Share and intensity of work current AI systems can materially affect.
SOC 35-2014
Cooks, Restaurant AI displacement risk
Kitchen robotics handle some frying and assembly in high-volume chains, but most restaurant cooking is variable, sensory, and fast-adapting work. Seasoning judgment, timing across stations, and quality control remain human skills kitchens struggle to staff.
Likely potential for exposed tasks to move to software after workflow integration.
Chronic cook shortages matter more than automation for near-term job security. Robotics concentrate in standardized quick-service formats, not the full-service kitchens where most cooks work.
Distribution
Where Cooks, Restaurant 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 2026-08-08. Directional occupation-level planning model using hand-reviewed public research, task exposure estimates, wage context, and transition-pathway assumptions.
20 O*NET task statements matched to SOC 35-2014. The displayed task profile combines these official task statements with the current public score model.
Median wage context: $37,390 (May 2025, US national). The latest BLS row matched SOC 35-2014.
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, Restaurant
SOC 35-2014 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, Restaurant
The current evidence import matched 20 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 tasks20
SOC35-2014
- Core task / ID 18723
Ensure food is stored and cooked at correct temperature by regulating temperature of ovens, broilers, grills, and roasters.
- Core task / ID 18722
Inspect and clean food preparation areas, such as equipment, work surfaces, and serving areas, to ensure safe and sanitary food-handling practices.
- Core task / ID 2173
Portion, arrange, and garnish food, and serve food to waiters or patrons.
- Core task / ID 18724
Ensure freshness of food and ingredients by checking for quality, keeping track of old and new items, and rotating stock.
- Core task / ID 2170
Season and cook food according to recipes or personal judgment and experience.
- Core task / ID 2180
Coordinate and supervise work of kitchen staff.
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
Cook and season dishes
Exposure 20, automation 10%, augmentation 20%.
O*NET evidence: Season and cook food according to recipes or personal judgment and experience. (ID 2170)
Portion, plate, and garnish food
Exposure 28, automation 18%, augmentation 22%.
O*NET evidence: Portion, arrange, and garnish food, and serve food to waiters or patrons. (ID 2173)
Manage food safety and sanitation
Exposure 30, automation 14%, augmentation 38%.
Estimate supplies and rotate stock
Exposure 46, automation 26%, augmentation 44%.
O*NET evidence: Estimate expected food consumption, requisition or purchase supplies, or procure food f... (ID 2178)
TaskExposureAutomationAugmentation
Cook and season dishes2010%20%
Portion, plate, and garnish food2818%22%
Manage food safety and sanitation3014%38%
Estimate supplies and rotate stock4626%44%
Transition pathways
Adjacent moves that preserve existing skills
role redesign
ModerateSous Chef
Training horizon: 6-12 months. Skill overlap 80. Wage preservation signal 128.
- Lead a station independently
- Learn inventory and costing
- Coach line cooks
adjacent role
ModerateKitchen Manager
Training horizon: 6-12 months. Skill overlap 72. Wage preservation signal 140.
- Own food cost tracking
- Manage vendor orders
- Run safety compliance checks
Comparison guides
Compare the next move before you commit
6-12 months
Cooks, Restaurant to Sous Chef
Compare AI displacement pressure, wage preservation, skill overlap, training time, and first proof project for moving from Cooks, Restaurant into Sous Chef.
6-12 months
Cooks, Restaurant to Kitchen Manager
Compare AI displacement pressure, wage preservation, skill overlap, training time, and first proof project for moving from Cooks, Restaurant into Kitchen Manager.
What the AI risk score means for Cooks, Restaurant
The displacement pressure score for Cooks, Restaurant 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. Estimate supplies and rotate stock carries 26% automation pressure, while Estimate supplies and rotate stock carries 44% 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: $37,390 (May 2025, US national). Employment context: Very large kitchen workforce with persistent shortages. Typical education: No formal educational credential.
Wage vulnerability is 72, while transition feasibility is 62. 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.
- Low to moderate displacement pressure
- Labor shortages persist
- Robotics target chain kitchens first
Upskilling priorities
Skills that make this role more resilient
The safest upskilling plan starts with skills already close to the work. For Cooks, Restaurant, 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.
Station management
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.
Sensory quality judgment
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.
Timing under pressure
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 Sous Chef, such as lead a station independently.
- By 90 days, compare internal openings and external postings for Sous Chef or Kitchen Manager and update your resume around measurable workflow outcomes.
FAQ
Questions about AI and Cooks, Restaurant
Will AI replace Cooks, Restaurant?
Kitchen robotics handle some frying and assembly in high-volume chains, but most restaurant cooking is variable, sensory, and fast-adapting work. Seasoning judgment, timing across stations, and quality control remain human skills kitchens struggle to staff. 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, Restaurant work are most exposed to AI?
Estimate supplies and rotate stock and Portion, plate, and garnish food show the strongest automation pressure in this model. Estimate supplies and rotate stock and Manage food safety and sanitation are better treated as AI-augmented work.
What should Cooks, Restaurant learn next?
Start with Station management, Sensory quality judgment, Food safety. The most practical adjacent paths in this model are Sous Chef and Kitchen Manager.
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
International Labour Organization / 20 May 2025Generative AI and Jobs: A Refined Global Index of Occupational ExposureO*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