Paper Goods Machine Setters, Operators, and Tenders
In short: today's best AI models could do about 0% 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 100% of the time, stays with people.
Set up, operate, or tend paper goods machines that perform a variety of functions, such as converting, sawing, corrugating, banding, wrapping, boxing, stitching, forming, or sealing paper or paperboard sheets into products.
96,130 people do this job in the US. $50,270 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 work0 h
- Desk work AI can't do yet0 h
- Stays with people40 h
Paper Goods Machine Setters, Operators, and Tenders, now: of a 40-hour week, AI could take on 0 hours, 0 hours become checking its work, 0 hours are desk work it can't do yet, and 40 hours stay with people.
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.
- 0%
- 0%
- 0%
- 0%
- 100%
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 0% 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, 0%. With Claude Mythos Preview (early), measured in April 2026, 0%. Today's estimate: 0%.
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 14 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 100% of this job's working time as physical work. For 74% of the working time, a robot has been shown doing most of the task somewhere: 54% in a purpose-built cell, 21% in a structured facility. 0.95 of 3, the 147th highest of the 923 jobs.
- No robot shown 26%
- In a purpose-built cell 54%
- In a structured facility 21%
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
100% of the working time: the conversation, in-person and hands-on parts of the tasks.
- Disassemble and repair machines, the hands-on work, 16%
- Install machine attachments, the hands-on work, 15%
- Examine work and adjust machines, the hands-on work, 13%
- Watch machines and correct faults, the hands-on work, 9%
- Adjust guides and folding mechanisms, the hands-on work, 8%
- Load rolls and thread paper, the hands-on work, 8%
What becomes checking the machine
No desk work within reach by then in tasks where a mistake costs something.
What to learn
- The hands-on craft. About 100% 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.
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 | ||||
|---|---|---|---|---|
| Disassemble machines to maintain, repair, or replace broken or worn parts, using hand or power tools.Parts replaced with hand and power tools.Done daily by most who do it. Robots: no robot shown. Anthropic's rating. | 16% | 1.3 h25 min to 3.3 h | Hands-on 100% | Stays with people |
| Install attachments to machines for gluing, folding, printing, or cutting.Attachments fitted for gluing, folding, printing or cutting.Done several times a day by most who do it.Robots: in a purpose-built cell, AV Flexologic FAMM 3.0 (Fully Automatic Mounting Machine) (sold). Anthropic's rating. | 15% | 38 min17 min to 1.7 h | Hands-on 100% | Stays with people |
| Examine completed work to detect defects and verify conformance to work orders, and adjust machinery as necessary to correct production problems.Products checked and the machine adjusted.Done hourly or more by most who do it. Robots: in a purpose-built cell, Valco Melton CartonPRO / ClearVision inspection and gluing systems for folder-gluers (sold). Anthropic's rating. | 13% | 13 min7 min to 38 min | Hands-on 100% | Stays with people |
| Observe operation of various machines to detect and correct machine malfunctions such as improper forming, glue flow, or pasteboard tension.Watching for forming, glue and tension problems.Done hourly or more by most who do it. Robots: no robot shown. Anthropic's rating. | 9% | 13 min4 min to 38 min | Hands-on 100% | Stays with people |
| Adjust guide assemblies, forming bars, and folding mechanisms according to specifications, using hand tools.Adjustments with hand tools.Done daily by most who do it.Robots: in a structured facility, Mitsubishi Heavy Industries EVOL flexo folder gluer (84/100/115/125) (sold). Anthropic's rating. | 8% | 25 min13 min to 50 min | Hands-on 100% | Stays with people |
| Place rolls of paper or cardboard on machine feed tracks, and thread paper through gluing, coating, and slitting rollers.Rolls placed and paper threaded through the rollers.Done daily by most who do it.Robots: in a structured facility, BHS iMotion / BHS Intralogistics (RHS, iPrep, iShuttle, iCMS) (sold). Anthropic's rating. | 8% | 21 min8 min to 38 min | Hands-on 100% | Stays with people |
