Molding, Coremaking, and Casting Machine Setters, Operators, and Tenders, Metal and Plastic
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 conversations, in-person and hands-on work, about 95% of the time, stays with people.
Set up, operate, or tend metal or plastic molding, casting, or coremaking machines to mold or cast metal or thermoplastic parts or products.
150,470 people do this job in the US. $44,350 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 on1 h
- A person checks AI's work1 h
- Desk work AI can't do yet0 h
- Stays with people38 h
Molding, Coremaking, and Casting Machine Setters, Operators, and Tenders, Metal and Plastic, now: of a 40-hour week, AI could take on 1 hours, 1 hours become checking its work, 0 hours are desk work it can't do yet, and 38 hours stay with people.
The largest pieces: Read specifications and plan sequences (under an hour, a person checks); Count stock and requisition supplies (under an hour); Maintain material inventories (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.
- 2%
- 2%
- 0%
- 2%
- 93%
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 5% 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, 1%. 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
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 29 tasks showed up. Within each of Anthropic's methods, never across a change: 0.0028% to none (released February and March 2025); none to 0.0023% (August 2025 to February 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.0028% | 667 of 708 | 1 of 29 |
| Released March 2025 | none | n/a | 0 of 29 |
| The week of Aug 4, 2025 (released September 2025) | none | n/a | 0 of 29 |
| The week of Nov 13, 2025 (released January 2026) | 0.0021% | 641 of 672 | 1 of 29 |
| The week of Feb 5, 2026 (released March 2026) | 0.0023% | 639 of 677 | 1 of 29 |
| April 2026 (released June 2026) | none | n/a | 0 of 29 |
| May 2026 (released June 2026) | none | n/a | 0 of 29 |
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 91% of this job's working time as physical work. For 89% of the working time, a robot has been shown doing most of the task somewhere: 61% in a purpose-built cell, 28% in a structured facility. 1.16 of 3, the 63rd highest of the 923 jobs.
- Not physical 9%
- No robot shown 3%
- In a purpose-built cell 61%
- In a structured facility 28%
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
95% of the working time: the conversation, in-person and hands-on parts of the tasks.
- Run molding and casting machines, the hands-on work, 16%
- Watch automatic machines and adjust, the hands-on work, 14%
- Clean and repair mold surfaces, the hands-on work, 5%
- Install and coat dies, the hands-on work, 5%
- Cool products, the hands-on work, 5%
- Repair molds and equipment, the hands-on work, 5%
What becomes checking the machine
2% 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. Another 2% is desk work that is small if wrong, which can be handed over with lighter checks.
- Read specifications and plan sequences, costly if wrong, 2%
What to learn
- The hands-on craft. About 93% 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.
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 . 29 tasks from .
| Task | ||||
|---|---|---|---|---|
| Set up, operate, or tend metal or plastic molding, casting, or coremaking machines to mold or cast metal or thermoplastic parts or products.Setting up and tending the machines.Done daily by most who do it. Robots: in a purpose-built cell, Yushin take-out robots + Universal Robots cobots at AIM Processing (deployed). Anthropic's rating. | 16% | 1.3 h25 min to 3.3 h | Hands-on 100% | Stays with people |
| Observe continuous operation of automatic machines to ensure that products meet specifications and to detect jams or malfunctions, making adjustments as necessary.Watching the run for jams and defects and adjusting.Done hourly or more by most who do it. Robots: in a structured facility, Wittmann Battenfeld presses with integrated cell monitoring at T&M Enterprises (deployed). Anthropic's rating. | 14% | 25 min13 min to 50 min | Hands-on 100% | Stays with people |
| Smooth and clean inner surfaces of molds, using brushes, scrapers, air hoses, or grinding wheels, and fill imperfections with refractory material.Brushing, grinding and filling the mold interior.Done daily by most who do it. Robots: in a purpose-built cell, Rimrock reciprocators / spray atomizers / robotic spray wands (Lincoln Electric Automation) (sold). Anthropic's rating. | 5% | 33 min13 min to 1.1 h | Hands-on 100% | Stays with people |
| Install dies onto machines or presses and coat dies with parting agents, according to work order specifications.Dies mounted on the press and coated.Done daily by most who do it.Robots: in a purpose-built cell, Stäubli QMC (quick-mold-change) system with mold loading table, Imag magnetic clamping and automatic multicouplings (sold). Anthropic's rating. | 5% | 38 min17 min to 1.3 h | Hands-on 100% | Stays with people |
| Cool products after processing to prevent distortion.Cooling parts after processing.Done hourly or more by most who do it.Robots: in a purpose-built cell, KC Robotics robotic IMM tending system with four-position chilled-air cooling rack (deployed). Anthropic's rating. | 5% | 13 min4 min to 25 min | Hands-on 100% | Stays with people |
