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Time Machine

Food Preparation Workers

Scrub through 151years of this role's history, from when it first emerged, through every wave of technology that reshaped it, to the cited projections for where it's heading next.

2026drag to travel through time
19001925195019752000now
Country
2026
Known today as Food Preparation Workers (BLS SOC 35-2021)
US Employment
894K
OEWS is a point-in-time survey snapshot, not a continuous time series; BLS advises against using it for year-over-year trend comparison.
Median Annual Wage
$35,320
≈ $34,414 in 2024 dollars
Each dot is a cited figure over time; the dotted line only links them (values between aren't measured). Hollow dots are estimates.
Tools of the era

The tools that defined the work

Select an era to see how it reshaped the work.

  • Hand tools + open-range batch cooking (early cafeteria kitchen)

    The early American cafeteria kitchen — as at the 1885 Kohler & Chase counter-service lunchroom in San Francisco and the 1902 Horn & Hardart Automat in Philadelphia — ran on hand tools: cleavers, French knives, box graters, mandolines, and stock pots over gas or coal ranges. The prep worker's core task was volume: reducing large quantities of raw ingredients into the portions that would feed hundreds of customers in a short service window. Speed and physical endurance defined the role. There was no mechanization in the modern sense; a cafeteria kitchen's productivity was entirely a function of how many hands could work simultaneously in the available space. The Horn & Hardart back-of-house — hidden from view behind the Automat's coin-operated walls — was organized as a production line: one worker cleaning, another slicing, another ladling into compartments, all at scale and on a schedule.

    Mainframe processingComputerized records
  • Commercial refrigeration + Hobart slicer + steam table (institutional kitchen standardization)

    Mechanical refrigeration became viable for commercial kitchens by the 1920s and was widespread by the 1930s, fundamentally changing how institutional kitchens organized prep work. Where pre-refrigeration kitchens had to prep daily — vegetables could not be cut more than a few hours ahead — refrigeration allowed prep workers to process ingredients a day or two in advance and hold them safely. The Hobart commercial meat slicer (Hobart Manufacturing Company, Troy, Ohio) became standard equipment in institutional kitchens through the 1930s and 1940s, mechanizing the most repetitive cutting task and reducing the hand-fatigue component of the prep worker's day. Steam tables — insulated trays that held prepared food at service temperature with hot water circulating underneath — became the primary serving infrastructure for the school cafeteria model created by the 1946 National School Lunch Act, and required prep workers to produce food in batch quantities precisely matched to the steam table system's capacity.

    Work toolChanging equipment
  • Aramark / Sodexo / Compass institutional foodservice model — contract managed services

    The founding and expansion of institutional foodservice management companies through the 1950s-1980s created the organizational structure that employs the largest share of food preparation workers today. Aramark (founded 1936 as Davidson Brothers, restructured as ARA — Automatic Retailers of America — in 1959) pioneered the managed-services model: a company contracts to operate the food service for a hospital, university, prison, or corporation, supplying both the management systems and the labor. Sodexo (founded in Marseille, France in 1966 by Pierre Bellon, US operations expanding from 1983, merger with Marriott Management Services in 1998) built a similar operation. Compass Group (founded 1941 as Factory Canteens Limited in the UK, US market entry 1996 through the Eurest subsidiary) completed the triopoly that collectively accounts for an estimated 600,000+ US food service workers across all categories. For the food preparation worker, the managed-services model meant standardized recipes, centralized purchasing, and systematic training — a professionalization of the institutional kitchen that raised baseline hygiene and safety standards even as it suppressed wages through contract competition.

    Work toolChanging equipment
  • Combi-oven + commercial food processor + HACCP compliance systems

    The combination convection-steam oven (combi-oven), commercially available from the 1970s and standard in institutional kitchens by the late 1980s-1990s, changed the heat-based prep task: a single combi-oven could simultaneously steam-cook vegetables at precise humidity levels while roasting proteins at precise internal temperature, reducing the constant monitoring previously required of prep workers managing multiple cooking vessels. Commercial food processors — Robot Coupe (founded France, 1960; US market from 1973) became the standard institutional kitchen tool for large-volume slicing, dicing, and shredding — mechanized the volume cutting tasks that had previously required dedicated hand-cutting workers. HACCP (Hazard Analysis and Critical Control Points) compliance systems, mandated in school nutrition programs through USDA policy from the 1990s, added documentation and temperature-logging requirements to the prep worker role — the first significant administrative layer on what had previously been a purely physical job.

