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Food Preparation Workers

Occupation · SOC 35-2021.00

Perform a variety of food preparation duties other than cooking, such as preparing cold foods and shellfish, slicing meat, and brewing coffee or tea.

Also called: Cook · Deli Clerk (Delicatessen Clerk) · Dietary Aide · Food Service Worker (FSW) · Cook Aide · Diet Aide · Food Prep (Food Preparer) · Food Service Aide · Line Cook · Nutrition Aide · Back of House Team Member (BOH Team Member) · Cafeteria Aide

Job family: Food Preparation and Serving Related Occupations

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Download .md

A source-stamped Markdown brief of this occupation — paste it into an agent, or fetch /roles/role-35-2021-00/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.

  • Store food in designated containers and storage areas to prevent spoilage. · 1.0%
  • Receive and store food supplies, equipment, and utensils in refrigerators, cupboards, and other storage areas. · 0.3%
See collaboration patterns →

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.

  • Store food in designated containers and storage areas to prevent spoilage. · 100.0% need a human
  • Receive and store food supplies, equipment, and utensils in refrigerators, cupboards, and other storage areas. · 100.0% need a human
See the boundary tasks →

17th-percentile task overlap — yet about 148,000 openings a year (-3.4% projected, BLS), and observed AI use leans 5538% 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.) Low 9th -1.2
LLM task exposure, γ (OpenAI / Eloundou) Low 8th 0.1
AI assistant applicability (Microsoft) Moderate 44th 0.1

OpenAI's exposure study scores tasks three ways: with a language model alone (α 0.0), with simple added tooling (β 0.0), and including AI-powered software (γ 0.1). 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 0.9 · 74th 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.

Store food in designated containers and storage areas to prevent spoilage. 2.0%
Keep records of the quantities of food used. 0.3%

Job outlook

Independent U.S. Bureau of Labor Statistics employment projection for 2024–2034 — a labor-market forecast, not an AI-impact forecast.

Outlook Declining · -3.4% by 2034
Projected annual openings 148,000
Employment 2024 → 2034 902,700 → 871,800

“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.

13% mean task exposure (2025)
11th percentile of 427 placed occupations
+5 pts shift 2023 → 2025
International occupation (ISCO-08) Task exposure (2025) Most tasks fall in
Kitchen Helpers · 9412 13% 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 55.4% working with AI · 20.0% handed to AI
Most common way people use AI here Learning · you ask AI to explain or teach
Typical AI autonomy 3.0 / 5 · higher = AI acts more independently

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
Store food in designated containers and storage areas to prevent spoilage. Learning 1.0%
Receive and store food supplies, equipment, and utensils in refrigerators, cupboards, and other storage areas. Learning 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.

Store food in designated containers and storage areas to prevent spoilage. 100.0%
Receive and store food supplies, equipment, and utensils in refrigerators, cupboards, and other storage areas. 100.0%

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 store food in designated containers and storage areas to prevent spoilage.

    From: Store food in designated containers and storage areas to prevent spoilage. · 1.0% of measured AI use · learning

  • Help me receive and store food supplies, equipment, and utensils in refrigerators, cupboards, and other storage areas.

    From: Receive and store food supplies, equipment, and utensils in refrigerators, cupboards, and other storage areas. · 0.3% of measured AI use · learning

Tasks

All 31 tasks O*NET lists for this occupation, ordered by importance. Each links to its own page with AI-exposure and observed-use detail.

Emerging tasks

Newer responsibilities O*NET has flagged as growing for this occupation.

  • Check and log refrigerator, freezer, and cooler temperatures.

Work activities

Knowledge, skills & abilities

O*NET importance rating, from 1 (not important) to 5 (extremely important).

