Share and intensity of work current AI systems can materially affect.
SOC 35-2015
Cooks, Short Order AI displacement risk
Short-order cooks grill, fry, and plate food to order in diners and counters. Robotic fryers and automated grills now handle the most repetitive stations in chain kitchens, but the diner reality — simultaneous tickets, custom requests, and equipment that breaks mid-rush — still rewards a fast human cook.
Likely potential for exposed tasks to move to software after workflow integration.
Automation lands first in high-volume chains where menus are standardized, and that is where short-order employment concentrates. Independent diners and hybrid kitchens keep the role alive, but this is honest moderate pressure.
Distribution
Where Cooks, Short Order sits across 620 tracked roles
Displacement pressure 34 — higher than 56% of the 620 occupations tracked on displacement.ai.
Score version
This page uses Seed model v0.4 (seed-v0.4-2026-05), last reviewed 2026-08-15. Directional occupation-level planning model using hand-reviewed public research, task exposure estimates, wage context, and transition-pathway assumptions.
11 O*NET task statements matched to SOC 35-2015. The displayed task profile combines these official task statements with the current public score model.
Median wage context: $35,880 (May 2025, US national). The latest BLS row matched SOC 35-2015.
Scores are planning signals, not forecasts. Local hiring demand, employer-specific workflows, licensing, and credentials must be validated before making career decisions.
2030 economic stress test
How Anthropic's scenarios classify Cooks, Short Order
SOC 35-2015 places this role in the paper's all-other occupation group. These group-level outcomes do not change the 34/100 role score and are not an occupation forecast.
+1.1% group wage
Employment rises and unemployment falls for the all-other group, but the paper does not publish a separate group rate.
Economy-wide: +1.6% GDP and 3.9% unemployment.
+5.9% group wage
Employment rises and unemployment falls for the all-other group, but the paper does not publish a separate group rate.
Economy-wide: +8.3% GDP and 4.6% unemployment.
+33.6% group wage
Employment rises and unemployment falls for the all-other group, but the paper does not publish a separate group rate.
Economy-wide: +32.4% GDP and 11.9% unemployment.
Compare the assumptions and limitations across all three scenarios. Source: The Anthropic Institute Working Paper No. 2026-02.
Official task evidence
O*NET task matches for Cooks, Short Order
The current evidence import matched 11 task statements from Task Statements 31.0 (August 2026). These rows are used as a grounding layer for judging which parts of the occupation are repeatable, language-heavy, analytical, social, physical, or compliance-sensitive.
Dataset31.0 (August 2026)
Matched tasks11
SOC35-2015
- Core task / ID 2187
Clean food preparation equipment, work areas, and counters or tables.
- Core task / ID 18725
Restock kitchen supplies, rotate food, and stamp the time and date on food in coolers.
- Core task / ID 2192
Complete orders from steam tables, placing food on plates and serving customers at tables or counters.
- Core task / ID 2188
Plan work on orders so that items served together are finished at the same time.
- Core task / ID 2189
Grill, cook, and fry foods such as french fries, eggs, and pancakes.
- Core task / ID 18726
Perform food preparation tasks, such as making sandwiches, carving meats, making soups or salads, baking breads or desserts, and brewing coffee or tea.
Source: O*NET Resource Center, Task Statements. Raw import target: data/raw/onet/task-statements-31-0.txt.
Task profile
Where AI changes the work
Grill, cook, and fry foods to order
Exposure 30, automation 15%, augmentation 36%.
O*NET evidence: Grill, cook, and fry foods such as french fries, eggs, and pancakes. (ID 2189)
Plan work so items finish simultaneously
Exposure 36, automation 17%, augmentation 40%.
O*NET evidence: Plan work on orders so that items served together are finished at the same time. (ID 2188)
Take orders and cook short-preparation foods
Exposure 34, automation 17%, augmentation 38%.
O*NET evidence: Take orders from customers and cook foods requiring short preparation times, according ... (ID 2190)
Restock supplies and rotate food
Exposure 30, automation 14%, augmentation 34%.
O*NET evidence: Restock kitchen supplies, rotate food, and stamp the time and date on food in coolers. (ID 18725)
TaskExposureAutomationAugmentation
Grill, cook, and fry foods to order3015%36%
Plan work so items finish simultaneously3617%40%
Take orders and cook short-preparation foods3417%38%
Restock supplies and rotate food3014%34%
Transition pathways
Adjacent moves that preserve existing skills
role redesign
ModerateKitchen Supervisor
Training horizon: 6-12 months. Skill overlap 66. Wage preservation signal 116.
