Food Servers, Nonrestaurant
In short: today's best AI models could do about 10% of this job's working time (projected from METR's April 2026 measurement and Epoch's November 2026 index) if the work were set up for them, and about the same by the end of 2028 if progress keeps its long-run pace. The conversations, in-person and hands-on work, about 90% of the time, stays with people.
Serve food to individuals outside of a restaurant environment, such as in hotel rooms, hospital rooms, residential care facilities, or cars.
293,900 people do this job in the US. $35,360 a year.
Reviewed on September 30, 2026: what each task is made of, and what handing it over would ask.
A typical 40-hour week
- AI could take on0 h
- A person checks AI's work4 h
- Desk work AI can't do yet0 h
- Stays with people36 h
Food Servers, Nonrestaurant, now: of a 40-hour week, AI could take on 0 hours, 4 hours become checking its work, 0 hours are desk work it can't do yet, and 36 hours stay with people.
The largest pieces: Record special items served (about 2 h, a person checks); Check meals reach the right people (about 1 h, a person checks); Take and relay orders (about 1 h, a person checks).
Estimates for a typical week of this job, if progress keeps its long-run pace, counting work the best models finish four times in five. Every task is below.
of the working time. Now is projected from METR's April 2026 measurement and Epoch's November 2026 index.
- 3%
- 7%
- 0%
- 11%
- 79%
of the work: Anthropic's measure of what people already bring to Claude at work (2025). It counts help with part of a task, so it can be higher than the share within reach.
On the chosen pace and reliability. Estimate.
Share of the working time within reach, now to 2030
Change assumptionsHide assumptionsLong-run pace, four in five
What each choice means: , , , , . Every pace starts from .
At this date and pace, models finish tasks up to 2.4 work days long four times in five.
What handing it over would take, now
The 10% within reach splits by what a model would need. The dates, pace and reliability follow the controls above. Estimates.
of the working time. The material can be handed to a model and the result handed back.
of the working time. The model has to be connected to the system the work lives in.
is conversation short enough by length. This site leaves conversation with people, so it is not in the total.
How far this has come
With GPT-4, measured in March 2023, 0% of this job's working time was within reach at . With Claude 3.7 Sonnet, measured in February 2025, 6%. With Claude Mythos Preview (early), measured in April 2026, 10%. Today's estimate: 10%.
A backcast: today's task data with the best model METR had measured by each date. It shows how fast the models have moved, not what anyone forecast at the time.
Measured use over time
Of the Claude.ai conversations Anthropic sampled and tied to a work task, no reportable share went to this job's tasks in May 2026; 0 of its 14 tasks showed up. Within each of Anthropic's methods, never across a change: none to 0.0069% (released February and March 2025).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | none | n/a | 0 of 14 |
| Released March 2025 | 0.0069% | 546 of 703 | 1 of 14 |
| The week of Aug 4, 2025 (released September 2025) | none | n/a | 0 of 14 |
| The week of Nov 13, 2025 (released January 2026) | none | n/a | 0 of 14 |
| The week of Feb 5, 2026 (released March 2026) | none | n/a | 0 of 14 |
| April 2026 (released June 2026) | none | n/a | 0 of 14 |
| May 2026 (released June 2026) | none | n/a | 0 of 14 |
Measured, not estimated: Anthropic's samples of Claude.ai conversations, each tied by a model to an O*NET task, from the Anthropic Economic Index. It says where Claude's use goes, not how much of this job's working time it covers, so it is not on the same scale as the reach above. The releases differ in their sample, their classifier and the smallest share they report (the June 2026 file rounds each task to a hundredth of a percent, so a smaller task reads as none), which is why a change of method starts a new line. At least 96% of each older release's task-tied use matched this site's tasks, and all of the newest. Claude.ai only, so use through other tools and other companies' models is not in it. Every job ranked.
Robots and the physical work
Anthropic rates 87% of this job's working time as physical work. For 85% of the working time, a robot has been shown doing most of the task somewhere: 72% in a purpose-built cell, 13% in a structured facility. 0.98 of 3, the 126th highest of the 923 jobs.
- Not physical 13%
- No robot shown 2%
- In a purpose-built cell 72%
- In a structured facility 13%
Anthropic's rating, not this site's estimate: Claude Opus 5, searching the web, rated each physical O*NET task by the kind of setting in which a robot it could cite (deployed, sold or demonstrated) does most of the task, weighted by its own estimate of each task's share of the time (What work can robots do?, September 30, 2026, data CC BY 4.0; every job ranked). A robot shown somewhere is not a robot in your building: cost, setup and safety decide that. The share within reach on this page still counts no body work. The robot behind each rated task is under the task below.
