Food and Tobacco Roasting, Baking, and Drying Machine Operators and Tenders
In short: today's best AI models could do about 8% 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 people and hands-on work, about 92% of the time, stays with people.
Operate or tend food or tobacco roasting, baking, or drying equipment, including hearth ovens, kiln driers, roasters, char kilns, and vacuum drying equipment.
20,370 people do this job in the US. $44,810 a year.
A typical 40-hour week
Not yet reviewed task by task- AI could take on3 h
- A person checks AI's work0 h
- Desk work AI can't do yet0 h
- Stays with people37 h
Food and Tobacco Roasting, Baking, and Drying Machine Operators and Tenders, now: of a 40-hour week, AI could take on 3 hours, 0 hours become checking its work, 0 hours are desk work it can't do yet, and 37 hours stay with people.
The largest pieces: Record production data, such as weight and amount of product processed, type of product, and time and temperature of processing (about 2 h); Read work orders to determine quantities and types of products to be baked, dried, or roasted (under an hour).
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.
- 8%
- 0%
- 92%
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.
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, 5%. With Claude Mythos Preview (early), measured in April 2026, 8%. Today's estimate: 8%.
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
None of this job's 19 tasks showed up in the Claude.ai conversations Anthropic sampled in any of its 7 releases, from February 2025 to May 2026.
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 85% 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: 29% in a purpose-built cell, 55% in a structured facility. 1.40 of 3, the 29th highest of the 923 jobs.
- Not physical 15%
- In a purpose-built cell 29%
- In a structured facility 55%
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.
The tasks
Sorted by . 19 tasks from .
| Task | Kind | |||
|---|---|---|---|---|
| Operate or tend equipment that roasts, bakes, dries, or cures food items such as cocoa and coffee beans, grains, nuts, and bakery products.Done hourly or more by most who do it. Robots: in a structured facility, Mecatherm oven/gantry pan line with ABI Katana robotic scoring and Mecatherm multi-tool depanner (deployed). Anthropic's rating. | 28% | 50 min25 min to 2.5 h | Stays with people | |
| Observe flow of materials and listen for machine malfunctions, such as jamming or spillage, and notify supervisors if corrective actions fail.Done hourly or more by most who do it. | 7% | 13 min4 min to 25 min | Stays with people | |
| Clean equipment with steam, hot water, and hoses.Done daily by most who do it.Robots: in a purpose-built cell, CleanBotix Rosie (R6) (deployed). Anthropic's rating. | 6% | 38 min13 min to 1.7 h | Stays with people | |
| Record production data, such as weight and amount of product processed, type of product, and time and temperature of processing.Done hourly or more by most who do it. | 6% | 8 min4 min to 17 min | 100%Half by now | |
| Set temperature and time controls, light ovens, burners, driers, or roasters, and start equipment, such as conveyors, cylinders, blowers, driers, or pumps.Done daily by most who do it. Robots: in a structured facility, Honeywell 7800 Series burner control units (RM/EC7800 flame safeguard) (deployed). Anthropic's rating. | 6% | 17 min8 min to 38 min | Stays with people | |
| Fill or remove product from trays, carts, hoppers, or equipment, using scoops, peels, or shovels, or by hand.Done hourly or more by most who do it. Robots: in a structured facility, Chef Robotics (Chef / Chef+ AI food assembly robot) (deployed). Anthropic's rating. | 6% | 13 min4 min to 33 min | Stays with people | |
| Observe, feel, taste, or otherwise examine products during and after processing to ensure conformance to standards.Done hourly or more by most who do it. Robots: in a purpose-built cell, KPM Analytics EyePro Q-Bake vision inspection system (sold). Anthropic's rating. | 5% | 7 min3 min to 13 min | Stays with people | |
| Weigh or measure products, using scale hoppers or scale conveyors.Done hourly or more by most who do it. Robots: in a purpose-built cell, Thayer Scale Model MWF weigh belt feeder (green bean blending system) (sold). Anthropic's rating. | 5% | 8 min3 min to 17 min | Stays with people | |
| Observe temperature, humidity, pressure gauges, and product samples and adjust controls, such as thermostats and valves, to maintain prescribed operating conditions for specific stages.Done hourly or more by most who do it. Robots: in a structured facility, EyePro Vision System with Real-Time Oven Feedback module (KPM Analytics) (sold). Anthropic's rating. | 5% | 8 min3 min to 21 min | Stays with people | |
| Open valves, gates, or chutes or use shovels to load or remove products from ovens or other equipment.Done hourly or more by most who do it.Robots: in a structured facility, PROBAT NEPTUNE drum roasters with ProCS M / PILOT PLANT control (Luckin Qingdao roastery) (deployed). Anthropic's rating. | 4% | 13 min4 min to 25 min | Stays with people | |
| Push racks or carts to transfer products to storage, cooling stations, or the next stage of processing.Done hourly or more by most who do it.Robots: in a structured facility, MiR250 Hook (Mobile Industrial Robots) (sold). Anthropic's rating. | 4% | 8 min4 min to 17 min | Stays with people | |
| Clear or dislodge blockages in bins, screens, or other equipment, using poles, brushes, or mallets.Done daily by most who do it.Robots: in a purpose-built cell, Normet Xrock Autobreaker (autonomous rock-breaking boom) (sold). Anthropic's rating. | 4% | 13 min4 min to 38 min | Stays with people |
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.
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.
- Food Batchmakers15% now, 17% by 2028
- Food Cooking Machine Operators and Tenders7% now, 7% by 2028
- Separating, Filtering, Clarifying, Precipitating, and Still Machine Setters, Operators, and Tenders5% now, 5% by 2028
- Furnace, Kiln, Oven, Drier, and Kettle Operators and Tenders10% now, 10% by 2028
- Graders and Sorters, Agricultural Products7% now, 7% by 2028
- Cooling and Freezing Equipment Operators and Tenders6% now, 6% by 2028
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 and Tobacco Roasting, Baking, and Drying Machine Operators and Tenders is within reach of AI now?
- An estimated 8% of the working time is within reach of AI models now and 8% 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 and Tobacco Roasting, Baking, and Drying Machine Operators and Tenders 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 production data, such as weight and amount of product processed, type of product, and time and temperature of processing (100% of the task's time now); and Read work orders to determine quantities and types of products to be baked, dried, or roasted (100% of the task's time now).
- Which tasks of Food and Tobacco Roasting, Baking, and Drying Machine Operators and Tenders stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Operate or tend equipment that roasts, bakes, dries, or cures food items such as cocoa and coffee beans, grains, nuts, and bakery products; Observe flow of materials and listen for machine malfunctions, such as jamming or spillage, and notify supervisors if corrective actions fail; and Clean equipment with steam, hot water, and hoses. Together such tasks are about 92% of the working time.
- Do people already use AI for the work of Food and Tobacco Roasting, Baking, and Drying Machine Operators and Tenders?
- 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 and Tobacco Roasting, Baking, and Drying Machine Operators and Tenders?
- Anthropic's robot exposure rating (September 2026) finds 85% 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, 55% in a structured facility. Its index is 1.40 of 3. One example: Mecatherm oven/gantry pan line with ABI Katana robotic scoring and Mecatherm multi-tool depanner for "operate or tend equipment that roasts, bakes, dries, or cures food items such as cocoa and coffee beans, grains, nuts, and bakery products". 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 19 tasks O*NET lists for the occupation, each with an estimated length checked against GDPval and a share of the working time, each classed as desk, people or body work, 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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