Manufacturing Engineers
In short: today's best AI models could do about 48% 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 91% by the end of 2028 if progress keeps its long-run pace. The people and hands-on work, about 6% of the time, stays with people.
Design, integrate, or improve manufacturing systems or related processes. May work with commercial or industrial designers to refine product designs to increase producibility and decrease costs.
$102,440 a year (for the broader BLS group this job sits in).
A typical 40-hour week
Not yet reviewed task by task- AI could take on19 h
- A person checks AI's work0 h
- Desk work AI can't do yet18 h
- Stays with people3 h
Manufacturing Engineers, now: of a 40-hour week, AI could take on 19 hours, 0 hours become checking its work, 18 hours are desk work it can't do yet, and 3 hours stay with people.
The largest pieces: Troubleshoot new or existing product problems involving designs, materials, or processes (about 3 h); Investigate or resolve operational problems, such as material use variances or bottlenecks (about 3 h); Provide technical expertise or support related to manufacturing (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.
- 94%
- 2%
- 4%
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, 0%. With Claude Mythos Preview (early), measured in April 2026, 8%. Today's estimate: 48%.
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, 0.12% went to this job's tasks in May 2026, the 150th largest of the 447 jobs that showed up at all; 6 of its 24 tasks showed up. Within each of Anthropic's methods, never across a change: 0.012% to 0.013% (released February and March 2025); 0.013% to 0.013% (August 2025 to February 2026); 0.068% to 0.12% (April to May 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.012% | 509 of 708 | 3 of 24 |
| Released March 2025 | 0.013% | 472 of 703 | 3 of 24 |
| The week of Aug 4, 2025 (released September 2025) | 0.013% | 422 of 655 | 3 of 24 |
| The week of Nov 13, 2025 (released January 2026) | 0.016% | 420 of 672 | 3 of 24 |
| The week of Feb 5, 2026 (released March 2026) | 0.013% | 456 of 677 | 3 of 24 |
| April 2026 (released June 2026) | 0.068% | 203 of 434 | 4 of 24 |
| May 2026 (released June 2026) | 0.12% | 150 of 447 | 6 of 24 |
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 almost none of this job's working time as physical work, so robots do not reach it.
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 . 24 tasks from .
| Task | Kind | |||
|---|---|---|---|---|
| Apply continuous improvement methods, such as lean manufacturing, to enhance manufacturing quality, reliability, or cost-effectiveness.Done daily by most who do it. | 15% | 1.7 work days3.3 h to 1.3 work weeks | 24%Half by May 2027 | |
| Troubleshoot new or existing product problems involving designs, materials, or processes.Done several times a day by most who do it. | 11% | 4.2 h1.7 h to 2.1 work days | 79%Half by now | |
| Identify opportunities or implement changes to improve manufacturing processes or products or to reduce costs, using knowledge of fabrication processes, tooling and production equipment, assembly methods, quality control standards, or product design, materials and parts.Done more than monthly by most who do it. | 9% | 6.7 h2.5 h to 4.2 work days | 52%Half by now | |
| Incorporate new manufacturing methods or processes to improve existing operations.Done more than yearly by most who do it. | 9% | 3.3 work days6.7 h to 2 work weeks | 10%Half by Oct 2027 | |
| Investigate or resolve operational problems, such as material use variances or bottlenecks.Done more than weekly by most who do it. | 9% | 3.3 h1.3 h to 1.7 work days | 84%Half by now | |
| Develop sustainable manufacturing technologies to reduce greenhouse gas emissions, minimize raw material use, replace toxic materials with non-toxic materials, replace non-renewable materials with renewable materials, or reduce waste.Done more than yearly by most who do it. | 8% | 4.2 work days6.7 h to 3.3 work weeks | 5%Half by Apr 2028 | |
| Provide technical expertise or support related to manufacturing.Done more than weekly by most who do it. AI observed on this task. | 7% | 1.7 h25 min to 5 h | 94%Half by now | |
| Prepare reports summarizing information or trends related to manufacturing performance.Done more than weekly by most who do it. | 4% | 4.2 h1.7 h to 1 work day | 97%Half by now | |
| Determine root causes of failures or recommend changes in designs, tolerances, or processing methods, using statistical procedures.Done more than monthly by most who do it. | 4% | 6.7 h2.5 h to 3.3 work days | 59%Half by now | |
| Design tests of finished products or process capabilities to establish standards or validate process requirements.Done more than monthly by most who do it. | 3% | 1.7 work days3.3 h to 1 work week | 28%Half by Apr 2027 | |
| Prepare documentation for new manufacturing processes or engineering procedures.Done more than monthly by most who do it. | 3% | 5 h2.1 h to 2.5 work days | 74%Half by now | |
| Design layout of equipment or workspaces to achieve maximum efficiency.Done more than yearly by most who do it. | 2% | 1.7 work days3.3 h to 1 work week | 28%Half by Apr 2027 |
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.
Where this job works
The industry groups that employ the most of it (BLS, May 2025). Counts are for the broader BLS group this job sits in.
- Aerospace Product and Parts Manufacturing25,680 people
- Architectural, Engineering, and Related Services25,420 people
- Semiconductor and Other Electronic Component Manufacturing20,060 people
- Machinery Manufacturing (3331, 3332, 3334, and 3339 only)18,200 people
- Motor Vehicle Parts Manufacturing17,250 people
Where the most of these jobs are
The metro areas with the most people in it (BLS, May 2025). Counts are for the broader BLS group this job sits in.
Questions about this job
- How much of the work of Manufacturing Engineers is within reach of AI now?
- An estimated 48% of the working time is within reach of AI models now and 91% by the end of 2028, on METR's long-run pace at four in five (79% to 93% across the three paces the site shows). 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 Manufacturing Engineers 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: Troubleshoot new or existing product problems involving designs, materials, or processes (79% of the task's time now, 100% by the end of 2028); Investigate or resolve operational problems, such as material use variances or bottlenecks (84% of the task's time now, 100% by the end of 2028); and Provide technical expertise or support related to manufacturing (94% of the task's time now, 100% by the end of 2028).
- Which tasks of Manufacturing Engineers stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Design, install, or troubleshoot manufacturing equipment; Evaluate manufactured products according to specifications and quality standards; and Supervise technicians, technologists, analysts, administrative staff, or other engineers. Together such tasks are about 6% of the working time.
- Do people already use AI for the work of Manufacturing Engineers?
- In the Claude.ai conversations Anthropic sampled for May 2026 and tied to a work task, 0.12% went to this job's tasks, the 150th largest share of the 447 jobs that showed up; 6 of its 24 tasks appeared. Anthropic's labor market measure puts the share of the job's tasks seen in real Claude use at work at 4%. 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 Manufacturing Engineers?
- Anthropic's robot exposure rating (September 2026) finds almost none of the working time is physical work, so robots do not reach it.
- How is this estimated?
- From the 24 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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