Knowledge

Customer and Personal Service 3.3
Food Production 2.9
Production and Processing 2.7
English Language 2.4
Administration and Management 2.3

Essential skills

Active Listening 3.0
Speaking 2.9
Critical Thinking 2.8
Reading Comprehension 2.6
Monitoring 2.5
Mathematics 2.0

Transferable skills

Service Orientation 3.0
Time Management 3.0
Coordination 2.9
Social Perceptiveness 2.6
Judgment and Decision Making 2.4
Quality Control Analysis 2.1

Abilities

Oral Comprehension 3.0
Trunk Strength 3.0
Near Vision 3.0
Oral Expression 2.9
Arm-Hand Steadiness 2.9
Manual Dexterity 2.9
Finger Dexterity 2.9
Speech Recognition 2.9
Speech Clarity 2.9
Information Ordering 2.8
Problem Sensitivity 2.6
Deductive Reasoning 2.6
Category Flexibility 2.6
Selective Attention 2.6
Inductive Reasoning 2.5
Stamina 2.5
Extent Flexibility 2.5
Far Vision 2.4
Written Comprehension 2.3
Static Strength 2.3
Visual Color Discrimination 2.3
Time Sharing 2.1
Multilimb Coordination 2.1

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 Office software Office suite software Hot technology
Barrington Software CookenPro Commercial Data base user interface and query software
CBORD Foodservice Suite Data base user interface and query software
CBORD NetRecipe Data base user interface and query software
Culinary Software Services ChefTec Data base user interface and query software
EGS CALCMENU Data base user interface and query software
iPro Data base user interface and query software
Master Cook Deluxe Professional Cook Data base user interface and query software
Mealmaster Cookbook Wizard Data base user interface and query software
MicroBlast Recipe Wizard for Windows Data base user interface and query software
Quizlet Computer based training software
Recipe software Data base user interface and query software
ValuSoft MasterCook Data base user interface and query software
YouTube Video creation and editing 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.

Indoors, Environmentally Controlled 4.7
Spend Time Standing 4.4
Contact With Others 4.2
Wear Common Protective or Safety Equipment such as Safety Shoes, Glasses, Gloves, Hearing Protection, Hard Hats, or Life Jackets 4.2
Importance of Being Exact or Accurate 4.2
Face-to-Face Discussions with Individuals and Within Teams 4.1
Time Pressure 3.9
Work With or Contribute to a Work Group or Team 3.9
Coordinate or Lead Others in Accomplishing Work Activities 3.6
Spend Time Using Your Hands to Handle, Control, or Feel Objects, Tools, or Controls 3.6
Spend Time Walking or Running 3.4
Health and Safety of Other Workers 3.4
Physical Proximity 3.3
Importance of Repeating Same Tasks 3.3
Spend Time Making Repetitive Motions 3.3
Frequency of Decision Making 3.2
Consequence of Error 3.1
Telephone Conversations 3.0
Impact of Decisions on Co-workers or Company Results 3.0
Freedom to Make Decisions 2.9
Work Outcomes and Results of Other Workers 2.7
Determine Tasks, Priorities and Goals 2.7
Exposed to Minor Burns, Cuts, Bites, or Stings 2.6
Spend Time Bending or Twisting Your Body 2.5
Degree of Automation 2.5
Deal With External Customers or the Public in General 2.3
Exposed to Hazardous Conditions 2.3
Pace Determined by Speed of Equipment 2.2
Written Letters and Memos 2.1
E-Mail 2.0
Exposed to Very Hot or Cold Temperatures 2.0
Level of Competition 1.9
Dealing With Unpleasant, Angry, or Discourteous People 1.9
Exposed to Disease or Infections 1.8
Spend Time Keeping or Regaining Balance 1.8
Public Speaking 1.8
Outdoors, Exposed to All Weather Conditions 1.7
Spend Time Kneeling, Crouching, Stooping, or Crawling 1.7
Conflict Situations 1.6
Outdoors, Under Cover 1.6

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.

Education of current workers

Share of people in this occupation at each level of education.

Doctoral Degree 4.2%
Less than a High School Diploma 2.7%
Post-Secondary Certificate 1.2%

Interests & work styles

The interests and personal qualities O*NET associates with people who do this work.

