Somewhat Resilient

Last Update: 6/19/2026

AI Resilience Score for Food Preparation Workers:

45.0%

Median Score

Meaningful human contribution

Med

Long-term employer demand

Med

Sustained economic opportunity

Low

Our confidence in this score:
Medium

Contributing sources

Methodology and Scoring Rationale

To score how resilient food preparation work is to AI, we ask one question in three parts:

First, how much of the job still needs a human, read from four AI-exposure sources: our own AI Resilience Model, Anthropic's Observed Exposure, Microsoft's AI Applicability, and Will Robots Take My Job. We call this dimension Meaningful Human Contribution (MHC) and weight it at 40%.

Next, whether employers will keep hiring for this job over the long term. This dimension, which we call Long-term Employer Demand (LTE), is calculated from BLS data and weighted at 30%.

Last, whether pay and mobility will hold up. We use wage bill and adaptive capacity data from independent researchers (Althoff & Reichardt, 2026; Manning & Aguirre, 2026). We call this dimension Sustained Economic Opportunity (SEO) and weight it at 30%.

For food preparation workers, six of seven sources had data, with Anthropic missing. Sources split on AI exposure: our AI Resilience Model saw low risk while Will Robots Take My Job saw high risk and Microsoft landed in the middle, holding confidence at medium. Low pay and limited mobility pulled the economic score down, landing this role at "Somewhat Resilient."

AI Resilience Report forFood Preparation Workers

$34,220 median salary148,000 annual openingsSOC Code: 35-2021.00

Food Preparation Workers are somewhat less resilient to AI impacts than most occupations, according to our analysis of 6 sources.

Food preparation work is labeled "Somewhat Resilient" because AI is genuinely starting to change parts of this job, but the changes are happening slowly and unevenly across different types of kitchens. Big chain restaurants like Sweetgreen are already using automated systems that cut labor needs by around 30 to 70 percent for assembly tasks, so repetitive, predictable work is the most at risk.

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This role is somewhat resilient

Food preparation work is labeled "Somewhat Resilient" because AI is genuinely starting to change parts of this job, but the changes are happening slowly and unevenly across different types of kitchens. Big chain restaurants like Sweetgreen are already using automated systems that cut labor needs by around 30 to 70 percent for assembly tasks, so repetitive, predictable work is the most at risk.

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Analysis of Current AI Resilience

Food Preparation Workers

Updated Quarterly

Analysis
Suggested Actions
State of Automation

How is AI changing Food Preparation Workers jobs?

The good news first: even though AI is moving into restaurant kitchens, most of what you do as a food prep worker is still being done by people. According to a National Restaurant Association report, about 26% of restaurant operators say they use AI tools, but the top uses are marketing and admin tasks — not chopping or cooking [1]. Where AI does show up in the back of house, it's usually as an augmenter — meaning it helps workers, not replaces them.

The Food Institute describes AI as a "kitchen manager" that prioritizes orders, predicts prep times, and optimizes labor so meals finish together [2]. True robot prep does exist, though. The Society for Hospitality and Foodservice Management notes that AI robots are helping in kitchens with repetitive tasks like chopping vegetables or flipping burgers [3], and Sweetgreen's "Infinite Kitchen" is a real example: it requires about one-third fewer workers and automates roughly 70% of the labor that used to go into assembling bowls [4].

Still, these systems are concentrated in big chains and assembly-style restaurants — not most cafeterias, schools, or independent kitchens.

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AI Adoption

How fast is AI adoption growing for Food Preparation Workers?

Adoption will likely be gradual rather than sudden. On the "push" side, restaurants face high turnover and labor costs — Nation's Restaurant News highlights operators dealing with 144% annual turnover and roughly $6,109 per replacement hire [5], which makes automation tempting. On the "pull-back" side, prep robots are expensive, hard to install in small kitchens, and can't easily handle the messy variety of real ingredients.

The U.S. Bureau of Labor Statistics projects employment of food preparation workers to decline just 3% from 2024 to 2034, with about 148,000 openings each year [6] — meaning jobs will still be plentiful. Human skills like teamwork, food safety judgment, flexibility, and helping cooks under pressure remain very hard for machines to copy, so workers who build those strengths will stay valuable even as kitchens get smarter.

Sources

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Will AI replace Food Preparation Workers?

Will AI replace Food Preparation Workers?

Not entirely. We think AI will take over some tasks, but not the whole job.

Food prep work is changing, but it is not disappearing. Robots can already handle repetitive tasks like chopping vegetables or flipping burgers [3], and assembly-style restaurants like Sweetgreen have built systems that automate roughly 70% of bowl assembly, requiring about one-third fewer workers [4]. That is real displacement, and we will not pretend otherwise. Our 45.0% AI Resilience Score reflects that this role faces meaningful pressure.

Still, most kitchens are not Sweetgreen. About 26% of restaurant operators use AI today, and the top uses are marketing and admin, not cooking [1]. Prep robots are expensive, hard to fit into small kitchens, and struggle with the messy variety of real ingredients. The skills that hold up best against automation are the ones food prep workers already use every day: food safety judgment, flexibility under pressure, and teamwork.

The Bureau of Labor Statistics projects about 148,000 job openings per year in this field through 2034 [6], so work will still exist. The economic picture is tighter, though. Workers who build adaptable skills and learn to work alongside smarter kitchen tools will be in the best position as this role keeps evolving.

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Latest AI news for Food Preparation Workers

These articles highlight how AI is reshaping careers in food preparation. For instance, the Deloitte piece shows how AI enhances restaurant experiences, which means food workers will need to adapt to new technologies that improve efficiency and customer service. Additionally, the PMC study on food manufacturing emphasizes AI's role in optimizing production and reducing waste, suggesting that food preparation workers will need to develop skills in working alongside AI tools. Embracing these changes will help students build resilient careers in a rapidly evolving industry.

More Career Info

Career: Food Preparation Workers

They help prepare ingredients by chopping vegetables, measuring ingredients, and following recipes to ensure meals are ready for cooking in restaurants or cafeterias.

Employment & Wage Data

Median Wage

$34,220

Jobs (2024)

902,700

Growth (2024-34)

-3.4%

Annual Openings

148,000

Education

No formal educational credential

Experience

None

Source: Bureau of Labor Statistics, Employment Projections 2024-2034

Task-Level AI Resilience Scores

AI-generated estimates of task resilience over the next 3 years

1

87% ResilienceSupplemental

Scrape leftovers from dishes into garbage containers.

2

86% ResilienceCore Task

Make special dressings and sauces as condiments for sandwiches.

3

85% ResilienceCore Task

Receive and store food supplies, equipment, and utensils in refrigerators, cupboards, and other storage areas.

4

84% ResilienceSupplemental

Butcher and clean fowl, fish, poultry, and shellfish to prepare for cooking or serving.

5

83% ResilienceCore Task

Remove trash and clean kitchen garbage containers.

6

82% ResilienceCore Task

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

7

82% ResilienceSupplemental

Cut, slice or grind meat, poultry, and seafood to prepare for cooking.

Tasks are ranked by their AI resilience, with the most resilient tasks shown first. Core tasks are essential functions of this occupation, while supplemental tasks provide additional context.

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