Machine Feeders and Offbearers
In short: today's best AI models could do about 5% 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 95% of the time, stays with people.
Feed materials into or remove materials from machines or equipment that is automatic or tended by other workers.
42,330 people do this job in the US. $41,220 a year.
A typical 40-hour week
Not yet reviewed task by task- AI could take on2 h
- A person checks AI's work0 h
- Desk work AI can't do yet0 h
- Stays with people38 h
Machine Feeders and Offbearers, now: of a 40-hour week, AI could take on 2 hours, 0 hours become checking its work, 0 hours are desk work it can't do yet, and 38 hours stay with people.
The largest pieces: Record production and operational data, such as amount of materials processed (about 2 h).
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.
- 5%
- 0%
- 95%
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, 4%. With Claude Mythos Preview (early), measured in April 2026, 5%. Today's estimate: 5%.
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 13 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 96% of this job's working time as physical work. For 96% of the working time, a robot has been shown doing most of the task somewhere: 53% in a purpose-built cell, 43% in a structured facility. 1.39 of 3, the 30th highest of the 923 jobs.
- Not physical 4%
- In a purpose-built cell 53%
- In a structured facility 43%
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 . 13 tasks from .
| Task | Kind | |||
|---|---|---|---|---|
| Clean and maintain machinery, equipment, and work areas to ensure proper functioning and safe working conditions.Done daily by most who do it. Robots: in a structured facility, Avidbots Neo (deployed). Anthropic's rating. | 18% | 21 min8 min to 50 min | Stays with people | |
| Fasten, package, or stack materials and products, using hand tools and fastening equipment.Done hourly or more by most who do it. Robots: in a purpose-built cell, Stretch (Boston Dynamics) (sold). Anthropic's rating. | 14% | 13 min4 min to 33 min | Stays with people | |
| Load materials and products into machines and equipment, or onto conveyors, using hand tools and moving devices.Done hourly or more by most who do it. Robots: in a structured facility, Figure 02 (deployed). Anthropic's rating. | 11% | 13 min4 min to 25 min | Stays with people | |
| Remove materials and products from machines and equipment, and place them in boxes, trucks or conveyors, using hand tools and moving devices.Done hourly or more by most who do it.Robots: in a purpose-built cell, Stretch (Boston Dynamics) (deployed). Anthropic's rating. | 11% | 13 min4 min to 25 min | Stays with people | |
| Inspect materials and products for defects, and to ensure conformance to specifications.Done hourly or more by most who do it. Robots: in a purpose-built cell, MESH 3D Vision Inspection Machine (Keyence LJV-7200 lasers, conveyorized track, reject bin) (deployed). Anthropic's rating. | 11% | 8 min2 min to 25 min | Stays with people | |
| Transfer materials and products to and from machinery and equipment, using industrial trucks or hand trucks.Done daily by most who do it. Robots: in a structured facility, OTTO 1500 AMR (lift attachment) with FactoryTalk Optix (deployed). Anthropic's rating. | 9% | 13 min4 min to 33 min | Stays with people | |
| Record production and operational data, such as amount of materials processed.Done hourly or more by most who do it. | 5% | 4 min2 min to 13 min | 100%Half by now | |
| Shovel or scoop materials into containers, machines, or equipment for processing, storage, or transport.Done daily by most who do it.Robots: in a structured facility, Chef Robotics ChefOS robotic arms (deployed). Anthropic's rating. | 4% | 10 min4 min to 21 min | Stays with people | |
| Weigh or measure materials or products to ensure conformance to specifications.Done hourly or more by most who do it. Robots: in a purpose-built cell, METTLER TOLEDO in-motion checkweighers (e.g. C-series) (Mettler-Toledo) (sold). Anthropic's rating. | 4% | 4 min2 min to 13 min | Stays with people | |
| Identify and mark materials, products, and samples, following instructions.Done daily by most who do it. Robots: in a purpose-built cell, Videojet label print and apply (LPA) systems (sold). Anthropic's rating. | 3% | 4 min1 min to 13 min | Stays with people | |
| Add chemicals, solutions, or ingredients to machines or equipment as required by the manufacturing process.Done daily by most who do it.Robots: in a purpose-built cell, Robotic depalletizer + automatic bag dump station (Tinsley Equipment Company integration) (deployed). Anthropic's rating. | 3% | 8 min4 min to 17 min | Stays with people | |
| Push dual control buttons and move controls to start, stop, or adjust machinery and equipment.Done daily by most who do it. Robots: in a purpose-built cell, FANUC CRX-20iA/L mobile manipulator on OTTO 100 AMR (built by Capriol) (demonstrated). Anthropic's rating. | 3% | 3 min1 min to 8 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.
- Cutting and Slicing Machine Setters, Operators, and Tenders7% now, 7% by 2028
- Adhesive Bonding Machine Operators and Tenders9% now, 9% by 2028
- Extruding, Forming, Pressing, and Compacting Machine Setters, Operators, and Tenders13% now, 13% by 2028
- Woodworking Machine Setters, Operators, and Tenders, Except Sawing9% now, 9% by 2028
- Paper Goods Machine Setters, Operators, and Tenders0% now, 0% by 2028
- Grinding, Lapping, Polishing, and Buffing Machine Tool Setters, Operators, and Tenders, Metal and Plastic10% now, 10% 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 Machine Feeders and Offbearers is within reach of AI now?
- An estimated 5% of the working time is within reach of AI models now and 5% 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 Machine Feeders and Offbearers 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 and operational data, such as amount of materials processed (100% of the task's time now).
- Which tasks of Machine Feeders and Offbearers stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Clean and maintain machinery, equipment, and work areas to ensure proper functioning and safe working conditions; Fasten, package, or stack materials and products, using hand tools and fastening equipment; and Load materials and products into machines and equipment, or onto conveyors, using hand tools and moving devices. Together such tasks are about 95% of the working time.
- Do people already use AI for the work of Machine Feeders and Offbearers?
- 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 Machine Feeders and Offbearers?
- Anthropic's robot exposure rating (September 2026) finds 96% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 96% of the working time, 43% in a structured facility. Its index is 1.39 of 3. One example: Avidbots Neo for "clean and maintain machinery, equipment, and work areas to ensure proper functioning and safe working conditions". 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 13 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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