Will AI replace Food Servers, Nonrestaurant?
Estimated risk score: 20 out of 100
Very low replacement risk
Estimate from published task research, not reviewed by a person · how we estimate
Within about 19 points for 4 in 5 of the jobs we checked (1 to 39).
For the occupation as a whole, from ratings of its 14 O*NET tasks published in 2023 and calibrated to our hand scores. A specialty inside it can sit higher or lower.
O*NET-SOC 35-3041.00 · Food Preparation and Serving Related
Tasks rated in 2023 as ones AI could do or speed up
Tasks a GPT-4-class model could do, or do in half the time or less: 2 of its 14 rated tasks. In O*NET’s words.
- Record amounts and types of special food items served to customers.
- Total checks, present them to customers, and accept payment for services.
Tasks rated in 2023 as not sped up by AI
Tasks such a model was rated as not speeding up or taking over: 11 of its 14 rated tasks; the first 6 are shown. In O*NET’s words.
- Carry food, silverware, or linen on trays or use carts to carry trays.
- Clean or sterilize dishes, kitchen utensils, equipment, or facilities.
- Determine where patients or patrons would like to eat their meals and help them get situated.
- Load trays with accessories, such as eating utensils, napkins, or condiments.
- Place food servings on plates or trays according to orders or instructions.
- Prepare food items, such as sandwiches, salads, soups, or beverages.
What the job is
Serve food to individuals outside of a restaurant environment, such as in hotel rooms, hospital rooms, residential care facilities, or cars.
Also called: Room Server, Tray Server, Curber, Boat Hop, Curb Hop, Car Attendant, Hot Tamale Man, Hot Tamale Worker.
Source. This site includes information from the O*NET 30.1 Database by the U.S. Department of Labor, Employment and Training Administration (USDOL/ETA). Used under the CC BY 4.0 license. O*NET® is a trademark of USDOL/ETA. USDOL/ETA has not approved, endorsed, or tested these modifications. (O*NET, CC BY 4.0.) Task ratings: Eloundou, Manning, Mishkin and Rock (2023), “GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models”, data used under the MIT licence (licence texts). Our change: we averaged the ratings over this occupation’s tasks and calibrated them to our 0–100 scale. It is not a prediction about any one person and not career advice. Disagree? Write to hello@yourstopwashit.com. How we estimate