Electrical Power-Line Installers and Repairers
In short: today's best AI models could do about 1% 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 99% of the time, stays with people.
Install or repair cables or wires used in electrical power or distribution systems. May erect poles and light or heavy duty transmission towers.
131,070 people do this job in the US. $95,320 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 work0 h
- Desk work AI can't do yet0 h
- Stays with people40 h
Electrical Power-Line Installers and Repairers, now: of a 40-hour week, AI could take on 0 hours, 0 hours become checking its work, 0 hours are desk work it can't do yet, and 40 hours stay with people.
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.
- 1%
- 0%
- 1%
- 1%
- 97%
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 1% 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, 1%. Today's estimate: 1%.
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 23 tasks showed up. Within each of Anthropic's methods, never across a change: 0.0024% to none (released February and March 2025); none to 0.0024% (August 2025 to February 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.0024% | 680 of 708 | 1 of 23 |
| Released March 2025 | none | n/a | 0 of 23 |
| The week of Aug 4, 2025 (released September 2025) | none | n/a | 0 of 23 |
| The week of Nov 13, 2025 (released January 2026) | none | n/a | 0 of 23 |
| The week of Feb 5, 2026 (released March 2026) | 0.0024% | 636 of 677 | 1 of 23 |
| April 2026 (released June 2026) | none | n/a | 0 of 23 |
| May 2026 (released June 2026) | none | n/a | 0 of 23 |
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 93% of this job's working time as physical work. For 61% of the working time, a robot has been shown doing most of the task somewhere: 42% in a purpose-built cell, 8% in a structured facility, 11% in any setting. 0.92 of 3, the 167th highest of the 923 jobs.
- Not physical 7%
- No robot shown 32%
- In a purpose-built cell 42%
- In a structured facility 8%
- In any setting 11%
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
99% of the working time: the conversation, in-person and hands-on parts of the tasks.
- Install and repair distribution systems, the hands-on work, 14%
- Dig holes and set poles, the hands-on work, 13%
- Replace damaged poles, the hands-on work, 9%
- String conductors and cables, the hands-on work, 9%
- Inspect lines from vehicles and aircraft, the hands-on work, 7%
- Fit cross-arms and insulators, the hands-on work, 6%
What becomes checking the machine
No desk work within reach by then in tasks where a mistake costs something.
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.
- The hands-on craft. About 97% of the time is hands-on work, which no model here does; robots are rated separately on this page.
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 . 23 tasks from .
| Task | ||||
|---|---|---|---|---|
| Install, maintain, and repair electrical distribution and transmission systems, including conduits, cables, wires, and related equipment, such as transformers, circuit breakers, and switches.Hands-on work on conduits, cables, transformers and switches.Done daily by most who do it. Robots: no robot shown. Anthropic's rating. | 14% | 4.2 h1.7 h to 1.7 work days | Hands-on 100% | Stays with people |
| Dig holes, using augers, and set poles, using cranes and power equipment.Augers, cranes and power equipment on the poles.Done daily by most who do it. Robots: in a purpose-built cell, RPD 35 / RPS 25 autonomous piling system (Built Robotics) (deployed). Anthropic's rating. | 13% | 3.3 h1.3 h to 6.7 h | Hands-on 100% | Stays with people |
| Replace or straighten damaged poles.Poles straightened or replaced.Done more than monthly by most who do it. Robots: no robot shown. Anthropic's rating. | 9% | 3.3 h1.7 h to 1.3 work days | Hands-on 100% | Stays with people |
| String wire conductors and cables between poles, towers, trenches, pylons, and buildings, setting lines in place and using winches to adjust tension.Lines strung and tensioned with winches.Done daily by most who do it. Robots: no robot shown. Anthropic's rating. | 9% | 3.3 h1.3 h to 1 work day | Hands-on 100% | Stays with people |
| Travel in trucks, helicopters, and airplanes to inspect lines for freedom from obstruction and adequacy of insulation.Patrolling the lines by truck, helicopter or plane.Done daily by most who do it. Robots: in any setting, AEP Ohio drone inspection program (Skydio aircraft + Levatas AI analysis) (American Electric Power / Skydio / Levatas) (deployed). Anthropic's rating. | 7% | 2.5 h50 min to 6.7 h | Hands-on 100% | Stays with people |