- Lead line teams
- Own station training
- Manage food costs
role redesign
ModerateCatering Cook
Training horizon: 6-12 months. Skill overlap 58. Wage preservation signal 110.
- Build event-menu skills
- Run off-site kitchens
- Grow client bookings
Comparison guides
Compare the next move before you commit
6-12 months
Cooks, Short Order to Kitchen Supervisor
Compare AI displacement pressure, wage preservation, skill overlap, training time, and first proof project for moving from Cooks, Short Order into Kitchen Supervisor.
6-12 months
Cooks, Short Order to Catering Cook
Compare AI displacement pressure, wage preservation, skill overlap, training time, and first proof project for moving from Cooks, Short Order into Catering Cook.
What the AI risk score means for Cooks, Short Order
The displacement pressure score for Cooks, Short Order is 34. That score blends task exposure, automation pressure, augmentation potential, wage vulnerability, transition feasibility, and source confidence. It is designed to help workers and workforce teams decide where to act first, not to claim a specific date when a job will disappear.
For this role, the clearest risk pattern is visible at the task level. Plan work so items finish simultaneously carries 17% automation pressure, while Plan work so items finish simultaneously carries 40% augmentation potential. That means the best response is usually a targeted redesign of work: move away from repeatable production tasks and toward judgment, exception handling, coordination, stakeholder context, and accountable use of AI tools.
Labor-market context and wage risk
Median wage: $35,880 (May 2025, US national). Employment context: Speed-line cooking where kitchen robots target the grill. Typical education: High school plus on-the-job training.
Wage vulnerability is 72, while transition feasibility is 60. A high wage-vulnerability score means workers should pay close attention to salary preservation before making a move. A high transition-feasibility score means there are adjacent paths that can reuse existing skills without requiring a complete career reset.
- Moderate displacement pressure
- Chain kitchens automate fry stations
- Ticket juggling stays human for now
Upskilling priorities
Skills that make this role more resilient
The safest upskilling plan starts with skills already close to the work. For Cooks, Short Order, the strongest near-term skill priorities are listed below. These are useful whether the goal is to stay in the role, move to a redesigned version of the role, or transition into an adjacent occupation.
Short-order cooking
Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.
Speed and accuracy
Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.
Food safety
Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.
Kitchen equipment
Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.
90-day transition plan
The most practical next step is not to wait for a layoff or a full role redesign. Use the next 90 days to create evidence that you can operate in a safer, more AI-augmented version of the work.
- In the first 30 days, document the repetitive tasks in your current work and identify where AI can reduce drafting, lookup, classification, or reporting time.
- By 60 days, complete one small project connected to Kitchen Supervisor, such as lead line teams.
- By 90 days, compare internal openings and external postings for Kitchen Supervisor or Catering Cook and update your resume around measurable workflow outcomes.
FAQ
Questions about AI and Cooks, Short Order
Will AI replace Cooks, Short Order?
Short-order cooks grill, fry, and plate food to order in diners and counters. Robotic fryers and automated grills now handle the most repetitive stations in chain kitchens, but the diner reality — simultaneous tickets, custom requests, and equipment that breaks mid-rush — still rewards a fast human cook. The better planning signal is not full replacement, but which tasks become automated, which tasks become AI-assisted, and which responsibilities still need human judgment.
Which parts of Cooks, Short Order work are most exposed to AI?
Plan work so items finish simultaneously and Take orders and cook short-preparation foods show the strongest automation pressure in this model. Plan work so items finish simultaneously and Take orders and cook short-preparation foods are better treated as AI-augmented work.
What should Cooks, Short Order learn next?
Start with Short-order cooking, Speed and accuracy, Food safety. The most practical adjacent paths in this model are Kitchen Supervisor and Catering Cook.
How should this score be used?
Use it as a planning signal, not a prediction. Confirm local hiring demand, wages, licensing, credentials, and employer adoption before making a career move.
Sources
Evidence trail
OECD / 11 July 2023OECD Employment Outlook 2023: Artificial Intelligence and the Labour MarketMcKinsey Global Institute / 26 July 2023Generative AI and the Future of Work in AmericaO*NET Resource Center / Database 31.0 (August 2026)Occupation, Task, Skill, and Work-Activity DataUS Bureau of Labor Statistics / May 2025 estimates (released 15 May 2026)Occupational Employment and Wage Statistics