Skip to sources
Time Machine

Cooks, Restaurant

Scrub through 209years 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
1850187519001925195019752000now
Country
2026
Known today as Cooks, Restaurant (BLS SOC 35-2014)
US Employment
1.41M
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
$37,390
≈ $36,431 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.

  • Open-hearth fireplace + hand tools (tavern and early restaurant kitchen)

    The kitchen of the early American tavern and the first American restaurants was built on fire management: an open hearth or brick oven fueled by wood, iron pots and spits, and the cook's ability to judge heat by hand and eye. American taverns of the late 18th century featured a single hearth serving an entire kitchen — soups, roasts, and breads competing for position around a single heat source. Delmonico's opened in 1827 with coal and wood ranges; the cook's central skill was temperature management across multiple preparations without independent heat zones. Knives were the precision instrument: a skilled cook could butcher, fabricate, and portion with tools that have not materially changed in two centuries.

    Work toolChanging equipment
  • Commercial gas range + commercial cast-iron range (urban restaurant kitchen)

    Commercial gas ranges reached American city restaurants by the 1860s-1880s as urban gas infrastructure expanded. The enclosed cast-iron range with multiple independent burners gave line cooks simultaneous independent heat zones for the first time — making it physically possible to hold a beurre blanc and a braise and a sauté simultaneously without competing for position around a single hearth. Alexis Soyer had demonstrated gas cooking at the Reform Club in London in 1841; by the 1870s American manufacturers including Garland (founded 1864) were producing commercial ranges for hotel and restaurant use. This tool shift enabled the Escoffier brigade model: multiple cooks at a single range line, each managing their own station at independent temperatures.

    Work toolChanging equipment
  • Horn & Hardart Automat steam tables + batch production (1902-1991)

    Horn & Hardart opened the first American Automat in Philadelphia in 1902 — coin-operated compartments dispensing pre-prepared food held in steam tables. At its peak the Automat was the largest restaurant chain in the world (over 80 New York locations), feeding hundreds of thousands of daily customers with no table service and a cooking model built on large-batch production: soups, stews, pot pies, and baked goods produced in quantity and portioned on demand. For the cooks who worked the Automat prep kitchens (hidden from view, unlike the public compartments), this was the first industrial model of restaurant cooking — volume production, standardized recipes, and batch replenishment rather than à la carte cooking to order. The Automat closed its last location in New York on April 9, 1991.

    Mainframe processingComputerized records
  • Escoffier brigade system + mise-en-place discipline (Le Guide Culinaire, 1903)

    Escoffier's Le Guide Culinaire (1903) codified the brigade de cuisine — the military-style kitchen hierarchy that became the organizing principle of every serious professional kitchen. For the line cook, the brigade system meant a defined station (saucier, rôtisseur, entremetier, garde manger), a defined mise-en-place (everything prepped and in place before service), and a defined chain of command. The cook's job became the mastery of a specific station's techniques rather than generalist competence. Hotel restaurants in New York, Chicago, and San Francisco adopted the brigade model through the 1910s and 1920s; as the model spread to casual dining through the 1930s and 1940s, it created the organizational template that fast-food kitchens would later industrial-rationalize.

    Work toolChanging equipment
  • McDonald's Speedee Service System — flat-top griddle + dedicated fry station (1948)

    In 1948 Richard and Maurice McDonald redesigned their San Bernardino drive-in around industrial engineering principles they called the Speedee Service System: a large flat-top griddle for burger patties, a dedicated french-fry station with commercial deep fryers, a milkshake machine bank, and an assembly line for condiment and bun preparation. Each cook did one repetitive task at high speed. The first McDonald's kitchen produced a hamburger in 30 seconds — faster than any short-order cook of the era. Ray Kroc observed the system in 1954 and began franchising in 1955; by 1963 McDonald's was selling one million hamburgers per day. The Speedee Service System is the direct ancestor of every fast-food kitchen operating today — and of the automation thesis, because a kitchen built on single-task repetition is inherently more automatable than one built on artisanal judgment.

    Effect on the work

    The Speedee Service System deskilled the fast-food kitchen relative to the Escoffier brigade: cooks no longer needed years of training, they needed days. This enabled rapid staffing of hundreds of identical kitchens but also created the conditions (single-task repetition, no craft learning) that eventually made fry stations automatable. The two-tier kitchen economy — skilled line cooks in full-service restaurants, deskilled fast-food workers — became structurally entrenched.

