Often handed to AI
Task areas most often handled directively in observed AI conversations — candidates to delegate with light review.
- Estimate amounts and costs of required supplies, such as food and ingredients. · 2.1%
Chefs and Head Cooks
Occupation · SOC 35-1011.00
Direct and may participate in the preparation, seasoning, and cooking of salads, soups, fish, meats, vegetables, desserts, or other foods. May plan and price menu items, order supplies, and keep records and accounts.
Also called: Chef · Executive Chef (Ex Chef) · Kitchen Manager · Sous Chef · Banquet Chef · Cook · Executive Pastry Chef · Executive Sous Chef · Food and Beverage Director · Head Cook · Baker · Bread and Pastry Baker
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-35-1011-00/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.
Use as a copilot
Task areas where people work with AI — iterating, learning, or checking — staying in the loop rather than handing the task off.
- Analyze recipes to assign prices to menu items, based on food, labor, and overhead costs. · 0.6%
Keep a human in the loop
Task areas where a human was still judged necessary in a large share of observed conversations — not a safety ruling, an observed-need signal.
- Estimate amounts and costs of required supplies, such as food and ingredients. · 99.5% need a human
- Plan, direct, or supervise the food preparation or cooking activities of multiple kitchens or restaurants in an establishment such as a restaurant chain, hospital, or hotel. · 90.3% need a human
- Analyze recipes to assign prices to menu items, based on food, labor, and overhead costs. · 89.5% need a human
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 →Market signal
Independent published positions, read together — not a forecast.
- Growing fast employment outlook (+7.1% by 2034)
- 24,400 openings/yr
- Moderate AI exposure
- Observed AI use leans automation
- Median pay $60,990/yr
- Work is mostly on-site (not teleworkable)
42nd-percentile task overlap — yet about 24,400 openings a year (+7.1% projected, BLS), and observed AI use leans 3851% copilot, not hand-off (AEI) . 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.) Moderate | 41st | -0.3 | |
| LLM task exposure, γ (OpenAI / Eloundou) Moderate | 39th | 0.4 | |
| AI assistant applicability (Microsoft) Moderate | 51st | 0.2 |
OpenAI's exposure study scores tasks three ways: with a language model alone (α 0.1), with simple added tooling (β 0.3), and including AI-powered software (γ 0.4). 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.
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 0.1 · 29th percentile among occupations · Low
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.
| Estimate amounts and costs of required supplies, such as food and ingredients. | 0.5% | |
| Meet with customers to discuss menus for special occasions, such as weddings, parties, or banquets. | 0.4% | |
| Check the quality of raw or cooked food products to ensure that standards are met. | 0.3% | |
| Coordinate planning, budgeting, or purchasing for all the food operations within establishments such as clubs, hotels, or restaurant chains. | 0.3% | |
| Collaborate with other personnel to plan and develop recipes or menus, taking into account such factors as seasonal availability of ingredients or the likely number of customers. | 0.3% | |
| Analyze recipes to assign prices to menu items, based on food, labor, and overhead costs. | 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 | Growing fast · +7.1% by 2034 |
| Projected annual openings | 24,400 |
| Employment 2024 → 2034 | 197,300 → 211,300 |
“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.
Chefs and Head Cooks sits at the 47th 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.
25% mean task exposure (2025)
47th percentile of 427 placed occupations
−1 pts shift 2023 → 2025
| International occupation (ISCO-08) | Task exposure (2025) | Most tasks fall in |
|---|---|---|
| Chefs · 3434 | 25% | 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.
Working with AI in this job
How people actually apply AI to this occupation's tasks, from Claude.ai (Free and Pro) conversations in the Anthropic Economic Index, 2026-01-15. This is one AI assistant's consumer sample — not all AI, not the whole workforce. Autonomy and the collaboration mix are model-rated estimates; figures below the sample floor are hidden.
| Augmentation vs. automation | 38.5% working with AI · 38.9% handed to AI |
| Most common way people use AI here | Directive · AI does it; you give the instruction |
| Typical AI autonomy | 4.0 / 5 · higher = AI acts more independently |
| Used for work (vs. personal / coursework) | 22.6% |
What people delegate to AI
The role's most common tasks in AI conversations, each tagged with how people work with the AI on it. “Usage” is the share of observed conversations, not of the job.