| Monitor finished cartons as they drop from forming machines into rotating hoppers and into gravity feed chutes to prevent jamming.Watching the chutes to prevent jams.Done hourly or more by most who do it.Robots: in a purpose-built cell, BOBST ACCUCHECK (on EXPERTFOLD/MASTERFOLD folder-gluer lines) (deployed). Anthropic's rating. | 6% | 13 min4 min to 38 min | Hands-on 100% | Stays with people |
| Measure, space, and set saw blades, cutters, and perforators, according to product specifications.Blades measured, spaced and set.Done daily by most who do it.Robots: in a purpose-built cell, BHS Corrugated Slitter Scorer (SR-C / SR series with iLFS) (deployed). Anthropic's rating. | 5% | 25 min8 min to 50 min | Hands-on 100% | Stays with people |
| Start machines and move controls to regulate tension on pressure rolls, to synchronize speed of machine components, and to adjust temperatures of glue or paraffin.Controls at the machine.Done daily by most who do it. Robots: in a purpose-built cell, BHS Corrugated 4.0 (CCC / WEC / AQW / Warp Control System) (sold). Anthropic's rating. | 5% | 17 min8 min to 33 min | Hands-on 100% | Stays with people |
| Stamp products with information such as dates, using hand stamps or automatic stamping devices.Dates stamped by hand or machine.Done hourly or more by most who do it.Robots: in a purpose-built cell, Videojet 2380 large character inkjet printer (sold). Anthropic's rating. | 4% | 8 min3 min to 17 min | Hands-on 100% | Stays with people |
| Remove finished cores, and stack or place them on conveyors for transfer to other work areas.Cores removed and placed on conveyors.Done daily by most who do it.Robots: in a purpose-built cell, Core Link CL 4090 automatic core cutter (sold). Anthropic's rating. | 3% | 13 min4 min to 25 min | Hands-on 100% | Stays with people |
| Cut products to specified dimensions, using hand or power cutters.Hand and power cutters on the products.Done hourly or more by most who do it.Robots: in a purpose-built cell, BHS Corrugated Slitter Scorer and Cutoff (corrugator dry end) (deployed). Anthropic's rating. | 3% | 13 min4 min to 38 min | Hands-on 100% | 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. 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.
- Adhesive Bonding Machine Operators and Tenders9% now, 9% by 2028
- Cutting and Slicing Machine Setters, Operators, and Tenders7% now, 7% by 2028
- Textile Cutting Machine Setters, Operators, and Tenders14% now, 14% by 2028
- Extruding and Forming Machine Setters, Operators, and Tenders, Synthetic and Glass Fibers5% now, 5% by 2028
- Machine Feeders and Offbearers5% now, 5% by 2028
- Extruding, Forming, Pressing, and Compacting Machine Setters, Operators, and Tenders13% now, 13% 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 Paper Goods Machine Setters, Operators, and Tenders is within reach of AI now?
- An estimated 0% of the working time is within reach of AI models now and 0% 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 Paper Goods Machine Setters, Operators, and Tenders come within reach first?
- No task has a meaningful share of its time within reach now or by the end of 2028, on the long-run pace at four in five: the work is mostly people work and body work, which the site does not count.
- Which tasks of Paper Goods 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: Disassemble and repair machines; Install machine attachments; and Examine work and adjust machines. Together such tasks are about 100% of the working time, and the people and body parts of the other tasks stay with people too.
- What should Paper Goods Machine Setters, Operators, and Tenders 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; and judgment where errors are severe. By the end of 2028 on the long-run pace at four in five, about 100% of the working time stays with people, 0% 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 Paper Goods 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 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 Paper Goods Machine Setters, Operators, and Tenders?
- Anthropic's robot exposure rating (September 2026) finds 100% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 74% of the working time, 21% in a structured facility. Its index is 0.95 of 3. One example: Mitsubishi Heavy Industries EVOL flexo folder gluer (84/100/115/125) for "adjust guides and folding mechanisms". 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.
This job in your state or metro area
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