    Work toolChanging equipment
  • Commercial microwave oven (Amana Radarange 1967) + commercial refrigeration expansion

    Amana introduced the first practical countertop microwave oven in 1967 (the Radarange, $495 retail). Commercial adoption in restaurant kitchens was rapid: by the late 1970s, most full-service and casual-dining restaurants used commercial microwave units for reheating, holding temperature, and accelerating prep tasks that did not require browning. The microwave was a genuine labor multiplier for the restaurant kitchen: a single cook with a microwave could handle tasks that previously required a second burner and constant attention. Combined with the expansion of commercial walk-in refrigeration, it enabled the shift from fully à la minute cooking toward partially par-cooked production, transforming kitchen prep economics across the industry.

    Work toolChanging equipment
  • POS ticket printer + kitchen display system (KDS) — digital order management

    The kitchen display system — a screen at the cook's station showing active tickets rather than printed paper — entered full-service restaurants through the 1990s and 2000s. Aloha Technologies (founded 1986), Micros Systems, and later Toast (founded 2013) built KDS units into their POS ecosystems. For the line cook, the KDS replaced the handwritten paper dupe and the shouted expo call with a visual queue: each ticket displayed on screen, fired in order, bumped when complete. The KDS did not change what the cook cooked, but it changed how the line managed throughput — cooks could see total ticket load at a glance, expeditors could call without paper, and the kitchen's rhythm became data-visible for the first time. By 2010, KDS was standard equipment in any full-service restaurant with a modern POS installation.

    Work toolChanging equipment
  • Miso Robotics Flippy + fry-station automation (CaliBurger 2018; White Castle 2020+)

    In March 2017, Miso Robotics unveiled Flippy — an AI-powered robot arm designed to flip burger patties and manage a commercial fry station. Its first deployment at CaliBurger in Pasadena in 2018 lasted two days before the surrounding human team could not keep pace with the robot's output; the deployment was paused for workflow redesign. White Castle deployed Flippy 2.0 in 2020 and expanded the program. As of 2023, Miso Robotics reported deployments at Jack in the Box, White Castle, and other fast-food chains. Flippy handles fry station tasks — dropping baskets, monitoring cook times, lifting baskets, draining oil — continuously without fatigue. It does not plate, season, expedite, or interact with the broader kitchen. The constraint is not the robot's capability but the workflow integration: a fry station inside a working kitchen requires constant human coordination that a single-task robot arm cannot manage alone.

    Effect on the work

    Miso Robotics' own figures suggest Flippy can replace 1-2 dedicated fry station workers per shift at high-volume fast-food locations. At White Castle, Flippy operates alongside human cooks rather than replacing them entirely — the robot handles the repetitive fry-station tasks while human cooks manage the rest of the kitchen. The displacement is real but narrow: confined to the specific repetitive subset of restaurant cook work that most closely resembles a single-axis industrial robot's capabilities.

