Aerospace Engineers
In short: today's best AI models could do about 38% 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 78% by the end of 2028 if progress keeps its long-run pace. The conversations, in-person and hands-on work, about 22% of the time, stays with people.
Perform engineering duties in designing, constructing, and testing aircraft, missiles, and spacecraft. May conduct basic and applied research to evaluate adaptability of materials and equipment to aircraft design and manufacture. May recommend improvements in testing equipment and techniques.
67,710 people do this job in the US. $134,960 a year.
Reviewed on October 2, 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 work15 h
- Desk work AI can't do yet16 h
- Stays with people9 h
Aerospace Engineers, now: of a 40-hour week, AI could take on 0 hours, 15 hours become checking its work, 16 hours are desk work it can't do yet, and 9 hours stay with people.
The largest pieces: Write technical reports and handbooks (about 4 h, a person checks); Evaluate designs for conformance (about 2 h, a person checks); Diagnose performance problems (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.
- 77%
- 1%
- 13%
- 0%
- 9%
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 38% 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, 3%. Today's estimate: 38%.
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, 0.074% went to this job's tasks in May 2026, the 193rd largest of the 447 jobs that showed up at all; 3 of its 14 tasks showed up. Within each of Anthropic's methods, never across a change: 0.033% to 0.021% (released February and March 2025); 0.02% to 0.016% (August 2025 to February 2026); 0.079% to 0.074% (April to May 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.033% | 347 of 708 | 4 of 14 |
| Released March 2025 | 0.021% | 412 of 703 | 3 of 14 |
| The week of Aug 4, 2025 (released September 2025) | 0.02% | 374 of 655 | 1 of 14 |
| The week of Nov 13, 2025 (released January 2026) | 0.017% | 410 of 672 | 1 of 14 |
| The week of Feb 5, 2026 (released March 2026) | 0.016% | 427 of 677 | 2 of 14 |
| April 2026 (released June 2026) | 0.079% | 178 of 434 | 3 of 14 |
| May 2026 (released June 2026) | 0.074% | 193 of 447 | 3 of 14 |
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
22% of the working time: the conversation, in-person and hands-on parts of the tasks.
- Direct R&D programs, the conversation, 7%
- Plan and run prototype tests, the hands-on work, 6%
- Direct engineering staff, the conversation, 4%
- Diagnose performance problems, the hands-on work, 3%
- Coordinate customer problem investigations, the conversation, 2%
What becomes checking the machine
76% 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.
- Write technical reports and handbooks, severe if wrong, 11%
- Create conceptual designs, severe if wrong, 11%
- Build analysis models, severe if wrong, 11%
- Analyze feasibility and cost, costly if wrong, 9%
- Diagnose performance problems, severe if wrong, 8%
- Evaluate designs for conformance, severe if wrong, 6%
What to learn
- 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.
- Briefing a model and checking its drafts. About 77% 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.
- Dealing with people outside the organization. Customers, patients, suppliers or the public: trust with them is built by a person.