What changes for the people in this job
From the task-by-task review, by the end of 2028 on the long-run pace at four in five. It says which parts of the work stay with people and which change, not whether anyone keeps a job: that depends on decisions no data set can see.
What stays with people
90% of the working time: the conversation, in-person and hands-on parts of the tasks.
- Wash and sterilize dishes, the hands-on work, 13%
- Watch that procedures are followed, the hands-on work, 12%
- Stock service stations, the hands-on work, 9%
- Prepare simple food items, the hands-on work, 8%
- Check meals reach the right people, the hands-on work, 8%
- Clear trays and dishes, the hands-on work, 7%
What becomes checking the machine
10% of the working time: desk work a model could do by then, in tasks where a mistake costs something or a licensed person signs. A person checks it.
- Record special items served, costly if wrong, 4%
- Check meals reach the right people, severe if wrong, 3%
- Take and relay orders, costly if wrong, 3%
What to learn
- The hands-on craft. About 79% of the time is hands-on work, which no model here does; robots are rated separately on this page.
- Judgment where errors are severe. Some tasks are severe if wrong. Knowing when not to trust an output matters more there than speed.
- Reviewing work you did not do yourself. The tasks under What becomes checking the machine, where a mistake costs something, stay a person's to check: spotting what a draft gets wrong is a skill of its own.
- Handling protected records. Much of the work touches protected personal records: knowing what may be shared with a model, and how, is part of the job.
- Dealing with people outside the organization. Customers, patients, suppliers or the public: trust with them is built by a person.
Your own version of this job: read it against your job description. The headline is free; the full personal report, every task with its timeline and what to learn, is $19 (a sample).
The tasks
Sorted by . 14 tasks from .
| Task | ||||
|---|---|---|---|---|
| Clean or sterilize dishes, kitchen utensils, equipment, or facilities.Washing up by hand and machine.Done daily by most who do it. Robots: in a purpose-built cell, Armstrong dishwashing robot (deployed). Anthropic's rating. | 13% | 13 min7 min to 33 min | Hands-on 100% | Stays with people |
| Monitor food preparation or serving techniques to ensure that proper procedures are followed.Watching the preparation and service on the floor.Done daily by most who do it. | 12% | 13 min4 min to 29 min | Hands-on 80%, in person 20% | Stays with people |
| Monitor food distribution, ensuring that meals are delivered to the correct recipients and that guidelines, such as those for special diets, are followed.Matching trays to patients and their diet orders.Done several times a day by most who do it. Robots: in a purpose-built cell, Relay+ (Savioke/Relay Robotics) at Dream Hollywood (deployed). Anthropic's rating. | 11% | 10 min4 min to 25 min | Hands-on 70%, documents 30% | 30%Desk part half by now |
| Stock service stations with items, such as ice, napkins, or straws.Restocking by hand.Done daily by most who do it. Robots: in a purpose-built cell, TX SCARA (Telexistence) (deployed). Anthropic's rating. | 9% | 10 min4 min to 21 min | Hands-on 100% | Stays with people |
| Prepare food items, such as sandwiches, salads, soups, or beverages.Making sandwiches, salads and drinks.Done several times a day by most who do it. Robots: in a purpose-built cell, Chef Robotics ChefOS robotic food-assembly arms (deployed). Anthropic's rating. | 8% | 10 min4 min to 21 min | Hands-on 100% | Stays with people |
| Remove trays and stack dishes for return to kitchen after meals are finished.Collecting and stacking by hand.Done several times a day by most who do it. Robots: in a purpose-built cell, Armstrong Robotics dishwashing robot (three 7-DoF arms) (sold). Anthropic's rating. | 7% | 7 min3 min to 13 min | Hands-on 100% | Stays with people |
| Take food orders and relay orders to kitchens or serving counters so they can be filled.Asking the patron and passing the order to the kitchen.Done daily by most who do it. | 6% | 7 min3 min to 13 min | In person 60%, systems 40% | 40%Desk part half by now |
| Place food servings on plates or trays according to orders or instructions.Portioning onto trays by hand.Done several times a day by most who do it. Robots: in a purpose-built cell, Chef Robotics food-assembly robot (Chef / Chef+) (deployed). Anthropic's rating. | 6% | 4 min3 min to 8 min | Hands-on 100% | Stays with people |
| Carry food, silverware, or linen on trays or use carts to carry trays.Carrying and pushing carts.Done daily by most who do it. Robots: in a structured facility, Servi (Bear Robotics) and Matradee (Richtech Robotics) (sold). Anthropic's rating. | 6% | 5 min3 min to 13 min | Hands-on 100% | Stays with people |