    Compliance systemsControls and audit files
  • Chowbotics "Sally" robot salad assembly (2014–2022) — the canonical automation failure

    Chowbotics was founded in 2014 with a specific thesis: the salad-assembly task performed by food preparation workers — reaching into bins of pre-cut vegetables, portioning each ingredient by weight, assembling in a bowl — was sufficiently repetitive and well-defined to be automated. Their robot, "Sally," was a vending-machine-sized unit with ingredient canisters that would dispense measured portions of pre-cut ingredients into a bowl on command. Sally was deployed in hospital cafeterias, corporate campuses, and hotel lobbies starting around 2016-2017. DoorDash acquired Chowbotics in February 2021 — reportedly for around $46 million — as part of an ambition to build automated food preparation into delivery kitchens. By June 2022, DoorDash shut Chowbotics down entirely. The reason: Sally cost approximately $35,000, required a human to stock, clean, and maintain it daily, could only assemble salads from pre-cut ingredients it did not itself cut, and competed against prep workers earning $13-16/hr who could perform a dozen tasks. The unit economics never closed against the labor cost it was designed to replace.

    Effect on the work

    Chowbotics' shutdown was the food-service automation sector's most instructive failure: a well-funded, purpose-built robotic system that attracted a $46 million acquisition by a major tech company but could not outcompete $14/hr labor when total ownership cost (purchase, cleaning, maintenance, human stocking labor) was accounted for. The failure reinforced the economics argument that food prep automation only closes financially when integrated into a restaurant designed around the robot from the ground up — not retrofitted into existing prep workflows.

    Work toolChanging equipment
  • Sweetgreen Infinite Kitchen — robotic assembly integrated from design (2021 Spyce acquisition, 2023 deployment)

    In August 2021, Sweetgreen acquired Spyce, a Boston startup founded by four MIT students that had operated a robotic fast-casual restaurant since 2018. Where Chowbotics tried to retrofit automation into existing cafeteria settings, the Spyce/Infinite Kitchen concept built the automation into the restaurant's design: a conveyor-based system that portions and assembles salad bowls from pre-cut ingredients held in temperature-controlled stations, integrated with digital ordering. Sweetgreen opened its first Infinite Kitchen location in Naperville, Illinois in May 2023. By Q1 2024, Infinite Kitchen locations were posting 28% restaurant-level profit margins — compared to 18.1% across the chain's standard locations. The key qualifier: the Infinite Kitchen's automation is confined to the assembly step — it does not cut, wash, or marinate. Human food preparation workers still perform all upstream prep. The automation eliminated the assembly-line worker for high-volume salad portioning at a purpose-built location; it has not eliminated the prep worker who cuts the vegetables those machines portion.

    Effect on the work

    The Infinite Kitchen model suggests that robotic bowl assembly can succeed when designed in rather than retrofitted — but its labor displacement is narrower than the headline suggests. Sweetgreen still employs food prep workers for vegetable cutting, protein cooking, and sauce preparation; the automation handles portioning and assembly. This is a task-substitution story rather than an occupation-substitution story, consistent with the pattern seen in Chipotle's Autocado avocado robot (which cores and peels avocados but does not make guacamole) and in Miso Robotics' Flippy (which manages fry baskets but not the surrounding kitchen).

    Work toolChanging equipment
Projection cone · present → 2034

What credible sources project

Scrub the slider past now to anchor each scenario on the scrubber. The spread is the range of futures credible sources project for this role.