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 | ||||
|---|---|---|---|---|
| Diagnose performance problems by reviewing reports or documentation from customers or field engineers or by inspecting malfunctioning or damaged products.Reading the field reports and examining the damaged parts.Done more than monthly by most who do it. | 11% | 6.7 h1.7 h to 2.5 work days | Documents 70%, hands-on 30% | 39%Desk part half by now |
| Write technical reports or other documentation, such as handbooks or bulletins, for use by engineering staff, management, or customers.Writing the reports, handbooks and bulletins.Done more than monthly by most who do it. AI observed on this task. | 11% | 6.7 h3.3 h to 2.5 work days | Documents 100% | 80%Half by now |
| Formulate conceptual design of aeronautical or aerospace products or systems to meet customer requirements or conform to environmental regulations.Design work on paper and in the modeling tools.Done more than yearly by most who do it. | 11% | 2.1 work days6.7 h to 4.2 work days | Documents 100% | 35%Half by Jan 2027 |
| Plan or conduct experimental, environmental, operational, or stress tests on models or prototypes of aircraft or aerospace systems or equipment.Planning the tests, then running them in the lab or on the rig.Done more than yearly by most who do it. | 11% | 2.1 work days6.7 h to 4.2 work days | Documents 50%, hands-on 50% | 17%Desk part half by Jan 2027 |
| Formulate mathematical models or other methods of computer analysis to develop, evaluate, or modify design, according to customer engineering requirements.Building the mathematical models and running the analyses.Done more than monthly by most who do it. | 11% | 2.1 work days3.3 h to 1.3 work weeks | Documents 100% | 18%Half by Jul 2027 |
| Direct aerospace research and development programs.Mostly conversation with the program's people, plus reading and deciding.Done hourly or more by most who do it. | 11% | 2.1 work days6.7 h to 4.2 work days | Conversation 60%, documents 40% | 14%Desk part half by Jan 2027 |
| Analyze project requests, proposals, or engineering data to determine feasibility, productibility, cost, or production time of aerospace or aeronautical products.Working through proposals and data to say what can be built, for what, by when.Done more than monthly by most who do it. | 10% | 1.7 work days3.3 h to 4.2 work days | Documents 100% | 31%Half by Mar 2027 |
| Direct or coordinate activities of engineering or technical personnel involved in designing, fabricating, modifying, or testing of aircraft or aerospace products.Mostly conversation with the engineers and technicians, plus reading and deciding.Done daily by most who do it. | 6% | 3.3 h50 min to 2.1 work days | Conversation 60%, documents 40% | 25%Desk part half by now |
| Evaluate product data or design from inspections or reports for conformance to engineering principles, customer requirements, environmental regulations, or quality standards.Reading the inspection data and designs against the principles and requirements.Done daily by most who do it. | 6% | 3.3 h1.7 h to 1.3 work days | Documents 100% | 97%Half by now |
| Plan or coordinate investigation and resolution of customers' reports of technical problems with aircraft or aerospace vehicles.Planning the investigation and keeping customers and the team in the conversation.Done more than monthly by most who do it. | 4% | 6.7 h1.7 h to 2.5 work days | Documents 50%, conversation 50% | 28%Desk part half by now |
| Develop design criteria for aeronautical or aerospace products or systems, including testing methods, production costs, quality standards, environmental standards, or completion dates.Writing the criteria a design must meet.Done more than monthly by most who do it. | 4% | 1.7 work days4.2 h to 4.2 work days | Documents 100% | 36%Half by Jan 2027 |
| Maintain records of performance reports for future reference.Filing the performance reports in the system.Done more than monthly by most who do it. | 1.0% | 50 min13 min to 2.5 h | Systems 100% | 99%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.
- Aerospace Engineering and Operations Technologists and Technicians10% now, 21% by 2028
- Electro-Mechanical and Mechatronics Technologists and Technicians20% now, 26% by 2028
- Avionics Technicians13% now, 15% by 2028
- Mechanical Engineering Technologists and Technicians35% now, 53% by 2028
- Mechanical Engineers23% now, 70% by 2028
- Aircraft Mechanics and Service Technicians11% now, 12% 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 Aerospace Engineers is within reach of AI now?
- An estimated 38% of the working time is within reach of AI models now and 78% by the end of 2028, on METR's long-run pace at four in five (72% to 78% 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 Aerospace 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: Write technical reports and handbooks (80% of the task's time now, 100% by the end of 2028); Evaluate designs for conformance (97% of the task's time now); and Diagnose performance problems (39% of the task's time now, 70% by the end of 2028).
- Which tasks of Aerospace Engineers stay with people?
- Every task has a desk part, so each can come partly within reach; the conversation, in-person and hands-on parts of each task stay with people, about 22% of the working time.
- What should Aerospace 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 judgment where errors are severe; 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 22% of the working time stays with people, 76% 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 Aerospace Engineers?
- In the Claude.ai conversations Anthropic sampled for May 2026 and tied to a work task, 0.074% went to this job's tasks, the 193rd largest share of the 447 jobs that showed up; 3 of its 14 tasks appeared. Anthropic's labor market measure puts the share of the job's tasks seen in real Claude use at work at 8%. 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 Aerospace 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 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 October 2, 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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