenditures. Supplemental · importance 4.3
- Train new employees. Core · importance 4.3
- Take inventory of supplies and equipment. Core · importance 4.2
- Requisition food supplies, kitchen equipment, and appliances, based on estimates of future needs. Core · importance 4.2
- Bake breads, rolls, or other pastries. Core · importance 3.8
- Determine meal prices, based on calculations of ingredient prices. Supplemental · importance 3.7
Work activities
- Monitor food services operations to ensure procedures are followed.
- Inspect facilities, equipment or supplies to ensure conformance to standards.
- Record operational or production data.
- Move equipment, supplies or food to required locations.
- Store supplies or goods in kitchens or storage areas.
- Maintain food, beverage, or equipment inventories.
- Clean food preparation areas, facilities, or equipment.
- Serve food or beverages.
- Cook foods.
- Cut cooked or raw foods.
- Prepare foods for cooking or serving.
- Clean tableware.
- Coordinate activities of food service staff.
- Prepare breads or doughs.
- Train food preparation or food service personnel.
- Plan menu options.
- Order materials, supplies, or equipment.
- Determine prices for menu items.
Knowledge, skills & abilities
O*NET importance rating, from 1 (not important) to 5 (extremely important).
Knowledge
| English Language | 3.6 | |
| Food Production | 3.6 | |
| Customer and Personal Service | 3.6 | |
| Mathematics | 3.5 | |
| Administration and Management | 3.3 | |
| Production and Processing | 3.1 | |
| Public Safety and Security | 3.0 |
Abilities
| Oral Expression | 3.3 | |
| Near Vision | 3.3 | |
| Oral Comprehension | 3.1 | |
| Problem Sensitivity | 3.1 | |
| Deductive Reasoning | 3.1 | |
| Information Ordering | 3.1 | |
| Category Flexibility | 3.1 | |
| Speech Clarity | 3.1 | |
| Written Comprehension | 3.0 | |
| Inductive Reasoning | 3.0 | |
| Visualization | 3.0 | |
| Selective Attention | 3.0 | |
| Time Sharing | 3.0 | |
| Arm-Hand Steadiness | 3.0 | |
| Manual Dexterity | 3.0 | |
| Finger Dexterity | 3.0 | |
| Trunk Strength | 3.0 | |
| Speech Recognition | 3.0 |
Essential skills
| Speaking | 3.1 | |
| Monitoring | 3.1 | |
| Active Listening | 3.0 | |
| Critical Thinking | 3.0 | |
| Reading Comprehension | 2.9 | |
| Mathematics | 2.9 | |
| Active Learning | 2.9 |
Transferable skills
Skills in demand
Skills employers ask for in job postings for this occupation (Lightcast), with whether each is a common or specialized skill.
Tools & technology
| Example | Category | |
|---|---|---|
| Microsoft Excel | Spreadsheet software | Hot technology |
| Microsoft Word | Word processing software | Hot technology |
| GNOME Gnutrition | Analytical or scientific software | |
| IBM Lotus 1-2-3 | Spreadsheet software | |
| Meals Plus | Data base user interface and query software | |
| PCS Revenue Control Systems FASTRAK School Meal Software | Point of sale POS software |
Work context
How characteristic each condition is of the job, on O*NET's 1–5 context scale (higher = more present in day-to-day work). Each condition links to how it varies across all occupations.
How to get in
- Job zone
- Zone 2 — Job Zone 1-2: Very Little to Some Preparation Needed
- Education
- Usually requires a high school diploma or GED, though some occupations may not.
- Typical entry-level education
- No formal educational credential · BLS, the typical path — not a requirement
- Related experience
- Some occupations may need little or no previous experience; others require several months to a year of experience. For example, landscaping and groundskeeping workers might require very little training or previous experience, while agricultural equipment operators can benefit from on-the job training.
- Preparation level
- SVP (Below 6.0) — total schooling plus on-the-job experience.
What to study: Culinary, Entertainment, and Personal Services , Family and Consumer Sciences/Human Sciences . Fields of study crosswalked to this occupation (NCES CIP–SOC), not a requirement.
Education of current workers
Share of people in this occupation at each level of education.
| High School Diploma | 71.1% | |
| Post-Secondary Certificate | 14.2% | |
| Bachelor's Degree | 6.8% | |
| Some College Courses | 5.8% | |
| Less than a High School Diploma | 1.9% | |
| Associate's Degree (or other 2-year degree) | 0.1% |
Interests & work styles
The interests and personal qualities O*NET associates with people who do this work.
