Electrical and Electronic Equipment Assemblers
In short: today's best AI models could do about 7% 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 the same by the end of 2028 if progress keeps its long-run pace. The conversations, in-person and hands-on work, about 93% of the time, stays with people.
Assemble or modify electrical or electronic equipment, such as computers, test equipment telemetering systems, electric motors, and batteries.
$45,850 a year (for the broader BLS group this job sits in).
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 on1 h
- A person checks AI's work2 h
- Desk work AI can't do yet0 h
- Stays with people37 h
Electrical and Electronic Equipment Assemblers, now: of a 40-hour week, AI could take on 1 hours, 2 hours become checking its work, 0 hours are desk work it can't do yet, and 37 hours stay with people.
The largest pieces: Keep production and time reports (about 1 h); Read schematics and work orders (about 1 h, a person checks); Test wiring and circuits (under an hour, 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.
- 3%
- 4%
- 3%
- 17%
- 73%
Anthropic's data does not cover this job.
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 7% 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: 8%.
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, 0.053% went to this job's tasks in May 2026, the 226th largest of the 447 jobs that showed up at all; 1 of its 17 tasks showed up. Within each of Anthropic's methods, never across a change: 0.0092% to 0.0051% (released February and March 2025); 0.0042% to 0.0025% (August 2025 to February 2026); 0.045% to 0.053% (April to May 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.0092% | 539 of 708 | 2 of 17 |
| Released March 2025 | 0.0051% | 579 of 703 | 2 of 17 |
| The week of Aug 4, 2025 (released September 2025) | 0.0042% | 552 of 655 | 2 of 17 |
| The week of Nov 13, 2025 (released January 2026) | 0.0019% | 649 of 672 | 1 of 17 |
| The week of Feb 5, 2026 (released March 2026) | 0.0025% | 630 of 677 | 1 of 17 |
| April 2026 (released June 2026) | 0.045% | 230 of 434 | 1 of 17 |
| May 2026 (released June 2026) | 0.053% | 226 of 447 | 1 of 17 |
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 86% of this job's working time as physical work. For 86% of the working time, a robot has been shown doing most of the task somewhere: 84% in a purpose-built cell, 3% in a structured facility. 0.89 of 3, the 186th highest of the 923 jobs.
- Not physical 14%
- In a purpose-built cell 84%
- In a structured facility 3%
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
93% of the working time: the conversation, in-person and hands-on parts of the tasks.
- Assemble systems and install components, the hands-on work, 29%
- Repair or replace components, the hands-on work, 11%
- Fabricate parts and coils, the hands-on work, 7%
- Explain assembly procedures, the in-person work, 7%
- Instruct customers on products, the in-person work, 6%
- Distribute materials to work areas, the hands-on work, 5%
What becomes checking the machine
4% 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 4% is desk work that is small if wrong, which can be handed over with lighter checks.
- Read schematics and work orders, costly if wrong, 3%
- Test wiring and circuits, costly if wrong, 0.8%
What to learn
- The hands-on craft. About 73% of the time is hands-on work, which no model here does; robots are rated separately on this page.
- The conversations. About 19% of the time is conversation and in-person work, which this site leaves with people: listening, explaining, persuading, calming.
- 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 . 17 tasks from .
| Task | ||||
|---|---|---|---|---|
| Assemble electrical or electronic systems or support structures and install components, units, subassemblies, wiring, or assembly casings, using rivets, bolts, soldering or micro-welding equipment.Riveting, bolting, soldering and micro-welding.Done hourly or more by most who do it. Robots: in a purpose-built cell, Robotiq Screwdriving Workcell with Universal Robots cobot (and Robotiq 2F-85/2F-140 grippers) (deployed). Anthropic's rating. | 29% | 1.3 h25 min to 3.3 h | Hands-on 100% | Stays with people |
| Adjust, repair, or replace electrical or electronic components to correct defects and to ensure conformance to specifications.Defects corrected at the bench.Done hourly or more by most who do it. Robots: in a purpose-built cell, VJ Electronix Summit LXi Auto (Summit rework series) (sold). Anthropic's rating. | 11% | 50 min17 min to 2.5 h | Hands-on 100% | Stays with people |
| Fabricate or form parts, coils, or structures according to specifications, using drills, calipers, cutters, or saws.Parts formed with drills, cutters and saws.Done daily by most who do it. Robots: in a purpose-built cell, Airbus robotic drilling cell (FANUC M-800iA/60 + FANUC CNC drilling effector) (deployed). Anthropic's rating. | 7% | 50 min17 min to 2.5 h | Hands-on 100% | Stays with people |
| Explain assembly procedures or techniques to other workers.Showing other workers at the bench.Done hourly or more by most who do it. | 7% | 25 min13 min to 1.3 h | In person 100% | Stays with people |
| Instruct customers in the installation, repair, or maintenance of products.Showing customers installation and repair, in person and by call.Done daily by most who do it. | 6% | 1.3 h25 min to 2.5 h | In person 60%, conversation 40% | Stays with people |