| Load trays with accessories, such as eating utensils, napkins, or condiments.Setting the trays up by hand.Done several times a day by most who do it. Robots: in a purpose-built cell, B.PRO / BRIMATO ASV-1 food portioning automation (Besteckaufleger cutlery placer module) (sold). Anthropic's rating. | 5% | 4 min2 min to 8 min | Hands-on 100% | Stays with people |
| Determine where patients or patrons would like to eat their meals and help them get situated.Asking where they want to eat and helping them get set.Done several times a day by most who do it. Robots: no robot shown. Anthropic's rating. | 5% | 7 min3 min to 13 min | In person 60%, hands-on 40% | Stays with people |
| Record amounts and types of special food items served to customers.Entries of what was served.Done hourly or more by most who do it. | 4% | 4 min2 min to 10 min | Systems 100% | 100%Half by now |
Within reach, per task: the share of the task's time whose instances are short enough for a model to finish at the chosen date, pace and reliability. Half by: the date half of that time comes within reach. Made of: how the task's time splits among five kinds of doing. Only the documents and systems parts can count as within reach, so a task that is 30% documents can be at most 30% within reach.
Jobs that share skills with this one
From O*NET's related occupations. Within reach now and by the end of 2028, long-run pace, four in five.
Where this job works
The industry groups that employ the most of it (BLS, May 2025).
Where the most of these jobs are
The metro areas with the most people in it (BLS, May 2025).
Questions about this job
- How much of the work of Food Servers, Nonrestaurant is within reach of AI now?
- An estimated 10% of the working time is within reach of AI models now and 10% by the end of 2028, on METR's long-run pace at four in five. Within reach means a model could finish work that long at that reliability. It is not a forecast of jobs lost or of savings.
- Which tasks of Food Servers, Nonrestaurant come within reach first?
- Weighted by the time each takes, the tasks with the most within reach now (projected from METR's April 2026 measurement and Epoch's November 2026 index) are: Record special items served (100% of the task's time now); Check meals reach the right people (30% of the task's time now); and Take and relay orders (40% of the task's time now).
- Which tasks of Food Servers, Nonrestaurant stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Wash and sterilize dishes; Watch that procedures are followed; and Stock service stations. Together such tasks are about 78% of the working time, and the people and body parts of the other tasks stay with people too.
- What should Food Servers, Nonrestaurant learn as AI takes on more of the work?
- By the job's own task-by-task review, the first things to learn are the hands-on craft; judgment where errors are severe; and reviewing work you did not do yourself. By the end of 2028 on the long-run pace at four in five, about 90% of the working time stays with people, 10% becomes checking a model's work and 0% could be handed over with lighter checks. It says which parts of the work change, never whether anyone keeps a job.
- Do people already use AI for the work of Food Servers, Nonrestaurant?
- In the Claude.ai conversations Anthropic sampled for May 2026, no reportable share went to this job's tasks. Anthropic's labor market measure puts the share of the job's tasks seen in real Claude use at work at 0%. These are measures of use, not of how much of the work AI could finish, and they cover Claude only.
- Can robots do the physical work of Food Servers, Nonrestaurant?
- Anthropic's robot exposure rating (September 2026) finds 87% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 85% of the working time, 13% in a structured facility. Its index is 0.98 of 3. One example: Servi (Bear Robotics) and Matradee (Richtech Robotics) for "carry trays and carts". A robot shown somewhere is not one in every workplace; this site's own estimates still count no physical work as within reach.
- How is this estimated?
- From the 14 tasks O*NET lists for the occupation, each with an estimated length checked against GDPval and a share of the working time, reviewed one task at a time on September 30, 2026 for what each is made of (documents, business systems, conversation, in person, hands-on), and METR's measurements of how long a task the best AI models can finish, carried forward to the date from the latest, Claude Mythos Preview (early) in April 2026. Data checked November 10, 2026.
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