Electrical and Electronic Engineering Technologists and Technicians
In short: today's best AI models could do about 39% 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 48% by the end of 2028 if progress keeps its long-run pace. The conversations, in-person and hands-on work, about 52% of the time, stays with people.
Apply electrical and electronic theory and related knowledge, usually under the direction of engineering staff, to design, build, repair, adjust, and modify electrical components, circuitry, controls, and machinery for subsequent evaluation and use by engineering staff in making engineering design decisions.
95,130 people do this job in the US. $78,190 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 on2 h
- A person checks AI's work13 h
- Desk work AI can't do yet4 h
- Stays with people21 h
Electrical and Electronic Engineering Technologists and Technicians, now: of a 40-hour week, AI could take on 2 hours, 13 hours become checking its work, 4 hours are desk work it can't do yet, and 21 hours stay with people.
The largest pieces: Review plans against codes (about 3 h, a person checks); Produce electronics drawings (about 2 h, a person checks); Conduct cost studies (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.
- 45%
- 3%
- 2%
- 7%
- 43%
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 39% 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, 11%. Today's estimate: 39%.
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 28 tasks showed up. Within each of Anthropic's methods, never across a change: 0.22% to 0.16% (released February and March 2025); 0.2% to 0.098% (August 2025 to February 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.22% | 84 of 708 | 7 of 28 |
| Released March 2025 | 0.16% | 107 of 703 | 9 of 28 |
| The week of Aug 4, 2025 (released September 2025) | 0.2% | 95 of 655 | 6 of 28 |
| The week of Nov 13, 2025 (released January 2026) | 0.091% | 168 of 672 | 6 of 28 |
| The week of Feb 5, 2026 (released March 2026) | 0.098% | 165 of 677 | 6 of 28 |
| April 2026 (released June 2026) | none | n/a | 0 of 28 |
| May 2026 (released June 2026) | none | n/a | 0 of 28 |
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 59% of this job's working time as physical work. For 33% of the working time, a robot has been shown doing most of the task somewhere: 33% in a purpose-built cell. 0.33 of 3, the 371st highest of the 923 jobs.
- Not physical 41%
- No robot shown 26%
- In a purpose-built cell 33%
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
51% of the working time: the conversation, in-person and hands-on parts of the tasks.
- Install control and automation systems, the hands-on work, 13%
- Repair electronics equipment, the hands-on work, 10%
- Assemble and test circuitry, the hands-on work, 7%
- Assemble electrical prototypes, the hands-on work, 4%
- Take part in training, the in-person work, 3%
- Resolve malfunctions with manufacturers, the hands-on work, 3%
What becomes checking the machine
35% 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 12% is desk work that is small if wrong, which can be handed over with lighter checks.
- Review plans against codes, severe if wrong, 8%
- Design electrical schematics, severe if wrong, 5%
- Produce electronics drawings, costly if wrong, 4%
- Calculate specifications and estimates, costly if wrong, 3%
- Run quality control programs, costly if wrong, 3%
- Integrate software and hardware, costly if wrong, 2%
What to learn
- Briefing a model and checking its drafts. About 45% 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 hands-on craft. About 43% of the time is hands-on work, which no model here does; robots are rated separately on this page.
- 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.
- 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 . 28 tasks from .
| Task | ||||
|---|---|---|---|---|
| Install or maintain electrical control systems, industrial automation systems, or electrical equipment, including control circuits, variable speed drives, or programmable logic controllers.Control circuits, drives and controllers installed and maintained.Done more than yearly by most who do it.Robots: no robot shown. Anthropic's rating. | 13% | 5 h1.7 h to 2.1 work days | Hands-on 100% | Stays with people |
| Modify, maintain, or repair electronics equipment or systems to ensure proper functioning.Equipment modified and repaired by hand.Done daily by most who do it. Robots: no robot shown. Anthropic's rating. | 10% | 2.5 h50 min to 5 h | Hands-on 100% | Stays with people |
| Conduct statistical studies to analyze or compare production costs for sustainable or nonsustainable designs.Statistical studies on paper.Done more than monthly by most who do it. | 9% | 1.7 work days5 h to 4.2 work days | Documents 100% | 41%Half by Dec 2026 |
| Review electrical engineering plans to ensure adherence to design specifications and compliance with applicable electrical codes and standards.Plans read against the specifications and codes.Done more than weekly by most who do it. | 8% | 2.5 h50 min to 6.7 h | Documents 100% | 96%Half by now |
| Assemble, test, or maintain circuitry or electronic components, according to engineering instructions, technical manuals, or knowledge of electronics, using hand or power tools.Circuitry built and tested with hand and power tools.Done daily by most who do it. Robots: in a purpose-built cell, Fuji NXT-R SMT placement machine (sold). Anthropic's rating. | 7% | 2.5 h50 min to 6.7 h | Hands-on 100% | Stays with people |