Career interests (Holland / RIASEC)
| Realistic | 5.9 | |
| Conventional | 4.3 | |
| Social | 3.2 | |
| Enterprising | 3.2 | |
| Artistic | 2.0 | |
| Investigative | 1.8 |
Interest areas
| Physical/Manual Labor | 3.8 | |
| Culinary Art | 3.4 | |
| Management/Administration | 2.3 | |
| Personal Service | 2.0 | |
| Human Resources | 1.8 | |
| Health Care Service | 1.7 | |
| Accounting | 1.6 |
Work styles
| Dependability | 2.6 | |
| Attention to Detail | 2.1 | |
| Cooperation | 1.6 |
Wages & employment
U.S. · annual wages (BLS OEWS)
| 10th percentile | $26,800 |
| 25th percentile | $30,530 |
| Median (50th) | $36,450 |
| 75th percentile | $42,860 |
| 90th percentile | $48,320 |
| People employed | 448,260 |
Industries that employ this occupation
Where these workers are employed, by number of jobs (national, BLS OEWS). Pay shown is the occupation's national median, not industry-specific.
| Industry | Workers | National median pay |
|---|---|---|
| Health Care and Social Assistance · Sector | 172,560 | $37,280 |
| Educational Services · Sector | 144,720 | $34,010 |
| Accommodation and Food Services · Sector | 86,900 | $37,560 |
| Administrative and Support and Waste Management and Remediation Services · Sector | 6,300 | $35,010 |
| Retail Trade · Sector | 6,200 | $29,410 |
| Residential Mental Health and Substance Abuse Facilities · National industry | 4,420 | $39,810 |
| Services for the Elderly and Persons with Disabilities · National industry | 4,160 | $32,860 |
| Arts, Entertainment, and Recreation · Sector | 3,600 | $36,880 |
| Other Services (except Public Administration) · Sector | 3,520 | $36,210 |
| Temporary Help Services · National industry | 2,730 | $35,620 |
| Real Estate and Rental and Leasing · Sector | 1,590 | $38,880 |
| Residential Intellectual and Developmental Disability Facilities · National industry | 1,220 | $35,180 |
Where this work is most concentrated
Industries where this occupation is far more common than in the economy as a whole. The location quotient is how many times more concentrated it is here (a value of 5 means five times its economy-wide share).
| Industry | Concentration | Workers |
|---|---|---|
| Residential Mental Health and Substance Abuse Facilities · National industry | 5.88× | 4,420 |
| Educational Services · Sector | 3.65× | 144,720 |
| Health Care and Social Assistance · Sector | 2.57× | 172,560 |
| Accommodation and Food Services · Sector | 2.1× | 86,900 |
| Residential Intellectual and Developmental Disability Facilities · National industry | 1.08× | 1,220 |
| Outpatient Mental Health and Substance Abuse Centers · National industry | 0.78× | 700 |
| Services for the Elderly and Persons with Disabilities · National industry | 0.59× | 4,160 |
| Arts, Entertainment, and Recreation · Sector | 0.47× | 3,600 |
Related occupations
Part of the Healthcare & Human Services , Hospitality, Events, & Tourism , Management & Entrepreneurship and Public Service & Safety career clusters.
- Cooks, Restaurant · 35-2014.00 Compare →
- Food Preparation Workers · 35-2021.00 Compare →
- Cooks, Private Household · 35-2013.00 Compare →
- Cooks, Short Order · 35-2015.00 Compare →
- Chefs and Head Cooks · 35-1011.00 Compare →
- Cooks, Fast Food · 35-2011.00 Compare →
- Bakers · 51-3011.00 Compare →
- Food Service Managers · 11-9051.00 Compare →
- Fast Food and Counter Workers · 35-3023.00 Compare →
- First-Line Supervisors of Food Preparation and Serving Workers · 35-1012.00 Compare →
- Food Servers, Nonrestaurant · 35-3041.00 Compare →
- Butchers and Meat Cutters · 51-3021.00 Compare →
Side-by-side comparisons place two occupations’ pay, preparation, skills, and AI exposure on the same page — same data, same scale, no forecast.
What you can do with this
Options the data surfaces for Cooks, Institution and Cafeteria — not advice or a forecast. Each is a real cross-link you can follow into the evidence.
Skills that travel
Capabilities this work builds that are used across many other occupations.
Adjacent roles
Occupations O*NET rates as related — the nearby moves on the map.
