Gini Loh System Tools

AI Automation Index

Will AI Replace Cooks, Restaurant?

Task-level automation exposure for Cooks, Restaurant: 20 O*NET tasks scored against their work activities, plus the simulator.

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Developed & audited by Gini Loh

Automation Exposure

22% weighted task index

20 of 20 tasks scored

Median Salary

$37,390 / year

BLS OEWS, May 2025 — this exact occupation

Employment Level

Very High

1,409,890 people hold this job — size, not growth

Projected 2025–35

+12.1% employment change

218,600 openings a year · BLS line item

Pay by state

BLS OEWS publishes 54 state estimates for this occupation. Each is its own survey estimate, not the national median adjusted for local prices.

$22,950 – $46,800

Highest medians

Washington $46,800
District of Columbia $46,130
Massachusetts $45,600
Hawaii $45,420
Vermont $45,390

Lowest medians

Guam $22,950
Puerto Rico $24,650
Louisiana $29,050
Mississippi $29,560
West Virginia $29,590

State figures come from the 35-2014 row in the May 2025 state panel. States where the estimate was suppressed or too small to publish are absent.

What the score is made of

Each task is mapped to its work activities, scored for AI automation potential, and weighted by how important those activities are to the job. These are the components.

Automation potential 22%

Importance-weighted mean of the scored tasks. This is the headline index.

Physical work 63%

Share of weighted tasks in hands-on or machine-operating work activities.

Judgment & influence 15%

Share in analysis, decisions, teaching, directing, advising, or caring for others.

Routine administration 4%

Share in documenting, recording, and administrative activities.

Rewritten by O*NET 0%

Share of weighted tasks O*NET rewrote in a recent update. Reported, not folded into the score.

Consequence of error 17/100 Low

O*NET's own rating of how serious an uncorrectable mistake would be here — respondents, not us. Deliberately not in the index: the score measures what AI can do with the task content, and multiplying it by stakes would be our judgment dressed as data.

Constituent Task Mix

20 tasks for this occupation, weighted by work-activity importance. Shares below are of total task weight, not task count.

High exposure (≥ 60% of the task is automatable) 10%

3 tasks

Medium exposure (≥ 35%) 16%

3 tasks

Low exposure (below 35%) 75%

14 tasks

How would you survive?

Move your week away from the high-exposure tasks and toward the ones that need judgment. The simulator recalculates the index as you shift the mix.

Simulate Upskilling →

Constituent Tasks

#18723 · Core · 42% automatable

Ensure food is stored and cooked at correct temperature by regulating temperature of ovens, broilers, grills, and roasters.

decision support — AI can interpret readings but hands-on assessment is human

Assess equipment functioning.
#18722 · Core · 16% automatable

Inspect and clean food preparation areas, such as equipment, work surfaces, and serving areas, to ensure safe and sanitary food-handling practices.

visual inspection — Physical conformance inspection of facilities/equipment

Inspect facilities, equipment or supplies to ensure conformance to standards. Clean food preparation areas, facilities, or equipment.
#2173 · Core · 6% automatable

Portion, arrange, and garnish food, and serve food to waiters or patrons.

physical manipulation — Plating food is fine manual dexterity

Serve food or beverages. Arrange food for serving.
#18724 · Core · 46% automatable

Ensure freshness of food and ingredients by checking for quality, keeping track of old and new items, and rotating stock.

data analysis — Inventory tracking and reorder logic largely automatable

Check quality of foods or supplies. Maintain food, beverage, or equipment inventories.
#2170 · Core · 6% automatable

Season and cook food according to recipes or personal judgment and experience.

physical manipulation — Cooking requires hands-on manipulation of real food

Cook foods.
#2180 · Core · 30% automatable

Coordinate and supervise work of kitchen staff.

interpersonal — Coordinating food service staff is live supervisory work

Coordinate activities of food service staff.
#2176 · Core · 6% automatable

Bake, roast, broil, and steam meats, fish, vegetables, and other foods.

