Cutting and Slicing Machine Setters, Operators, and Tenders
In short: today's best AI models could do about 7% 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 93% of the time, stays with people.
Set up, operate, or tend machines that cut or slice materials, such as glass, stone, cork, rubber, tobacco, food, paper, or insulating material.
44,980 people do this job in the US. $46,570 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
Cutting and Slicing Machine Setters, 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: Review work orders, blueprints, specifications, or job samples to determine components, settings, and adjustments for cutting and slicing machines (about 2 h); Maintain production records, such as quantities, types, and dimensions of materials produced (about 1 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.
- 7%
- 2%
- 91%
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, 1%. With Claude Mythos Preview (early), measured in April 2026, 7%. Today's estimate: 7%.
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 28 tasks showed up. Within each of Anthropic's methods, never across a change: 0.03% to 0.005% (released February and March 2025); 0.0053% to 0.0016% (August 2025 to February 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.03% | 362 of 708 | 1 of 28 |
| Released March 2025 | 0.005% | 582 of 703 | 1 of 28 |
| The week of Aug 4, 2025 (released September 2025) | 0.0053% | 526 of 655 | 1 of 28 |
| The week of Nov 13, 2025 (released January 2026) | none | n/a | 0 of 28 |
| The week of Feb 5, 2026 (released March 2026) | 0.0016% | 666 of 677 | 1 of 28 |
| April 2026 (released June 2026) | none | n/a | 0 of 28 |
| May 2026 (released June 2026) | none | n/a | 0 of 28 |
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 84% of this job's working time as physical work. For 81% of the working time, a robot has been shown doing most of the task somewhere: 68% in a purpose-built cell, 13% in a structured facility. 0.94 of 3, the 156th highest of the 923 jobs.
- Not physical 16%
- No robot shown 3%
- In a purpose-built cell 68%
- 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.
The tasks
Sorted by . 28 tasks from .
| Task | Kind | |||
|---|---|---|---|---|
| Set up, operate, or tend machines that cut or slice materials, such as glass, stone, cork, rubber, tobacco, food, paper, or insulating material.Done hourly or more by most who do it. Robots: in a purpose-built cell, Weber high-capacity slicer with Food Robotics automation / SmartLoader (sold). Anthropic's rating. | 32% | 1.7 h25 min to 3.3 h | Stays with people | |
| Remove defective or substandard materials from machines, and readjust machine components so that products meet standards.Done daily by most who do it. Robots: in a purpose-built cell, Weber weSLICE 9500 / 604 slicer with CCU, checkweigher (CCW) and rocker (sold). Anthropic's rating. | 6% | 21 min8 min to 50 min | Stays with people | |
| Examine, measure, and weigh materials or products to verify conformance to specifications, using measuring devices, such as rulers, micrometers, or scales.Done hourly or more by most who do it. Robots: in a purpose-built cell, METTLER TOLEDO food/in-motion checkweighers (Mettler-Toledo) (sold). Anthropic's rating. | 5% | 13 min4 min to 33 min | Stays with people | |
| Start machines to verify setups, and make any necessary adjustments.Done daily by most who do it. Robots: in a structured facility, Weber Slicer 604 (weSLICE family) (sold). Anthropic's rating. | 4% | 17 min8 min to 25 min | Stays with people | |
| Stack and sort cut material for packaging, further processing, or shipping, according to types and sizes of material.Done hourly or more by most who do it. Robots: in a purpose-built cell, Alliance Automation robotic sheet stacker (FANUC M-900iA/260L) (deployed). Anthropic's rating. | 4% | 13 min4 min to 33 min | Stays with people | |
| Review work orders, blueprints, specifications, or job samples to determine components, settings, and adjustments for cutting and slicing machines.Done daily by most who do it. AI observed on this task. | 4% | 13 min4 min to 33 min | 100%Half by now | |
| Monitor operation of cutting or slicing machines to detect malfunctions or to determine whether supplies need replenishment.Done hourly or more by most who do it. | 4% | 13 min4 min to 38 min | Stays with people | |
| Type instructions on computer keyboards, push buttons to activate computer programs, or manually set cutting guides, clamps, and knives.Done daily by most who do it. Robots: in a purpose-built cell, POLAR PACE 200 automated cutting system (N137 AT high-speed cutter) (POLAR-Mohr / Heidelberg) (sold). Anthropic's rating. | 4% | 13 min4 min to 33 min | Stays with people | |
| Operate cranes, or signal crane operators to position or remove stone from cars or saw beds.Done hourly or more by most who do it. | 3% | 17 min4 min to 33 min | Stays with people | |
| Maintain production records, such as quantities, types, and dimensions of materials produced.Done daily by most who do it. | 3% | 13 min4 min to 25 min | 100%Half by now | |
| Move stock or scrap to and from machines manually, or by using carts, handtrucks, or lift trucks.Done daily by most who do it. Robots: in a structured facility, Seegrid Palion AMRs (Pallet Truck, Lift RS1/CR1, Tow Tractor S7) (sold). Anthropic's rating. | 3% | 13 min4 min to 33 min | Stays with people | |
| Feed stock into cutting machines, onto conveyors, or under cutting blades, by threading, guiding, pushing, or turning handwheels.Done hourly or more by most who do it. Robots: in a purpose-built cell, Weber high capacity slicer with automatic loading (sold). Anthropic's rating. | 3% | 13 min4 min to 25 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.
- Woodworking Machine Setters, Operators, and Tenders, Except Sawing9% now, 9% by 2028
- Grinding, Lapping, Polishing, and Buffing Machine Tool Setters, Operators, and Tenders, Metal and Plastic10% now, 10% by 2028
- Textile Cutting Machine Setters, Operators, and Tenders14% now, 14% by 2028
- Cutting, Punching, and Press Machine Setters, Operators, and Tenders, Metal and Plastic6% now, 6% by 2028
- Sawing Machine Setters, Operators, and Tenders, Wood8% now, 8% by 2028
- Paper Goods Machine Setters, Operators, and Tenders0% now, 0% 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 Cutting and Slicing Machine Setters, Operators, and Tenders is within reach of AI now?
- An estimated 7% of the working time is within reach of AI models now and 7% 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 Cutting and Slicing Machine Setters, 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: Review work orders, blueprints, specifications, or job samples to determine components, settings, and adjustments for cutting and slicing machines (100% of the task's time now); and Maintain production records, such as quantities, types, and dimensions of materials produced (100% of the task's time now).
- Which tasks of Cutting and Slicing Machine Setters, 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: Set up, operate, or tend machines that cut or slice materials, such as glass, stone, cork, rubber, tobacco, food, paper, or insulating material; Remove defective or substandard materials from machines, and readjust machine components so that products meet standards; and Examine, measure, and weigh materials or products to verify conformance to specifications, using measuring devices, such as rulers, micrometers, or scales. Together such tasks are about 93% of the working time.
- Do people already use AI for the work of Cutting and Slicing Machine Setters, 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 3%. 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 Cutting and Slicing Machine Setters, Operators, and Tenders?
- Anthropic's robot exposure rating (September 2026) finds 84% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 81% of the working time, 13% in a structured facility. Its index is 0.94 of 3. One example: Weber Slicer 604 (weSLICE family) for "start machines to verify setups, and make any necessary adjustments". 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 28 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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