Paths in
How people typically prepare for this work.
- No formal educational credential · typical entry level
- Job zone 2 — Job Zone 1-2: Very Little to Some Preparation Needed · preparation tier
- Culinary, Entertainment, and Personal Services · field of study
- Family and Consumer Sciences/Human Sciences · field of study
Zoom out
On the global GenAI exposure gradient this work sits around the 29th percentile of 427 international occupations.
Write a report on thisheadline · factoids · citation
Cooks, Institution and Cafeteria show 22nd-percentile AI task overlap — and about 69,700 annual U.S. openings
- Cooks, Institution and Cafeteria rank in the 22nd percentile (Low band) for AI task overlap across U.S. occupations — a measure of how much of the work today's AI can attempt, not how much is automated.Eloundou et al. (GPTs are GPTs) + Felten AIOE
- The occupation is projected to see about 69,700 U.S. job openings per year (2024–34), counting growth and replacement — a labor-demand projection made independently of AI.BLS Employment Projections 2024–34
- BLS projects employment to be about average (+2%) from 2024 to 2034.BLS Employment Projections 2024–34
- Median annual pay is $36,450, across about 448,260 U.S. workers.BLS OEWS (May 2024)
Copy the whole kit
Cooks, Institution and Cafeteria show 22nd-percentile AI task overlap — and about 69,700 annual U.S. openings • Cooks, Institution and Cafeteria rank in the 22nd percentile (Low band) for AI task overlap across U.S. occupations — a measure of how much of the work today's AI can attempt, not how much is automated. (Eloundou et al. (GPTs are GPTs) + Felten AIOE) • The occupation is projected to see about 69,700 U.S. job openings per year (2024–34), counting growth and replacement — a labor-demand projection made independently of AI. (BLS Employment Projections 2024–34) • BLS projects employment to be about average (+2%) from 2024 to 2034. (BLS Employment Projections 2024–34) • Median annual pay is $36,450, across about 448,260 U.S. workers. (BLS OEWS (May 2024)) Source: Singulariki — "Cooks, Institution and Cafeteria". https://singulariki.com/roles/role-35-2012-00 Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.
AssetsShare imageMethodology & sourcesPress & newsroomThe newsroom
Every line is built only from figures this page already shows and cites. AI task overlap means what today's AI can attempt — not automation, job loss, or a forecast.
Sources for this page
Every figure above traces to a named public dataset and the exact release below — not hand-written opinion. See the full methodology for what each measure does and does not mean.
- O*NET 30.3 U.S. Department of Labor / National Center for O*NET Development
- BLS Occupational Employment and Wage Statistics (OEWS) May 2024 U.S. Bureau of Labor Statistics
- BLS Employment Projections 2024–2034 U.S. Bureau of Labor Statistics
- Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27) Anthropic
- Microsoft “Working with AI” working-with-ai Microsoft Research
- “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130 OpenAI / academic
- AI Occupational Exposure (AIOE) Felten, Raj & Seamans academic
- ILO / Gmyrek et al. GenAI exposure gradient 2025 International Labour Organization
- IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022 Institute for Structural Research (IBS)
- Frey & Osborne (2013) frey-osborne-automation academic
- Dingel & Neiman (2020) dingel-neiman-workathome academic
Data compiled June 2, 2026. Figures are estimates, not advice.
Cite this page
Plain
Singulariki. "Cooks, Institution and Cafeteria." Singulariki: a source-backed encyclopedia of work. Built from O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); Microsoft “Working with AI” working-with-ai; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans; ILO / Gmyrek et al. GenAI exposure gradient 2025; IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022; Frey & Osborne (2013) frey-osborne-automation; Dingel & Neiman (2020) dingel-neiman-workathome. Accessed June 7, 2026. https://singulariki.com/roles/role-35-2012-00
APA
Singulariki. (2026). Cooks, Institution and Cafeteria. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-35-2012-00
BibTeX
@misc{singulariki-role-35-2012-00,
title = {Cooks, Institution and Cafeteria},
author = {{Singulariki}},
year = {2026},
note = {O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); Microsoft “Working with AI” working-with-ai; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans; ILO / Gmyrek et al. GenAI exposure gradient 2025; IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022; Frey & Osborne (2013) frey-osborne-automation; Dingel & Neiman (2020) dingel-neiman-workathome. Accessed June 7, 2026},
url = {https://singulariki.com/roles/role-35-2012-00}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.