| Task | How | Usage |
|---|---|---|
| Estimate amounts and costs of required supplies, such as food and ingredients. | Directive | 2.1% |
| Analyze recipes to assign prices to menu items, based on food, labor, and overhead costs. | Iteration | 0.6% |
| Plan, direct, or supervise the food preparation or cooking activities of multiple kitchens or restaurants in an establishment such as a restaurant chain, hospital, or hotel. | — | 0.3% |
Where a human is still needed
Tasks where the model most often judged that a person remained necessary — a useful read on the current boundary, not a guarantee.
| Estimate amounts and costs of required supplies, such as food and ingredients. | 99.5% | |
| Plan, direct, or supervise the food preparation or cooking activities of multiple kitchens or restaurants in an establishment such as a restaurant chain, hospital, or hotel. | 90.3% | |
| Analyze recipes to assign prices to menu items, based on food, labor, and overhead costs. | 89.5% |
What people most often hand AI here
Example prompts phrased from the tasks people most often delegate to AI in this occupation (Anthropic Economic Index). Each shows the underlying measured task and its share of observed AI use. They are suggested phrasings of real tasks — starting points, not endorsed instructions.
-
Help me estimate amounts and costs of required supplies, such as food and ingredients.From: Estimate amounts and costs of required supplies, such as food and ingredients. · 2.1% of measured AI use · directive
-
Help me analyze recipes to assign prices to menu items, based on food, labor, and overhead costs.From: Analyze recipes to assign prices to menu items, based on food, labor, and overhead costs. · 0.6% of measured AI use · task iteration
-
Help me plan, direct, or supervise the food preparation or cooking activities of multiple kitchens or restaurants in an establishment such as a restaurant chain, hospital, or hotel.From: Plan, direct, or supervise the food preparation or cooking activities of multiple kitchens or restaurants in an establishment such as a restaurant chain, hospital, or hotel. · 0.3% of measured AI use
Tasks
All 21 tasks O*NET lists for this occupation, ordered by importance. Each links to its own page with AI-exposure and observed-use detail.
- Monitor sanitation practices to ensure that employees follow standards and regulations. Core · importance 4.9
- Instruct cooks or other workers in the preparation, cooking, garnishing, or presentation of food. Core · importance 4.6
- Supervise or coordinate activities of cooks or workers engaged in food preparation. Core · importance 4.5
- Order or requisition food or other supplies needed to ensure efficient operation. Core · importance 4.4
- Inspect supplies, equipment, or work areas to ensure conformance to established standards. Core · importance 4.3
- Check the quantity and quality of received products. Core · importance 4.3
- Check the quality of raw or cooked food products to ensure that standards are met. Core · importance 4.3
- Estimate amounts and costs of required supplies, such as food and ingredients. Core · importance 4.3
- Coordinate planning, budgeting, or purchasing for all the food operations within establishments such as clubs, hotels, or restaurant chains. Core · importance 4.0
- Analyze recipes to assign prices to menu items, based on food, labor, and overhead costs. Core · importance 4.0
- Plan, direct, or supervise food preparation or cooking activities of multiple kitchens or restaurants in an establishment such as a restaurant chain, hospital, or hotel. Core · importance 3.9
- Determine how food should be presented and create decorative food displays. Core · importance 3.8
- Determine production schedules and staff requirements necessary to ensure timely delivery of services. Core · importance 3.8
- Prepare and cook foods of all types, either on a regular basis or for special guests or functions. Core · importance 3.8
- Meet with customers to discuss menus for special occasions, such as weddings, parties, or banquets. Core · importance 3.6
- Recruit and hire staff, such as cooks and other kitchen workers. Core · importance 3.6
- Record production or operational data on specified forms. Core · importance 3.5
- Meet with sales representatives to negotiate prices or order supplies. Core · importance 3.5
- Arrange for equipment purchases or repairs. Core · importance 3.5
- Demonstrate new cooking techniques or equipment to staff. Core · importance 3.5
- Collaborate with other personnel to plan and develop recipes or menus, taking into account such factors as seasonal availability of ingredients or the likely number of customers. Core · importance 3.4
Work activities
- Check quality of foods or supplies.
