Industrial Engineers
In short: today's best AI models could do about 60% 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 86% by the end of 2028 if progress keeps its long-run pace. The conversations, in-person and hands-on work, about 14% of the time, stays with people.
Design, develop, test, and evaluate integrated systems for managing industrial production processes, including human work factors, quality control, inventory control, logistics and material flow, cost analysis, and production coordination.
365,740 people do this job in the US. $102,440 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 work24 h
- Desk work AI can't do yet10 h
- Stays with people6 h
Industrial Engineers, now: of a 40-hour week, AI could take on 0 hours, 24 hours become checking its work, 10 hours are desk work it can't do yet, and 6 hours stay with people.
The largest pieces: Plan the sequence of operations (about 4 h, a person checks); Recommend utilization improvements (about 3 h, a person checks); Design plant layouts (about 2 h, a person checks).
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.
- 83%
- 3%
- 8%
- 5%
- 2%
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 60% 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, 7%. Today's estimate: 60%.
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, 0.021% went to this job's tasks in May 2026, the 318th largest of the 447 jobs that showed up at all; 2 of its 20 tasks showed up. Within each of Anthropic's methods, never across a change: 0.03% to 0.011% (released February and March 2025); 0.0047% to 0.014% (August 2025 to February 2026); 0.023% to 0.021% (April to May 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.03% | 363 of 708 | 9 of 20 |
| Released March 2025 | 0.011% | 495 of 703 | 2 of 20 |
| The week of Aug 4, 2025 (released September 2025) | 0.0047% | 536 of 655 | 1 of 20 |
| The week of Nov 13, 2025 (released January 2026) | 0.0062% | 545 of 672 | 3 of 20 |
| The week of Feb 5, 2026 (released March 2026) | 0.014% | 443 of 677 | 4 of 20 |
| April 2026 (released June 2026) | 0.023% | 310 of 434 | 2 of 20 |
| May 2026 (released June 2026) | 0.021% | 318 of 447 | 2 of 20 |
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.
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
14% of the working time: the conversation, in-person and hands-on parts of the tasks.
- Develop standards with management and users, the conversation, 4%
- Direct inspection and testing staff, the in-person work, 3%
- Implement quality control, the conversation, 2%
- Evaluate equipment accuracy, the hands-on work, 2%
- Confer with clients, vendors and staff, the conversation, 2%
- Set disposition methods for defective parts, the conversation, 1.0%
What becomes checking the machine
85% 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.
- Plan the sequence of operations, costly if wrong, 16%
- Recommend utilization improvements, costly if wrong, 12%
- Develop methods and labor standards, costly if wrong, 12%
- Design plant layouts, costly if wrong, 9%
- Set quality objectives from data, costly if wrong, 8%
- Estimate production costs and savings, costly if wrong, 6%
What to learn
- 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.
- Briefing a model and checking its drafts. About 83% of the time is documents and data, the part models reach first: writing a clear brief, giving the right material, and checking what comes back.
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 . 20 tasks from .
| Task | ||||
|---|---|---|---|---|
| Plan and establish sequence of operations to fabricate and assemble parts or products and to promote efficient utilization.Process planning at the desk.Done more than weekly by most who do it. | 16% | 1 work day2.5 h to 2.1 work days | Documents 100% | 66%Half by now |
| Recommend methods for improving utilization of personnel, material, and utilities.Written recommendations from the analysis.Done more than weekly by most who do it. | 12% | 6.7 h1.7 h to 1.7 work days | Documents 100% | 69%Half by now |
| Develop manufacturing methods, labor utilization standards, and cost analysis systems to promote efficient staff and facility utilization.Designing the methods and standards at the desk.Done more than monthly by most who do it. | 12% | 1.7 work days4.2 h to 1 work week | Documents 100% | 32%Half by Feb 2027 |
| Draft and design layout of equipment, materials, and workspace to illustrate maximum efficiency using drafting tools and computer.Layout design in CAD.Done more than yearly by most who do it. | 9% | 1 work day3.3 h to 2.5 work days | Documents 100% | 69%Half by now |
| Analyze statistical data and product specifications to determine standards and establish quality and reliability objectives of finished product.Analysis of the quality data.Done more than monthly by most who do it. | 8% | 6.7 h2.5 h to 2.5 work days | Documents 100% | 69%Half by now |
| Estimate production costs, cost saving methods, and the effects of product design changes on expenditures for management review, action, and control.Cost analysis at the desk.Done daily by most who do it. | 6% | 5 h1.7 h to 1.7 work days | Documents 100% | 80%Half by now |
| Evaluate precision and accuracy of production and testing equipment and engineering drawings to formulate corrective action plan.Checking equipment and drawings, then the corrective plan.Done more than monthly by most who do it. | 6% | 5 h2.5 h to 1.7 work days | Documents 70%, hands-on 30% | 65%Desk part half by now |
| Communicate with management and user personnel to develop production and design standards.Meetings to agree the standards, then written up.Done more than weekly by most who do it. | 5% | 3.3 h1.7 h to 6.7 h | Conversation 70%, documents 30% | 30%Desk part half by now |
| Coordinate and implement quality control objectives, activities, or procedures to resolve production problems, maximize product reliability, or minimize costs.Procedures written, worked through with the teams, some on the floor.Done more than yearly by most who do it. | 4% | 6.7 h2.5 h to 3.3 work days | Documents 50%, conversation 30%, in person 20% | 30%Desk part half by now |
| Implement methods and procedures for disposition of discrepant material and defective or damaged parts, and assess cost and responsibility.Written procedures and the cost and responsibility worked out.Done more than monthly by most who do it. | 3% | 3.3 h1.7 h to 6.7 h | Documents 70%, conversation 30% | 70%Desk part half by now |
| Direct workers engaged in product measurement, inspection, and testing activities to ensure quality control and reliability.On the floor with the inspectors.Done more than monthly by most who do it. | 3% | 1.7 h38 min to 5 h | In person 100% | Stays with people |
| Apply statistical methods and perform mathematical calculations to determine manufacturing processes, staff requirements, and production standards.Calculations and analysis at the desk.Done more than monthly by most who do it. | 3% | 5 h1.7 h to 2.1 work days | Documents 100% | 73%Half by now |
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.
Where this job works
The industry groups that employ the most of it (BLS, May 2025).
- 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).
Questions about this job
- How much of the work of Industrial Engineers is within reach of AI now?
- An estimated 60% of the working time is within reach of AI models now and 86% by the end of 2028, on METR's long-run pace at four in five (84% to 86% 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 Industrial 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: Plan the sequence of operations (66% of the task's time now, 100% by the end of 2028); Recommend utilization improvements (69% of the task's time now, 100% by the end of 2028); and Design plant layouts (69% of the task's time now, 100% by the end of 2028).
- Which tasks of Industrial Engineers stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Direct inspection and testing staff; and Confer with clients, vendors and staff. Together such tasks are about 5% of the working time, and the people and body parts of the other tasks stay with people too.
- What should Industrial Engineers learn as AI takes on more of the work?
- By the job's own task-by-task review, the first things to learn are reviewing work you did not do yourself; and briefing a model and checking its drafts. By the end of 2028 on the long-run pace at four in five, about 14% of the working time stays with people, 85% becomes checking a model's work and 1% 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 Industrial Engineers?
- In the Claude.ai conversations Anthropic sampled for May 2026 and tied to a work task, 0.021% went to this job's tasks, the 318th largest share of the 447 jobs that showed up; 2 of its 20 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 Industrial 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 20 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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