    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.
BLS Occupational Outlook Handbook 2023-33
2033
+6%
BLS Employment Projections 2023-33 cycle. Published change for SOC 35-2014: +6% ("As fast as average"), approximately 1,217,500 projected jobs by 2033 (up from 1,148,600 in 2023), with roughly 200,000+ annual openings projected driven primarily by very high turnover. BLS models continued demand growth from restaurant industry expansion, ghost-kitchen proliferation, and post-COVID recovery. The projection explicitly does not model meaningful automation displacement because the BLS task-exposure model for 35-2014 assigns high automation risk only to the repetitive single-task subset (frying, slicing) while the coordination and judgment tasks of a multi-station kitchen remain human.
BLS National Employment Matrix 2024-34
2034
+6%
BLS National Employment Matrix detailed projections for SOC 35-2014. Full-service restaurants and limited-service eating places both show growth; healthcare foodservice and ghost-kitchen operations add to the base. The matrix models sectoral demand shifts but projects net positive employment for restaurant cooks through 2034. Automation deployments (Flippy, Hyphen, Infinite Kitchen) are implicitly modeled as displacing fast-food workers more than the restaurant-cook category, which concentrates in full-service and fast-casual kitchens where multi-task coordination still requires human cooks.
Ghost-kitchen expansion + robotization-acceleration scenario
2030
-10%
Industry-scenario combining two countervailing forces. Downside: if Miso Robotics' Flippy scales to 10,000+ fast-food locations and Chipotle's Hyphen makeline rolls out chain-wide, the repetitive-station subset of the restaurant cook workforce (estimated at roughly 15-20% of total employment — fry station, cold prep, assembly line) could be displaced. Upside: ghost-kitchen proliferation continues, adding net new cooking establishments that require human kitchen crews. The -10% scenario models the displacement exceeding the ghost-kitchen offset — roughly 115,000 positions eliminated net over the period. This is more pessimistic than BLS OOH but less extreme than F&O; it represents the realistic automation scenario if current pilots scale commercially.
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
25%
of tasks
Gaussian-process classifier on O*NET task features. Frey & Osborne (2013) rated restaurant cooks among the highest-probability-of-computerization occupations in their study — approximately 0.96 probability, placing them in the top decile of automation risk. The F&O algorithm detected high repetition rates, limited social intelligence requirements, and physical-task patterns it associated with robotic substitution. A decade later, the prediction has partially materialized (fry station robots, avocado-prep robots, bowl-assembly makelines) but the wholesale employment displacement implied by a 0.96 score has not: restaurant cook employment in 2023 is near its all-time high. The -25% estimate here represents the pessimistic interpretation of the F&O score — displacement of roughly one-quarter of the workforce through automation of the most repetitive station tasks. Displayed as the pessimistic tail of the uncertainty cone.
Eloundou et al. — "GPTs are GPTs" (2023)
2028
2%
of tasks
GPT-4 task-by-task LLM exposure labeling on O*NET tasks for SOC 35-2014. Restaurant cooks score very low on LLM exposure — the core tasks (cooking proteins, building sauces, managing station prep, executing mise-en-place, expediting) 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 small positive projection reflects the augmentation scenario: AI tools that handle inventory forecasting, recipe costing, and scheduling for the kitchen management layer potentially make the restaurant more efficient and sustainable, supporting steady employment rather than displacing it.
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 onExecute high-volume fry-station production at QSR and fast-casual settings, managing fryer baskets, timer coordination, and hold times across multiple simultaneous orders — a task where Miso Robotics Flippy (120 baskets/hour, 40+ fried food types) now handles physical execution at a growing subset of White Castle and other QSR deployments.

Execute high-volume fry-station production at QSR and fast-casual settings, managing fryer baskets, timer coordination, and hold times across multiple simultaneous orders — a task where Miso Robotics Flippy (120 baskets/hour, 40+ fried food types) now handles physical execution at a growing subset of White Castle and other QSR deployments.[5],[12]

Where your edge is

Fry-station robotics are deployed and improving — Flippy's latest generation is twice as fast as earlier models and 75% cheaper to install. In a QSR kitchen where Flippy is installed, the cook's role shifts to loading, quality oversight, troubleshooting, and handling the exceptions the robot misses. Build skills that travel across station types (grill, sauté, prep) so your value doesn't hinge on a single high-automation position. Full-service and scratch kitchens remain far from robotic fry automation.

AI is taking this onAssist with high-volume repetitive prep tasks — chopping vegetables, processing bulk ingredients, assembling standardized menu components — at fast-casual chains where automated assembly systems like Sweetgreen's Infinite Kitchen (500 bowls/hour) and Chipotle's Autocado avocado robot (26 seconds per avocado) are progressively absorbing the most structured portions of this work.

Assist with high-volume repetitive prep tasks — chopping vegetables, processing bulk ingredients, assembling standardized menu components — at fast-casual chains where automated assembly systems like Sweetgreen's Infinite Kitchen (500 bowls/hour) and Chipotle's Autocado avocado robot (26 seconds per avocado) are progressively absorbing the most structured portions of this work.[13],[14]

Where your edge is

Standardized bulk prep — the most repetitive, highest-volume assembly tasks — is exactly what fast-casual automation targets first. Sweetgreen's Infinite Kitchen processes 500 bowls/hour and Chipotle's Autocado halves guacamole prep time. If you're in a fast-casual kitchen, develop skills that travel beyond the automated stations: sauce and seasoning development, quality supervision of the automated output, and the ability to spot when the machine's output falls short of standard. In full-service settings, the premium is on technique-intensive prep (butchering, charcuterie, pastry work) that automated systems have not approached.

AI is sitting alongside you hereTrack and manage ingredient freshness — rotating stock (FIFO), checking for quality on delivery, and flagging items approaching end of shelf life — with AI food-waste tracking systems like Winnow VisionAI automatically identifying and weighing discarded items to surface waste patterns chefs can act on.