- Monitor activities of individuals to ensure safety or compliance with rules.
- Order materials, supplies, or equipment.
- Coordinate activities of food service staff.
- Inspect facilities, equipment or supplies to ensure conformance to standards.
- Create new recipes or food presentations.
- Train food preparation or food service personnel.
- Estimate supplies, ingredients, or staff requirements for food preparation activities.
- Plan menu options.
- Determine prices for menu items.
- Cook foods.
- Coordinate timing of food production activities.
- Perform human resources activities.
- Plan special events.
- Communicate with customers to resolve complaints or ensure satisfaction.
- Schedule equipment maintenance.
- Record operational or production data.
- Manage food service operations or parts of operations.
Knowledge, skills & abilities
O*NET importance rating, from 1 (not important) to 5 (extremely important).
Transferable skills
Knowledge
Abilities
| Oral Expression | 4.1 | |
| Problem Sensitivity | 4.1 | |
| Oral Comprehension | 4.0 | |
| Information Ordering | 4.0 | |
| Deductive Reasoning | 3.9 | |
| Speech Clarity | 3.9 | |
| Inductive Reasoning | 3.8 | |
| Near Vision | 3.8 | |
| Speech Recognition | 3.8 | |
| Written Comprehension | 3.5 | |
| Originality | 3.4 | |
| Selective Attention | 3.4 | |
| Fluency of Ideas | 3.3 | |
| Category Flexibility | 3.3 | |
| Visualization | 3.3 |
Essential skills
| Monitoring | 4.0 | |
| Speaking | 3.9 | |
| Critical Thinking | 3.8 | |
| Active Listening | 3.6 | |
| Reading Comprehension | 3.5 | |
| Active Learning | 3.4 | |
| Learning Strategies | 3.3 |
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
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 3 — Job Zone Three: Medium Preparation Needed
- Education
- Most occupations in this zone require training in vocational schools, related on-the-job experience, or an associate's degree.
- Typical entry-level education
- High school diploma or equivalent · BLS, the typical path — not a requirement
- Related experience
- Previous work-related skill, knowledge, or experience is required for these occupations. For example, an electrician must have completed three or four years of apprenticeship or several years of vocational training, and often must have passed a licensing exam, in order to perform the job.
- Preparation level
- SVP (6.0 to < 7.0) — total schooling plus on-the-job experience.
What to study: Culinary, Entertainment, and Personal Services . 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.
| Associate's Degree (or other 2-year degree) | 54.2% | |
| Post-Secondary Certificate | 16.7% | |
| High School Diploma | 12.5% | |
| Some College Courses | 8.3% | |
| Bachelor's Degree | 8.3% |
Interests & work styles
The interests and personal qualities O*NET associates with people who do this work.
Interest areas
| Culinary Art | 6.8 | |
| Management/Administration | 5.6 | |
| Physical/Manual Labor | 3.3 | |
| Human Resources | 3.1 | |
| Accounting | 3.1 | |
| Business Initiatives | 2.9 | |
| Personal Service | 2.9 | |
| Teaching/Education | 2.8 | |
| Applied Arts and Design | 2.6 |
Career interests (Holland / RIASEC)
| Enterprising | 5.1 | |
| Realistic | 4.8 | |
| Conventional | 4.3 | |
| Social | 3.0 | |
| Artistic | 2.7 |
Work styles
| Dependability | 4.0 | |
| Attention to Detail | 3.0 |
Wages & employment
U.S. · annual wages (BLS OEWS)
| 10th percentile | $36,000 |
| 25th percentile | $47,710 |
| Median (50th) | $60,990 |
| 75th percentile | $76,790 |
| 90th percentile | $96,030 |
| People employed | 182,320 |
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 |
|---|---|---|
| Accommodation and Food Services · Sector | 142,030 | $60,580 |
| Full-Service Restaurants · National industry | 87,040 | $59,490 |
| Arts, Entertainment, and Recreation · Sector | 12,060 | $68,070 |
| Health Care and Social Assistance · Sector | 8,780 | $57,350 |
| Educational Services · Sector | 4,110 | $52,040 |
| Casino Hotels · National industry | 3,690 | $61,120 |
| Retail Trade · Sector | 3,200 | $49,920 |