| Read and interpret schematic drawings, diagrams, blueprints, specifications, work orders, or reports to determine materials requirements or assembly instructions.Reading the drawing or order; the knowing is the assembler's own.Done hourly or more by most who do it. AI observed on this task. | 6% | 25 min8 min to 1.3 h | Documents 50%, in person 50% | 50%Desk part half by now |
| Distribute materials, supplies, or subassemblies to work areas.Supplies carried to the stations.Done several times a day by most who do it. Robots: in a structured facility, MiR100 AMR (MiR Fleet) (Mobile Industrial Robots) (deployed). Anthropic's rating. | 5% | 21 min8 min to 50 min | Hands-on 100% | Stays with people |
| Drill or tap holes in specified equipment locations to mount control units or to provide openings for elements, wiring, or instruments.Holes drilled and tapped by hand.Done hourly or more by most who do it.Robots: in a purpose-built cell, Universal Robots UR5 drilling/tapping cell (deployed). Anthropic's rating. | 5% | 38 min13 min to 1.7 h | Hands-on 100% | Stays with people |
| Position, align, or adjust workpieces or electrical parts to facilitate wiring or assembly.Aligning workpieces and parts by hand.Done hourly or more by most who do it. Robots: in a purpose-built cell, AgiBot (Zhiyuan) Genie G2 wheeled humanoid (deployed). Anthropic's rating. | 4% | 17 min4 min to 50 min | Hands-on 100% | Stays with people |
| Inspect or test wiring installations, assemblies, or circuits for resistance factors or for operation, and record results.Testing at the bench, with the results entered.Done daily by most who do it. Robots: in a purpose-built cell, Cirris harness/cable test systems (Easy-Touch Pro, 5150) with smart adapters (sold). Anthropic's rating. | 4% | 21 min8 min to 50 min | Hands-on 80%, systems 20% | 20%Desk part half by now |
| Complete, review, or maintain production, time, or component waste reports.Reports completed and kept.Done hourly or more by most who do it. | 4% | 25 min8 min to 1.3 h | Systems 100% | 100%Half by now |
| Pack finished assemblies for shipment, and transport them to storage areas, using hoists or handtrucks.Packing and moving with hoists or hand trucks.Done daily by most who do it. Robots: in a purpose-built cell, UR5 / UR10 collaborative robots in end-of-line packing and palletizing cells (Universal Robots) (deployed). Anthropic's rating. | 3% | 21 min8 min to 50 min | Hands-on 100% | Stays with people |
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.
- Electromechanical Equipment Assemblers2% now, 2% by 2028
- Aircraft Structure, Surfaces, Rigging, and Systems Assemblers4% now, 4% by 2028
- Engine and Other Machine Assemblers9% now, 9% by 2028
- Electric Motor, Power Tool, and Related Repairers3% now, 3% by 2028
- Industrial Machinery Mechanics13% now, 13% by 2028
- Electrical and Electronics Repairers, Commercial and Industrial Equipment26% now, 32% by 2028
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.
- Semiconductor and Other Electronic Component Manufacturing49,310 people
- Navigational, Measuring, Electromedical, and Control Instruments Manufacturing40,200 people
- Electrical Equipment Manufacturing30,940 people
- Other Electrical Equipment and Component Manufacturing27,620 people
- Machinery Manufacturing (3331, 3332, 3334, and 3339 only)14,550 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 Electrical and Electronic Equipment Assemblers is within reach of AI now?
- An estimated 8% of the working time is within reach of AI models now and 8% 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 Equipment Assemblers 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: Keep production and time reports (100% of the task's time now); Read schematics and work orders (50% of the task's time now); and Test wiring and circuits (20% of the task's time now).
- Which tasks of Electrical and Electronic Equipment Assemblers stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Assemble systems and install components; Repair or replace components; and Fabricate parts and coils. Together such tasks are about 86% of the working time, and the people and body parts of the other tasks stay with people too.
- What should Electrical and Electronic Equipment Assemblers learn as AI takes on more of the work?
- By the job's own task-by-task review, the first things to learn are the hands-on craft; the conversations; and reviewing work you did not do yourself. By the end of 2028 on the long-run pace at four in five, about 93% of the working time stays with people, 4% becomes checking a model's work and 4% 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 Equipment Assemblers?
- In the Claude.ai conversations Anthropic sampled for May 2026 and tied to a work task, 0.053% went to this job's tasks, the 226th largest share of the 447 jobs that showed up; 1 of its 17 tasks appeared. 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 Equipment Assemblers?
- Anthropic's robot exposure rating (September 2026) finds 86% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 86% of the working time, 3% in a structured facility. Its index is 0.89 of 3. One example: MiR100 AMR (MiR Fleet) for "distribute materials to work areas". 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 17 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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