Employment outlook
Projected change in the number of people doing this work.
O*NET / BLS Occupational Outlook 2024-34
2034
-3%
O*NET-summarized BLS employment projections for SOC 35-2021. Classified as "Decline (-1% or lower)" — consistent with the National Employment Matrix figure. 148,000 projected annual openings despite net contraction reflects the enormous replacement-need driven by turnover: food preparation workers typically leave the occupation within 1-3 years, creating a persistent hiring demand even when headcount is not growing. The occupation remains one of the most numerically large in the US food service sector — above 860,000 workers — despite the projected contraction.
BLS National Employment Matrix 2024-34
2034
-3.4%
BLS National Employment Matrix detailed projections for SOC 35-2021. Projected employment falls from 902,700 in 2024 to approximately 871,800 by 2034 — a decline of roughly 30,900 positions (-3.4%). The BLS projects mild headcount contraction driven by continued automation of assembly-line prep tasks in fast-casual restaurants (Sweetgreen Infinite Kitchen model, Chipotle Autocado/Hyphen), productivity improvements in institutional kitchens from better combi-oven and food-processor technology, and slower growth in commercial foodservice relative to the early 2020s recovery. The decline is offset by strong replacement needs: BLS projects 148,000 annual job openings through 2034, driven by the very high turnover characteristic of the occupation (annual turnover rates in food service consistently above 70%). This is a mild structural contraction, not an employment collapse.
Infinite Kitchen scale scenario (institutional automation)
2034
-15%
Industry scenario: if the Sweetgreen Infinite Kitchen model — which achieves 28% restaurant-level margins vs. the 18% chain average — scales to the broader fast-casual and institutional sectors, the assembly-line subset of food preparation work faces meaningful displacement. Sweetgreen has indicated plans to expand Infinite Kitchen to additional locations; if 10-20% of high-volume fast-casual and institutional cafeteria operations adopt similar integrated robotic assembly by 2034, the displacement of assembly-worker roles within the 35-2021 tier could approach 10-15% net reduction beyond the BLS baseline. This scenario is more pessimistic than BLS but consistent with the Infinite Kitchen unit economics: unlike the Chowbotics model, the Infinite Kitchen's 28% vs 18% margin advantage is a real financial case for institutional adoption at scale, if and when capital costs come down.
AI task exposure
Share of the role’s tasks that researchers estimate AI can do. This is a measure of task exposure, not a forecast of jobs lost.
Frey & Osborne (2013)
2030
30%
of tasks
Gaussian-process classifier on O*NET task features. Frey & Osborne (2013) rated food preparation workers at high probability of computerization — the repetitive nature of chopping, portioning, and assembling cold preparations placed the occupation in the high-automation-risk tier. The Chowbotics Sally failure (2014-2022) was a direct test of the F&O thesis: a robot designed specifically to perform the most repetitive subset of food prep assembly failed commercially not because the task was technically impossible to automate but because the economics of automation against $14/hr labor did not close. The -30% estimate represents the pessimistic interpretation of F&O — displacement of roughly one-third of the workforce through automation of the most repetitive task subset. The actual observed trajectory (mild -3.4% BLS projection through 2034) has not validated the F&O pessimism, consistent with the economics failure documented in the Chowbotics case.
Eloundou et al. — "GPTs are GPTs" (2023)
2028
1%
of tasks
GPT-4 task-by-task LLM exposure labeling on O*NET tasks for SOC 35-2021. Food preparation workers score very low on LLM exposure — the core tasks (cutting, portioning, washing, assembling) are physical and sensory tasks that a large language model cannot perform. Eloundou explicitly notes that physical-preparation occupations have near-zero direct LLM task substitution risk. The mild negative projection reflects the marginal case: AI-assisted ordering and inventory systems in institutional foodservice may slightly reduce the labor input per meal served (better demand forecasting means less food prepared in excess), but the physical prep work itself is not LLM-automatable. Displayed near the BLS baseline.
Today, in this role

What's shifting in the work right now

The historical view above shows how this role has moved. This is the present-day detail: which AI tools are picking up which tasks, where the edge still is, and the natural directions this work can grow.

What's changing in your day

Three parts of your work where AI is already doing real lifting, and what stays yours.

AI is taking this onOperate fryers and other cooking stations for high-volume prep items (fries, chicken tenders, onion rings): load baskets, monitor oil temperature and cook times, and ensure consistent output quality across hundreds of daily portions.