Career interests (Holland / RIASEC)

Realistic 6.4
Conventional 4.2
Social 2.7
Enterprising 2.2
Artistic 1.9
Investigative 1.4

Interest areas

Physical/Manual Labor 4.8
Culinary Art 2.5
Personal Service 1.9
Health Care Service 1.7
Management/Administration 1.2
Social Service 1.2
Accounting 1.2

Work styles

Dependability 2.1
Attention to Detail 1.8
Cautiousness 1.2

Wages & employment

U.S. · annual wages (BLS OEWS)

$23k10th$29k25th$34kMedian$38k75th$44k90th
Annual wages by percentile — U.S. (BLS OEWS). The light band spans the 10th–90th percentile; the darker band is the middle half (25th–75th); the line is the median.
903k2024872k2034 (proj.)-3.4% · Declining
Projected U.S. employment, 2024–2034 (BLS Employment Projections). A labor-market forecast for the occupation, not an AI-impact forecast.
10th percentile $23,490
25th percentile $28,740
Median (50th) $34,220
75th percentile $37,540
90th percentile $44,260
People employed 888,770

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 515,940 $33,280
Retail Trade · Sector 233,660 $35,270
Full-Service Restaurants · National industry 214,960 $35,540
Health Care and Social Assistance · Sector 54,410 $33,800
Educational Services · Sector 33,580 $36,190
Manufacturing · Sector 15,000 $35,130
Arts, Entertainment, and Recreation · Sector 10,030 $35,720
Administrative and Support and Waste Management and Remediation Services · Sector 9,920 $33,500
Temporary Help Services · National industry 7,840 $33,040
Other Services (except Public Administration) · Sector 3,400 $33,390
Casino Hotels · National industry 3,040 $38,770
Services for the Elderly and Persons with Disabilities · National industry 2,930 $29,680

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 6.96× 214,960
Accommodation and Food Services · Sector 6.29× 515,940
Retail Trade · Sector 2.6× 233,660
Casino Hotels · National industry 1.56× 3,040
Theater Companies and Dinner Theaters · National industry 0.67× 280
Arts, Entertainment, and Recreation · Sector 0.66× 10,030
Temporary Help Services · National industry 0.51× 7,840
Residential Mental Health and Substance Abuse Facilities · National industry 0.46× 690

Part of the Hospitality, Events, & Tourism career cluster.

Exposure quadrant: AI task-overlap percentile vs Median pay Food Preparation Workers sits at the 17th percentile of AI task-overlap and the 2nd percentile of median pay, placed here against 12 adjacent occupations on the same two axes. Lower overlap · higher pay Higher overlap · higher pay Higher overlap · lower pay Lower overlap · lower pay Food Preparation Workers Cooks, Institution and Cafeteria Butchers and Meat Cutters Chefs and Head Cooks Cooks, Private Household AI task-overlap percentile → ↑ Median pay
AI task-overlap percentile (horizontal) vs. median-pay percentile (vertical), across all scored occupations. This occupation is highlighted; related occupations are plotted alongside it. Overlap measures shared tasks with AI, not automation.

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 Food Preparation Workers — 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.

Paths in

How people typically prepare for this work.

Zoom out

On the global GenAI exposure gradient this work sits around the 11th percentile of 427 international occupations.

Write a report on thisheadline · factoids · citation

Food Preparation Workers show 17th-percentile AI task overlap — and about 148,000 annual U.S. openings

  • Food Preparation Workers rank in the 17th 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 148,000 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 declining (-3.4%) from 2024 to 2034.BLS Employment Projections 2024–34
  • Median annual pay is $34,220, across about 888,770 U.S. workers.BLS OEWS (May 2024)
  • Of the AI use actually observed for this work, 55% 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
Food Preparation Workers show 17th-percentile AI task overlap — and about 148,000 annual U.S. openings

• Food Preparation Workers rank in the 17th 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 148,000 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 declining (-3.4%) from 2024 to 2034. (BLS Employment Projections 2024–34)
• Median annual pay is $34,220, across about 888,770 U.S. workers. (BLS OEWS (May 2024))
• Of the AI use actually observed for this work, 55% 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 — "Food Preparation Workers". https://singulariki.com/roles/role-35-2021-00
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.

Data compiled June 2, 2026. Figures are estimates, not advice.

Cite this page
Plain

Singulariki. "Food Preparation Workers." 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-35-2021-00

APA

Singulariki. (2026). Food Preparation Workers. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-35-2021-00

BibTeX
@misc{singulariki-role-35-2021-00,
  title  = {Food Preparation Workers},
  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-35-2021-00}
}

Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.

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