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AI Automation Index
Will AI Replace Food Servers, Nonrestaurant?
Task-level automation exposure for Food Servers, Nonrestaurant: 14 O*NET tasks scored against their work activities, plus the simulator.
E-E-A-T Verified
Developed & audited by Gini Loh Automation Exposure
25%
weighted task index
14 of 14 tasks scored
Median Salary
$35,360 / year
BLS OEWS, May 2025 — this exact occupation
Employment Level
High
293,900 people hold this job — size, not growth
Projected 2025–35
+4.5%
employment change
48,800 openings a year · BLS line item
Pay by state
BLS OEWS publishes 53 state estimates for this occupation. Each is its own survey estimate, not the national median adjusted for local prices.
$21,840 – $39,370
Highest medians
New York $39,370
California $39,010
Colorado $38,900
Washington $38,870
Alaska $38,090
Lowest medians
Puerto Rico $21,840
Louisiana $27,200
Mississippi $27,250
Arkansas $27,600
Oklahoma $28,490
State figures come from the 35-3041 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 25%
Importance-weighted mean of the scored tasks. This is the headline index.
Physical work 51%
Share of weighted tasks in hands-on or machine-operating work activities.
Judgment & influence 7%
Share in analysis, decisions, teaching, directing, advising, or caring for others.
Routine administration 12%
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 22/100
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
14 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) 12%
2 tasks
Medium exposure (≥ 35%) 22%
3 tasks
Low exposure (below 35%) 66%
9 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
#11152 · Core · 7% automatable
Place food servings on plates or trays according to orders or instructions.
physical manipulation — Plating food is fine manual dexterity
Arrange food for serving.
#11150 · Core · 7% automatable
Clean or sterilize dishes, kitchen utensils, equipment, or facilities.
physical manipulation — Hands-on dishwashing of physical tableware
Clean tableware.
#11149 · Core · 35% automatable
Monitor food distribution, ensuring that meals are delivered to the correct recipients and that guidelines, such as those for special diets, are followed.
visual inspection — Procedure compliance in kitchens requires on-site human observation
Monitor food services operations to ensure procedures are followed.
#11151 · Core · 20% automatable
Examine trays to ensure that they contain required items.
visual inspection — Food/supply quality check is sensory and physical
Check quality of foods or supplies. Inspect food products.
#11153 · Core · 8% automatable
Load trays with accessories, such as eating utensils, napkins, or condiments.
physical manipulation — Physically stocking serving stations and dining areas
Stock serving stations or dining areas with food or supplies.
#11154 · Core · 55% automatable
Take food orders and relay orders to kitchens or serving counters so they can be filled.
interpersonal — Order relay in live kitchen; AI can transcribe only
Communicate dining or order details to kitchen personnel.
#11158 · Core · 35% automatable
Monitor food preparation or serving techniques to ensure that proper procedures are followed.
visual inspection — Procedure compliance in kitchens requires on-site human observation
Monitor food services operations to ensure procedures are followed.
#11156 · Core · 5% automatable
Remove trays and stack dishes for return to kitchen after meals are finished.
physical manipulation — Collecting dishes requires hands-on bussing
Collect dirty dishes or other tableware.
#11159 · Core · 9% automatable
Carry food, silverware, or linen on trays or use carts to carry trays.
physical manipulation — Hands-on moving of supplies to locations
Move equipment, supplies or food to required locations.
#11161 · Core · 82% automatable
Record amounts and types of special food items served to customers.
data analysis — Record production data into structured logs
Record operational or production data.
#11155 · Core · 8% automatable
Stock service stations with items, such as ice, napkins, or straws.
physical manipulation — Physically stocking serving stations and dining areas
Stock serving stations or dining areas with food or supplies.
#11157 · Core · 6% automatable
Prepare food items, such as sandwiches, salads, soups, or beverages.
physical manipulation — Cooking requires hands-on manipulation of real food
Cook foods.
#11160 · Core · 20% automatable
Determine where patients or patrons would like to eat their meals and help them get situated.
interpersonal — Physical seating arrangement and hosting
Assist customers with seating arrangements.
#11162 · Supplemental · 70% automatable
Total checks, present them to customers, and accept payment for services.
data analysis — Billing and payment processing largely automated
Process customer bills or payments.
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How this was scored
- 1. Tasks. O*NET task statements for this occupation, from a release whose newest record is dated 08/2026.
- 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. 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. 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
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