| Other Services (except Public Administration) · Sector | 1,970 | $63,700 |
| Administrative and Support and Waste Management and Remediation Services · Sector | 1,920 | $72,670 |
| Management of Companies and Enterprises · Sector | 1,910 | $75,940 |
| Manufacturing · Sector | 1,850 | $61,770 |
| Fitness and Recreational Sports Centers · National industry | 660 | $77,980 |
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 |
|---|---|---|
| Full-Service Restaurants · National industry | 13.73× | 87,040 |
| Casino Hotels · National industry | 9.26× | 3,690 |
| Accommodation and Food Services · Sector | 8.44× | 142,030 |
| Arts, Entertainment, and Recreation · Sector | 3.86× | 12,060 |
| Residential Mental Health and Substance Abuse Facilities · National industry | 1.08× | 330 |
| Fitness and Recreational Sports Centers · National industry | 0.89× | 660 |
| Management of Companies and Enterprises · Sector | 0.57× | 1,910 |
| Other Services (except Public Administration) · Sector | 0.38× | 1,970 |
Related occupations
Part of the Hospitality, Events, & Tourism and Management & Entrepreneurship career clusters.
- Bakers · 51-3011.00 Compare →
- Cooks, Restaurant · 35-2014.00 Compare →
- Cooks, Private Household · 35-2013.00 Compare →
- Cooks, Institution and Cafeteria · 35-2012.00 Compare →
- Food Service Managers · 11-9051.00 Compare →
- Cooks, Short Order · 35-2015.00 Compare →
- First-Line Supervisors of Food Preparation and Serving Workers · 35-1012.00 Compare →
- Food Batchmakers · 51-3092.00 Compare →
- Waiters and Waitresses · 35-3031.00 Compare →
- Dietetic Technicians · 29-2051.00 Compare →
- Food Preparation Workers · 35-2021.00 Compare →
- Cooks, Fast Food · 35-2011.00 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 Chefs and Head Cooks — 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.
- High school diploma or equivalent · typical entry level
- Job zone 3 — Job Zone Three: Medium Preparation Needed · preparation tier
- Culinary, Entertainment, and Personal Services · field of study
Zoom out
On the global GenAI exposure gradient this work sits around the 47th percentile of 427 international occupations.
Write a report on thisheadline · factoids · citation
Chefs and Head Cooks show 42nd-percentile AI task overlap — and about 24,400 annual U.S. openings
- Chefs and Head Cooks rank in the 42nd percentile (Moderate 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 24,400 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 growing fast (+7.1%) from 2024 to 2034.BLS Employment Projections 2024–34
- Median annual pay is $60,990, across about 182,320 U.S. workers.BLS OEWS (May 2024)
- Of the AI use actually observed for this work, 39% looks like augmentation (drafting, iterating, checking) rather than hands-off automation — from a Claude.ai usage sample, not a census.2026-01-15-v4-plus-2025-03-27-v2
Copy the whole kit
Chefs and Head Cooks show 42nd-percentile AI task overlap — and about 24,400 annual U.S. openings • Chefs and Head Cooks rank in the 42nd percentile (Moderate 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 24,400 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 growing fast (+7.1%) from 2024 to 2034. (BLS Employment Projections 2024–34) • Median annual pay is $60,990, across about 182,320 U.S. workers. (BLS OEWS (May 2024)) • Of the AI use actually observed for this work, 39% looks like augmentation (drafting, iterating, checking) rather than hands-off automation — from a Claude.ai usage sample, not a census. (2026-01-15-v4-plus-2025-03-27-v2) Source: Singulariki — "Chefs and Head Cooks". https://singulariki.com/roles/role-35-1011-00 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. "Chefs and Head Cooks." 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-35-1011-00
APA
Singulariki. (2026). Chefs and Head Cooks. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-35-1011-00
BibTeX
@misc{singulariki-role-35-1011-00,
title = {Chefs and Head Cooks},
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-35-1011-00}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.