| Repair or replace damaged molds, pipes, belts, chains, or other equipment, using hand tools, hand-powered presses, or jib cranes.Repairs with hand tools, presses and jib cranes.Done more than weekly by most who do it.Robots: no robot shown. Anthropic's rating. | 5% | 1.3 h25 min to 2.5 h | Hands-on 100% | Stays with people |
| Obtain and move specified patterns to work stations, manually or using hoists, and secure patterns to machines, using wrenches.Patterns moved by hand or hoist and bolted on.Done daily by most who do it.Robots: in a purpose-built cell, Stäubli QMC / QMC 123 magnetic clamping system (sold). Anthropic's rating. | 5% | 25 min8 min to 58 min | Hands-on 100% | Stays with people |
| Read specifications, blueprints, and work orders to determine setups, temperatures, and time settings required to mold, form, or cast plastic materials, as well as to plan production sequences.Reading the order and blueprint and planning the run; the knowing is the operator's own.Done daily by most who do it. | 4% | 17 min4 min to 50 min | Documents 60%, in person 40% | 60%Desk part half by now |
| Measure and visually inspect products for surface and dimension defects to ensure conformance to specifications, using precision measuring instruments.Measuring and looking over the products.Done hourly or more by most who do it. Robots: in a purpose-built cell, Sentinel Vision 3D LaserScan (Zebra AltiZ sensors + VisionCore) (deployed). Anthropic's rating. | 4% | 8 min3 min to 25 min | Hands-on 100% | Stays with people |
| Perform maintenance work such as cleaning and oiling machines.Maintenance by hand.Done daily by most who do it. Robots: in a purpose-built cell, LoopCLEAN robotic laser cleaning system (sold). Anthropic's rating. | 3% | 25 min13 min to 50 min | Hands-on 100% | Stays with people |
| Remove parts, such as dies, from machines after production runs are finished.Dies taken off the machine.Done more than weekly by most who do it. Robots: in a purpose-built cell, EAS Mold Change Tables / Quick Mold Change system (hydraulic clamping cylinders, ejector coupler, mold centering cylinder, driven rollers, automatic multi couplers) (deployed). Anthropic's rating. | 3% | 21 min8 min to 50 min | Hands-on 100% | Stays with people |
| Trim excess material from parts, using knives, and grind scrap plastic into powder for reuse.Trimming with knives and grinding scrap.Done daily by most who do it.Robots: in a purpose-built cell, Robotic Production Technology (RPT) deflashing cell with FANUC M-16i robots and compliant knives (deployed). Anthropic's rating. | 3% | 17 min4 min to 50 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.
- Extruding and Drawing Machine Setters, Operators, and Tenders, Metal and Plastic7% now, 7% by 2028
- Molders, Shapers, and Casters, Except Metal and Plastic0% now, 0% by 2028
- Extruding and Forming Machine Setters, Operators, and Tenders, Synthetic and Glass Fibers5% now, 5% by 2028
- Extruding, Forming, Pressing, and Compacting Machine Setters, Operators, and Tenders13% now, 13% by 2028
- Multiple Machine Tool Setters, Operators, and Tenders, Metal and Plastic10% now, 10% by 2028
- Forging Machine Setters, Operators, and Tenders, Metal and Plastic6% 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 Molding, Coremaking, and Casting Machine Setters, Operators, and Tenders, Metal and Plastic 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 Molding, Coremaking, and Casting Machine Setters, Operators, and Tenders, Metal and Plastic 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: Read specifications and plan sequences (60% of the task's time now); Count stock and requisition supplies (40% of the task's time now); and Maintain material inventories (40% of the task's time now).
- Which tasks of Molding, Coremaking, and Casting Machine Setters, Operators, and Tenders, Metal and Plastic stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Run molding and casting machines; Watch automatic machines and adjust; and Clean and repair mold surfaces. Together such tasks are about 89% of the working time, and the people and body parts of the other tasks stay with people too.
- What should Molding, Coremaking, and Casting Machine Setters, Operators, and Tenders, Metal and Plastic 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 95% of the working time stays with people, 2% becomes checking a model's work and 2% 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 Molding, Coremaking, and Casting Machine Setters, Operators, and Tenders, Metal and Plastic?
- 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 Molding, Coremaking, and Casting Machine Setters, Operators, and Tenders, Metal and Plastic?
- Anthropic's robot exposure rating (September 2026) finds 91% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 89% of the working time, 28% in a structured facility. Its index is 1.16 of 3. One example: Wittmann Battenfeld presses with integrated cell monitoring at T&M Enterprises for "watch automatic machines and adjust". 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 29 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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