---
title: "Will AI Replace Food Preparation Workers? (2026)"
description: "BLS rates food preparation workers' exposure to AI as low. What that means, which parts of the work AI touches, and the 2025–2035 outlook (-3.0%…"
canonical: "https://nuecareer.com/careers/will-ai-replace-food-preparation-workers"
last-updated: "2026-10-15T08:19:32.066Z"
---

# Will AI Replace Food Preparation Workers? (2026)

**Short answer:** Very unlikely. BLS rates food preparation workers among the occupations least exposed to AI, and most of the work is the kind current AI tools cannot do.

The Bureau of Labor Statistics places food preparation workers in its low AI exposure category, among the occupations least exposed to current AI. BLS projects employment to fall by 3.0% over 2025–2035, against 3.5% for all occupations, with about 135,700 openings a year.

| Measure | Value | Source |
| --- | --- | --- |
| BLS relative AI exposure | Low | BLS Employment Projections, AI exposure categories |
| NueCareer AI-resilience score | 49/100 | NueCareer analysis of O\*NET 31.0 Database |
| Projected employment change | -3.0% | BLS EP 2025–2035 |
| Openings a year | 135,700 | BLS EP 2025–2035 |
| Median annual wage | $35,320 | BLS OEWS May 2025 |

## Exposure categories

| BLS category | Occupations |
| --- | --- |
| Low (this job) | 203 |
| Moderate | 194 |
| High | 190 |
| Very high | 199 |

Exposure means AI could be or has been used to assist with or complete some of the work. BLS says it does not imply job loss, productivity gains, automation probability or wage effects. Method: https://www.bls.gov/emp/publications/ai-exposure-categories.htm

## What holds up

- Face-to-face discussions: 4.1/5 (O\*NET work context)
- Time spent on your feet: 4.4/5 (O\*NET work context)
- Performing general physical activities: 3.4/5 (O\*NET work activity importance)
- Hands-on work with tools and objects: 3.6/5 (O\*NET work context)

## What AI reaches first

- Getting information: 3.9/5 (O\*NET work activity importance)
- Evaluating information to determine compliance with standards: 3.6/5 (O\*NET work activity importance)
- Being exact or highly accurate: 4.2/5 (O\*NET work context)

## O\*NET tasks

- Clean and sanitize work areas, equipment, utensils, dishes, or silverware.
- Carry food supplies, equipment, and utensils to and from storage and work areas.
- Remove trash and clean kitchen garbage containers.
- Store food in designated containers and storage areas to prevent spoilage.
- Inform supervisors when equipment is not working properly and when food and supplies are getting low, and order needed items.
- Receive and store food supplies, equipment, and utensils in refrigerators, cupboards, and other storage areas.

## Related careers that are also low-exposure

- [Dining Room and Cafeteria Attendant and Bartender Helper](https://nuecareer.com/careers/dining-room-and-cafeteria-attendant-and-bartender-helper): BLS exposure Low, median $33,980; [Will AI replace bussers?](https://nuecareer.com/careers/will-ai-replace-bussers)
- [Dishwasher](https://nuecareer.com/careers/dishwasher): BLS exposure Low, median $34,810; [Will AI replace dishwashers?](https://nuecareer.com/careers/will-ai-replace-dishwashers)
- [Cook, Institution and Cafeteria](https://nuecareer.com/careers/cook-institution-and-cafeteria): BLS exposure Low, median $37,450

## FAQ

**Will AI replace food preparation workers?**

Very unlikely. BLS rates food preparation workers among the occupations least exposed to AI, and most of the work is the kind current AI tools cannot do. BLS defines exposure as AI being able to assist with or complete some of the work, and says it does not imply job loss, productivity gains or wage effects. BLS projects employment to fall by 3.0% over 2025–2035, against 3.5% for all occupations, with about 135,700 openings a year.

**How exposed are food preparation workers to AI?**

BLS sorts 786 occupations into four relative categories: low, moderate, high and very high. Food Preparation Workers are in the low category, alongside 202 other occupations. The categories combine five public measures of where AI could be or already is used, and they compare occupations with each other rather than giving an absolute risk.

**What parts of a food preparation worker's job can AI do?**

In O\*NET's description of the work, the parts that overlap most with what AI handles well are getting information, evaluating information to determine compliance with standards and being exact or highly accurate. The parts that hold up best are face-to-face discussions, time spent on your feet and performing general physical activities. These come from O\*NET ratings of how important each activity is to the job, read through NueCareer's AI-resilience method.

**Is being a food preparation worker a safe career from AI?**

On NueCareer's AI-resilience score, built from O\*NET work activities, food preparation workers score 49 out of 100, higher than 59% of the occupations we score. The job pays a median of $35,320 a year (BLS OEWS, May 2025). No job is fully safe from technological change, but the federal exposure category and the projected openings are the two numbers worth weighing.

**What careers similar to food preparation workers are less exposed to AI?**

Dining Room and Cafeteria Attendant and Bartender Helper (low exposure, $33,980 median), Dishwasher (low exposure, $34,810 median), Cook, Institution and Cafeteria (low exposure, $37,450 median). Each is also in the low category, and most are listed by O\*NET as related to the work.

Full profile: https://nuecareer.com/careers/food-preparation-worker.

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This bank includes information from the O\*NET 31.0 Database by the U.S. Department of Labor, Employment and Training Administration (USDOL/ETA). Used under the CC BY 4.0 license (https://creativecommons.org/licenses/by/4.0/). O\*NET® is a trademark of USDOL/ETA. NueCareer has transformed the data by joining it to BLS wage and projection data and deriving facet, personality-fit and AI-resilience scores. BLS and BEA data are public domain (17 U.S.C. §105).

O\*NET content is used under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/). How these figures are sourced and derived: https://nuecareer.com/careers/methodology