| Attach cross-arms, insulators, and auxiliary equipment to poles prior to installing them.Hardware attached to poles.Done daily by most who do it. Robots: in a purpose-built cell, House of Design automated roof/floor truss systems (sold). Anthropic's rating. | 6% | 1.7 h38 min to 3.3 h | Hands-on 100% | Stays with people |
| Drive vehicles equipped with tools and materials to job sites.Driving the line truck.Done hourly or more by most who do it. Robots: in any setting, Waymo Driver (6th-gen) robotaxi (deployed). Anthropic's rating. | 5% | 38 min17 min to 1.3 h | Hands-on 100% | Stays with people |
| Inspect and test power lines and auxiliary equipment to locate and identify problems, using reading and testing instruments.Instruments on the lines and equipment.Done daily by most who do it. Robots: in a structured facility, AEP Ohio drone inspection program (Skydio drones) (American Electric Power (AEP Ohio) with Skydio) (deployed). Anthropic's rating. | 5% | 1.3 h25 min to 2.5 h | Hands-on 100% | Stays with people |
| Install watt-hour meters and connect service drops between power lines and consumers' facilities.Meters and drops connected at the customer's building.Done more than monthly by most who do it. Robots: in a purpose-built cell, Automated electricity-meter verification line, State Grid Hubei Marketing Service Center (Metering Center) (deployed). Anthropic's rating. | 4% | 1.7 h38 min to 3.3 h | Hands-on 100% | Stays with people |
| Trim trees that could be hazardous to the functioning of cables or wires.Trees cut back from the lines.Done more than monthly by most who do it. Robots: no robot shown. Anthropic's rating. | 3% | 2.5 h50 min to 5 h | Hands-on 100% | Stays with people |
| Adhere to safety practices and procedures, such as checking equipment regularly and erecting barriers around work areas.Checking equipment and setting barriers by the rules.Done hourly or more by most who do it. Robots: in a purpose-built cell, Kratos Autonomous Truck-Mounted Attenuator (ATMA) (deployed). Anthropic's rating. | 3% | 25 min13 min to 50 min | Hands-on 100% | Stays with people |
| Splice or solder cables together or to overhead transmission lines, customer service lines, or street light lines, using hand tools, epoxies, or specialized equipment.Cables spliced or soldered to the lines.Done daily by most who do it. Robots: in a purpose-built cell, Outdoor live-working robot (室外带电作业机器人), new generation (Yijiahe Technology) (sold). Anthropic's rating. | 3% | 1.7 h38 min to 3.3 h | 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.
- Telecommunications Line Installers and Repairers3% now, 3% by 2028
- Helpers--Electricians1% now, 1% by 2028
- Electricians12% now, 12% by 2028
- Electrical and Electronics Repairers, Powerhouse, Substation, and Relay19% now, 19% by 2028
- Hoist and Winch Operators0% now, 0% 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).
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 Power-Line Installers and Repairers is within reach of AI now?
- An estimated 1% of the working time is within reach of AI models now and 1% 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 Power-Line Installers and Repairers 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: Find defective devices (20% of the task's time now); and Test and identify conductors (20% of the task's time now).
- Which tasks of Electrical Power-Line Installers and Repairers stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Install and repair distribution systems; Dig holes and set poles; and Replace damaged poles. Together such tasks are about 96% of the working time, and the people and body parts of the other tasks stay with people too.
- What should Electrical Power-Line Installers and Repairers 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; and the hands-on craft. By the end of 2028 on the long-run pace at four in five, about 99% of the working time stays with people, 0% 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 Electrical Power-Line Installers and Repairers?
- 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 0%. 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 Power-Line Installers and Repairers?
- Anthropic's robot exposure rating (September 2026) finds 93% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 61% of the working time, 11% in any setting. Its index is 0.92 of 3. One example: AEP Ohio drone inspection program (Skydio aircraft + Levatas AI analysis) for "inspect lines from vehicles and aircraft". 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 23 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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