Operate fryers and other cooking stations for high-volume prep items (fries, chicken tenders, onion rings): load baskets, monitor oil temperature and cook times, and ensure consistent output quality across hundreds of daily portions.[6],[3]

Where your edge is

Learn Flippy or equivalent robotic fryer operation and maintenance so you are the crew member who keeps the robot running, not the one replaced by it. Robotic fryer installations still require human oversight for oil changes, basket cleaning, and exception handling when items jam or overflow.

AI is taking this onPrepare pizza, flatbread, and similar assembled items: apply sauce and cheese per recipe spec, distribute toppings evenly, and manage throughput to match oven capacity

Prepare pizza, flatbread, and similar assembled items: apply sauce and cheese per recipe spec, distribute toppings evenly, and manage throughput to match oven capacity; adapt for custom or dietary-modification orders.[7],[11]

Where your edge is

Where Picnic Works or similar systems are deployed, the operator role shifts to loading ingredients into the machine, clearing jams, and handling custom/modified orders the robot cannot process. Developing allergen awareness and custom-order fluency keeps the human role relevant.

AI is sitting alongside you hereAssemble cold food items, salads, wraps, and bowls according to standardized recipes: layer ingredients in correct sequence, apply dressings and toppings, and portion to spec for both in-person and digital orders.

Assemble cold food items, salads, wraps, and bowls according to standardized recipes: layer ingredients in correct sequence, apply dressings and toppings, and portion to spec for both in-person and digital orders.[4],[5]

Where your edge is

Develop the speed and accuracy to match robotic assembly output on in-person orders while learning to monitor and quality-check automated assembly for digital orders. Customizations, allergen substitutions, and guest-facing interaction remain human work.

Where this role is heading

Natural next steps for someone with your foundation: not exits, evolutions.

A direction you could grow

First-Line Supervisors of Food Preparation and Serving Workers

Food prep workers who demonstrate reliability, food safety knowledge, and the ability to manage task flow across a kitchen are the natural pipeline for shift supervisor and kitchen manager positions. The BLS projects supervisor openings to remain stable as restaurants need experienced humans to oversee robotic equipment and train new staff. Workers who document food safety compliance accurately and communicate with management proactively are typically promoted within 1-3 years.

What you'd add
  • · Food safety certification (ServSafe Manager or equivalent, one-day exam)
  • · Basic labor scheduling and cost-of-goods awareness
  • · Kitchen Display System and POS system proficiency
  • · Conflict resolution and team communication in a fast-paced environment
What it takesSome new skills to pick up
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The data behind this timeline

On record since1885
Latest tracked employment893,600 (US, 2025)
Latest median pay$35,320 (2025)
Outlook-3.4% by 2034 (BLS National Employment Matrix 2024-34)
View all 28 cited data points
YearUS employmentMedian annual paySource
1946300,000n/aESTIMATE
1950n/a$1,800ESTIMATE
1970600,000n/aESTIMATE
1980n/a$7,800ESTIMATE
2000840,000n/aBLS-OEWS
2003852,890$16,470BLS-OEWS
2004863,700$16,710BLS-OEWS
2005880,360$17,040BLS-OEWS
2006871,470$17,410BLS-OEWS
2007873,470$18,150BLS-OEWS
2008880,480$18,630BLS-OEWS
2009849,400$19,020BLS-OEWS
2010802,650$19,800BLS-OEWS
2011775,140$19,270BLS-OEWS
2012785,370$19,300BLS-OEWS
2013824,080$19,440BLS-OEWS
2014850,220$19,560BLS-OEWS
2015862,740$20,180BLS-OEWS
2016850,670$21,440BLS-OEWS
2017832,690$22,730BLS-OEWS
2018814,600$23,730BLS-OEWS
2019885,000$24,800BLS-OEWS
2020650,000$26,070ESTIMATE, BLS-OEWS
2021783,350$28,780BLS-OEWS
2022904,330$29,790BLS-OEWS
2023879,610$32,420BLS-OEWS
2024902,700$34,220BLS-OEWS
2025893,600$35,320BLS-OEWS
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