| Design or modify engineering schematics for electrical transmission and distribution systems or for electrical installation in residential, commercial, or industrial buildings, using computer-aided design (CAD) software.Schematics designed in CAD.Done more than yearly by most who do it. | 5% | 5 h1.7 h to 1.9 work days | Documents 100% | 77%Half by now |
| Produce electronics drawings or other graphics representing industrial control, instrumentation, sensors, or analog or digital telecommunications networks, using computer-aided design (CAD) software.Drawings made in CAD.Done more than yearly by most who do it. | 4% | 3.3 h1.3 h to 1.3 work days | Documents 100% | 91%Half by now |
| Specify, coordinate, or conduct quality control or quality assurance programs or procedures.Procedures written and checks made at the bench.Done daily by most who do it.Robots: in a purpose-built cell, Koh Young Zenith / Zenith Alpha 3D AOI (sold). Anthropic's rating. | 4% | 3.3 h50 min to 1.3 work days | Documents 60%, hands-on 40% | 48%Desk part half by now |
| Assemble electrical systems or prototypes, using hand tools or measuring instruments.Systems built with hand tools and instruments.Done more than yearly by most who do it. Robots: in a purpose-built cell, Japan Unix soldering robots (UNIX-GF / HFR / VFR / DF series) (sold). Anthropic's rating. | 4% | 3.3 h50 min to 6.7 h | Hands-on 100% | Stays with people |
| Supervise the installation or operation of electronic equipment or systems.Overseeing installation on site, with the plans.Done more than yearly by most who do it. | 4% | 3.3 h50 min to 1.7 work days | In person 70%, documents 30% | 21%Desk part half by now |
| Participate in training or continuing education activities to stay abreast of engineering or industry advances.Attendance and learning only the technician can do.Done more than yearly by most who do it. | 3% | 3.3 h50 min to 6.7 h | In person 100% | Stays with people |
| Integrate software or hardware components, using computer, microprocessor, or control architecture.Components integrated on the bench and in code.Done more than yearly by most who do it.Robots: no robot shown. Anthropic's rating. | 3% | 3.3 h1.3 h to 1.3 work days | Documents 60%, hands-on 40% | 55%Desk part 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.
- Calibration Technologists and Technicians37% now, 55% by 2028
- Electronics Engineers, Except Computer26% now, 73% by 2028
- Mechanical Engineering Technologists and Technicians35% now, 53% by 2028
- Electrical and Electronics Repairers, Commercial and Industrial Equipment26% now, 32% by 2028
- Robotics Technicians22% now, 26% by 2028
- Electrical and Electronics Installers and Repairers, Transportation Equipment8% now, 8% by 2028
Where this job works
The industry groups that employ the most of it (BLS, May 2025).
- Architectural, Engineering, and Related Services12,120 people
- Semiconductor and Other Electronic Component Manufacturing9,690 people
- Navigational, Measuring, Electromedical, and Control Instruments Manufacturing7,870 people
- Federal Executive Branch7,330 people
- Electric Power Generation, Transmission and Distribution6,020 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 Electrical and Electronic Engineering Technologists and Technicians is within reach of AI now?
- An estimated 39% of the working time is within reach of AI models now and 48% 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 Electrical and Electronic Engineering Technologists and Technicians 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: Review plans against codes (96% of the task's time now); Produce electronics drawings (91% of the task's time now, 100% by the end of 2028); and Conduct cost studies (41% of the task's time now, 100% by the end of 2028).
- Which tasks of Electrical and Electronic Engineering Technologists and Technicians stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Install control and automation systems; Repair electronics equipment; and Assemble and test circuitry. Together such tasks are about 42% of the working time, and the people and body parts of the other tasks stay with people too.
- What should Electrical and Electronic Engineering Technologists and Technicians learn as AI takes on more of the work?
- By the job's own task-by-task review, the first things to learn are briefing a model and checking its drafts; the hands-on craft; and reviewing work you did not do yourself. By the end of 2028 on the long-run pace at four in five, about 51% of the working time stays with people, 35% becomes checking a model's work and 12% 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 Electrical and Electronic Engineering Technologists and Technicians?
- 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 2%. 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 Electrical and Electronic Engineering Technologists and Technicians?
- Anthropic's robot exposure rating (September 2026) finds 59% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 33% of the working time. Its index is 0.33 of 3. One example: Fuji NXT-R SMT placement machine for "assemble and test circuitry". 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 28 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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