physical manipulation — Cooking requires hands-on manipulation of real food

Cook foods.
#2172 · Core · 19% automatable

Weigh, measure, and mix ingredients according to recipes or personal judgment, using various kitchen utensils and equipment.

physical manipulation — Physical measuring of ingredients by hand

Measure ingredients. Mix ingredients.
#2169 · Core · 6% automatable

Turn or stir foods to ensure even cooking.

physical manipulation — Cooking requires hands-on manipulation of real food

Cook foods.
#2171 · Core · 20% automatable

Observe and test foods to determine if they have been cooked sufficiently, using methods such as tasting, smelling, or piercing them with utensils.

visual inspection — Food/supply quality check is sensory and physical

Check quality of foods or supplies.
#2175 · Core · 5% automatable

Substitute for or assist other cooks during emergencies or rush periods.

physical manipulation — Hands-on kitchen assistance

Assist chefs or caterers with food or drink preparation.
#2177 · Core · 5% automatable

Wash, peel, cut, and seed fruits and vegetables to prepare them for consumption.

physical manipulation — Manual food preparation

Prepare foods for cooking or serving.
#2183 · Core · 6% automatable

Bake breads, rolls, cakes, and pastries.

physical manipulation — Dough handling is tactile physical craft

Prepare breads or doughs.
#2179 · Core · 5% automatable

Carve and trim meats such as beef, veal, ham, pork, and lamb for hot or cold service, or for sandwiches.

physical manipulation — Hands-on food cutting

Cut cooked or raw foods.
#2185 · Supplemental · 82% automatable

Keep records and accounts.

data analysis — Record production data into structured logs

Record operational or production data.
#2184 · Supplemental · 6% automatable

Prepare relishes and hors d'oeuvres.

physical manipulation — Cooking requires hands-on manipulation of real food

Cook foods.
#2178 · Supplemental · 67% automatable

Estimate expected food consumption, requisition or purchase supplies, or procure food from storage.

decision support — Ordering via systems automatable; human approves spend

Estimate supplies, ingredients, or staff requirements for food preparation activities. Order materials, supplies, or equipment.
#2181 · Supplemental · 55% automatable

Consult with supervisory staff to plan menus, taking into consideration factors such as costs and special event needs.

text generation — Menu drafts aided; cost and kitchen constraints human

Plan menu options.
#2182 · Supplemental · 5% automatable

Butcher and dress animals, fowl, or shellfish, or cut and bone meat prior to cooking.

physical manipulation — Hands-on food cutting

Cut cooked or raw foods.
#2186 · Supplemental · 68% automatable

Plan and price menu items.

decision support — Menu pricing aided; owner decides strategy

Determine prices for menu items.
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Community Sentiment

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Do you agree with the AI automation risk score calculated for this occupation?

Method

How this was scored

  1. 1. Tasks. O*NET task statements for this occupation, from a release whose newest record is dated 08/2026.
  2. 2. Work activities. Each task maps to 1–5 Detailed Work Activities; each activity belongs to one of 41 Generalized Work Activities that O*NET rates for importance (1–5) in this occupation.
  3. 3. Automation potential. Every work activity carries one score for how far current AI can perform it end-to-end. Tasks inherit the mean of their activities.
  4. 4. Weighting. Task weight = 0.35 + 0.65 × (importance − 1)/4, scaled by how often the task is performed and by 0.7 for Supplemental tasks. Importance is the task's own O*NET rating where it exists (18,369 of 18,838 tasks); the rest inherit their work activities' importance. The index is the weighted mean.

Check: across the 910 occupations where O*NET also rates how far machine speed sets the pace, this index moves opposite to it (Spearman ρ = -0.49). The more a job is paced by equipment, the less of its task content AI can address — the relationship you would expect if the scoring is working.

Sources · O*NET 31.0 (task records to 08/2026) · BLS OEWS May 2025 · BLS projections 2025-2035 · rubric v2.1 · tasks for O*NET, not a forecast

See the full method →

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