Track and manage ingredient freshness — rotating stock (FIFO), checking for quality on delivery, and flagging items approaching end of shelf life — with AI food-waste tracking systems like Winnow VisionAI automatically identifying and weighing discarded items to surface waste patterns chefs can act on.[15],[10]

Tools picking this up
Where your edge is

Winnow VisionAI and similar systems automatically log every item thrown away (scale + camera recognition trained on 500M+ images) and deliver daily waste reports to kitchen leadership. Cooks who engage with these reports — understanding which prep items are consistently over-produced, which raw ingredients arrive in poor condition — drive the operational decisions (adjusted par levels, supplier conversations, menu tweaks) that actually close the waste loop. A 64% waste reduction at Guckenheimer's multi-site operations (2025 case study) reflects both the tool and the cook behavior it enables.

Where this role is heading

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

A direction you could grow

Chefs and Head Cooks

The most direct career progression from restaurant cook: accumulating technique depth, station mastery, and culinary leadership experience across multiple years is the documented path to sous chef and head chef roles. BLS projects 6% growth for Chefs and Head Cooks through 2034 and the median wage is substantially higher (~$60K vs. ~$37K for cooks). Chefs and head cooks who direct kitchen operations, develop menus, and manage the culinary team carry substantially more human advantage — the creative, supervisory, and food-business judgment that robots and AI prep tools do not exercise. AI literacy (understanding Winnow data, KDS analytics, prep forecasting) becomes a differentiator for cooks angling toward kitchen leadership: demonstrating you can optimize kitchen economics, not just cook well, is the language head chef candidates need to speak in a data-driven restaurant.

What you'd add
  • · Multi-station mastery: work every station in the kitchen across multiple service types before moving up
  • · Culinary fundamentals at the professional level: stocks, mother sauces, butchery, pastry basics — ServSafe Manager certification
  • · Menu costing: recipe costing, food cost percentage targets, portion control against yield data
  • · Team leadership fundamentals: scheduling coordination, shift briefings, training junior cooks
  • · AI kitchen analytics literacy: reading Winnow waste reports and ClearCOGS prep recommendations to make data-backed kitchen decisions
What it takesSome new skills to pick up
Share this year
Drops anyone you send it to straight into 2026.
Preview card
Part of Food Service · see all 14roles →
Different role?

See the same long-arc view for your own profession.

Browse the directory by industry, or search by title or SOC code. New roles ship every few weeks. Every profile cites every claim.

Browse all roles

The data behind this timeline

On record since1827
Latest tracked employment1,409,890 (US, 2025)
Latest median pay$37,390 (2025)
Outlook+6% by 2033 (BLS Occupational Outlook Handbook 2023-33)
View all 29 cited data points
YearUS employmentMedian annual paySource
1900200,000n/aESTIMATE
1948400,000n/aESTIMATE
1950n/a$2,400ESTIMATE
1980n/a$9,200ESTIMATE
1990870,000n/aBLS-OEWS
2000870,000n/aBLS-OEWS
2003734,870$19,260BLS-OEWS
2004765,670$19,520BLS-OEWS
2005791,450$19,840BLS-OEWS
2006825,840$20,340BLS-OEWS
2007878,990$21,220BLS-OEWS
2008899,620$21,990BLS-OEWS
2009898,820$22,170BLS-OEWS
2010900,000$23,130BLS-OEWS
2011947,060$22,080BLS-OEWS
20121,000,710$22,030BLS-OEWS
20131,057,550$22,160BLS-OEWS
20141,104,790$22,490BLS-OEWS
20151,150,760$23,100BLS-OEWS
20161,217,370$24,140BLS-OEWS
20171,276,510$25,180BLS-OEWS
20181,340,810$26,530BLS-OEWS
20191,166,500$27,790BLS-OEWS
2020700,000$28,800ESTIMATE, BLS-OEWS
20211,193,860$30,010BLS-OEWS
20221,321,480$32,280BLS-OEWS
20231,148,600$35,780BLS-OEWS
20241,193,700$35,020BLS-OEWS
20251,409,890$37,390BLS-OEWS
Embed this timeline on your site

Free for any site. Paste this where the timeline should appear; it stays interactive, every datapoint stays cited, and it sets no cookies on your page. How embedding works

<iframe src="https://futurehistory.earth/embed/35-2014"
  width="100%" height="430" style="border:0"
  title="Cooks, Restaurant, a Future History timeline"
  loading="lazy"></iframe>

See all roles in Food Service