Architectural and Engineering Managers
In short: today's best AI models could do about 41% 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 72% by the end of 2028 if progress keeps its long-run pace. The conversations, in-person and hands-on work, about 28% of the time, stays with people.
Plan, direct, or coordinate activities in such fields as architecture and engineering or research and development in these fields.
220,260 people do this job in the US. $171,270 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 work16 h
- Desk work AI can't do yet13 h
- Stays with people11 h
Architectural and Engineering Managers, now: of a 40-hour week, AI could take on 0 hours, 16 hours become checking its work, 13 hours are desk work it can't do yet, and 11 hours stay with people.
The largest pieces: Coordinate technical work (about 3 h, a person checks); Assess project feasibility (about 3 h, a person checks); Set engineering standards (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.
- 71%
- 1%
- 24%
- 4%
- 0%
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 41% 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: 41%.
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, 0.064% went to this job's tasks in May 2026, the 203rd largest of the 447 jobs that showed up at all; 3 of its 19 tasks showed up. Within each of Anthropic's methods, never across a change: 0.11% to 0.086% (released February and March 2025); 0.051% to 0.12% (August 2025 to February 2026); 0.068% to 0.064% (April to May 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.11% | 156 of 708 | 6 of 19 |
| Released March 2025 | 0.086% | 175 of 703 | 5 of 19 |
| The week of Aug 4, 2025 (released September 2025) | 0.051% | 241 of 655 | 4 of 19 |
| The week of Nov 13, 2025 (released January 2026) | 0.085% | 171 of 672 | 6 of 19 |
| The week of Feb 5, 2026 (released March 2026) | 0.12% | 137 of 677 | 6 of 19 |
| April 2026 (released June 2026) | 0.068% | 194 of 434 | 3 of 19 |
| May 2026 (released June 2026) | 0.064% | 203 of 447 | 3 of 19 |
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
27% of the working time: the conversation, in-person and hands-on parts of the tasks.
- Coordinate technical work, the conversation, 13%
- Direct facility installation and testing, the in-person work, 4%
- Negotiate specifications with clients, the conversation, 3%
- Confer with staff on projects, the conversation, 3%
- Approve design changes, the conversation, 2%
- Present to clients, the conversation, 0.9%
What becomes checking the machine
72% 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.
- Set engineering standards, costly if wrong, 22%
- Assess project feasibility, costly if wrong, 12%
- Coordinate technical work, costly if wrong, 9%
- Approve design changes, severe if wrong, 6%
- Direct facility installation and testing, severe if wrong, 4%
- Evaluate environmental impacts, costly if wrong, 3%
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 71% 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.
- The conversations. About 28% of the time is conversation and in-person work, which this site leaves with people: listening, explaining, persuading, calming.
- 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 . 19 tasks from .
| Task | ||||
|---|---|---|---|---|
| Manage the coordination and overall integration of technical activities in architecture or engineering projects.Mostly conversation with the leads, plus reading and deciding.Done several times a day by most who do it. | 22% | 3.3 h1.7 h to 1.7 work days | Conversation 60%, documents 40% | 37%Desk part half by now |
| Develop or implement policies, standards, or procedures for engineering and technical work.Writing at the desk.Done more than monthly by most who do it. | 22% | 1.7 work days3.3 h to 1 work week | Documents 100% | 28%Half by Apr 2027 |
| Assess project feasibility by analyzing technology, resource needs, or market demand.Analysis at the desk.Done more than weekly by most who do it. | 12% | 6.7 h1.7 h to 2.5 work days | Documents 100% | 55%Half by now |
| Plan or direct the installation, testing, operation, maintenance, or repair of facilities or equipment.Plans at the desk and time on site.Done more than yearly by most who do it. | 8% | 6.7 h1.7 h to 2.5 work days | Documents 50%, in person 50% | 28%Desk part half by now |
| Direct, review, or approve project design changes.Reviews at the desk and conversations with the engineers.Done more than weekly by most who do it. | 8% | 1.7 h25 min to 5 h | Documents 70%, conversation 30% | 66%Desk part half by now |
| Consult or negotiate with clients to prepare project specifications.Conversations with the client and the spec drafted.Done more than weekly by most who do it. | 4% | 2.5 h50 min to 1.3 work days | Conversation 70%, documents 30% | 26%Desk part half by now |
| Evaluate the environmental impacts of engineering, architecture, or research and development activities.Analysis at the desk.Done more than yearly by most who do it. | 3% | 6.7 h1.7 h to 2.5 work days | Documents 100% | 55%Half by now |
| Identify environmental threats or opportunities associated with the development and launch of new technologies.Analysis at the desk.Done more than yearly by most who do it. | 3% | 6.7 h1.7 h to 2.5 work days | Documents 100% | 55%Half by now |
| Develop or implement programs to improve sustainability or reduce the environmental impacts of engineering or architecture activities or operations.Design on paper and coordination.Done more than yearly by most who do it. | 3% | 1.7 work days3.3 h to 1 work week | Documents 80%, conversation 20% | 22%Desk part half by Apr 2027 |
| Confer with management, production, or marketing staff to discuss project specifications or procedures.Working conversations.Done more than monthly by most who do it. | 3% | 1.3 h25 min to 3.3 h | Conversation 100% | Stays with people |
| Evaluate environmental regulations or social pressures related to environmental issues to inform strategic or operational decision-making.Reading and analysis at the desk.Done yearly or less by most who do it. | 2% | 5 h1.7 h to 2.5 work days | Documents 100% | 67%Half by now |
| Perform administrative functions, such as reviewing or writing reports, approving expenditures, enforcing rules, or purchasing of materials or services.Reports and approvals at the desk.Done more than monthly by most who do it. | 2% | 1.7 h25 min to 3.3 h | Documents 60%, systems 40% | 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.
Where this job works
The industry groups that employ the most of it (BLS, May 2025).
- Architectural, Engineering, and Related Services57,730 people
- Management of Companies and Enterprises14,950 people
- Scientific Research and Development Services13,240 people
- Aerospace Product and Parts Manufacturing11,760 people
- Navigational, Measuring, Electromedical, and Control Instruments Manufacturing9,080 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 Architectural and Engineering Managers is within reach of AI now?
- An estimated 41% of the working time is within reach of AI models now and 72% by the end of 2028, on METR's long-run pace at four in five (67% to 72% 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 Architectural and Engineering Managers 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: Coordinate technical work (37% of the task's time now); Assess project feasibility (55% of the task's time now, 100% by the end of 2028); and Set engineering standards (28% of the task's time now, 99% by the end of 2028).
- Which tasks of Architectural and Engineering Managers stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Confer with staff on projects; and Win support from officials and the public. Together such tasks are about 3% of the working time, and the people and body parts of the other tasks stay with people too.
- What should Architectural and Engineering Managers 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; briefing a model and checking its drafts; and the conversations. By the end of 2028 on the long-run pace at four in five, about 27% of the working time stays with people, 72% 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 Architectural and Engineering Managers?
- In the Claude.ai conversations Anthropic sampled for May 2026 and tied to a work task, 0.064% went to this job's tasks, the 203rd largest share of the 447 jobs that showed up; 3 of its 19 tasks appeared. Anthropic's labor market measure puts the share of the job's tasks seen in real Claude use at work at 3%. 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 Architectural and Engineering Managers?
- 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 19 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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