Automotive Engineering Technicians
In short: today's best AI models could do about 19% 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 people and hands-on work, about 81% of the time, stays with people.
Assist engineers in determining the practicality of proposed product design changes and plan and carry out tests on experimental test devices or equipment for performance, durability, or efficiency.
$74,510 a year (for the broader BLS group this job sits in).
A typical 40-hour week
Not yet reviewed task by task- AI could take on8 h
- A person checks AI's work0 h
- Desk work AI can't do yet0 h
- Stays with people32 h
Automotive Engineering Technicians, now: of a 40-hour week, AI could take on 8 hours, 0 hours become checking its work, 0 hours are desk work it can't do yet, and 32 hours stay with people.
The largest pieces: Analyze test data for automotive systems, subsystems, or component parts (about 3 h); Analyze performance of vehicles or components that have been redesigned to increase fuel efficiency, such as camless or dual-clutch engines or alternative types of air-conditioning systems (about 2 h); Recommend product or component design improvements, based on test data or observations (under an hour).
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.
- 19%
- 0%
- 81%
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.
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, 10%. Today's estimate: 19%.
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, 0.032% went to this job's tasks in May 2026, the 257th largest of the 447 jobs that showed up at all; 2 of its 18 tasks showed up. Within each of Anthropic's methods, never across a change: 0.069% to 0.028% (released February and March 2025); 0.013% to 0.0045% (August 2025 to February 2026); 0.023% to 0.032% (April to May 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.069% | 229 of 708 | 5 of 18 |
| Released March 2025 | 0.028% | 370 of 703 | 5 of 18 |
| The week of Aug 4, 2025 (released September 2025) | 0.013% | 419 of 655 | 5 of 18 |
| The week of Nov 13, 2025 (released January 2026) | 0.0064% | 540 of 672 | 2 of 18 |
| The week of Feb 5, 2026 (released March 2026) | 0.0045% | 580 of 677 | 1 of 18 |
| April 2026 (released June 2026) | 0.023% | 288 of 434 | 1 of 18 |
| May 2026 (released June 2026) | 0.032% | 257 of 447 | 2 of 18 |
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 58% of this job's working time as physical work. For 32% of the working time, a robot has been shown doing most of the task somewhere: 32% in a purpose-built cell. 0.32 of 3, the 378th highest of the 923 jobs.
- Not physical 42%
- No robot shown 26%
- In a purpose-built cell 32%
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.
The tasks
Sorted by . 18 tasks from .
| Task | Kind | |||
|---|---|---|---|---|
| Test performance of vehicles that use alternative fuels, such as alcohol blends, natural gas, liquefied petroleum gas, biodiesel, nano diesel, or alternative power methods, such as solar energy or hydrogen fuel cells.Done more than monthly by most who do it. Robots: in a purpose-built cell, HORIBA ADS-7000 Automatic Driving System (with MEXA emissions bench and VETS) (sold). Anthropic's rating. | 15% | 6.7 h1.7 h to 2.5 work days | Stays with people | |
| Monitor computer-controlled test equipment, according to written or verbal instructions.Done several times a day by most who do it. | 10% | 1.7 h25 min to 6.7 h | Stays with people | |
| Improve fuel efficiency by testing vehicles or components that use lighter materials, such as aluminum, magnesium alloy, or plastic.Done more than monthly by most who do it. Robots: in a purpose-built cell, HORIBA ADS-7000 Automatic Driving System (sold). Anthropic's rating. | 9% | 6.7 h1.7 h to 2.5 work days | Stays with people | |
| Perform or execute manual or automated tests of automotive system or component performance, efficiency, or durability.Done more than weekly by most who do it. Robots: in a purpose-built cell, HORIBA ADS EVO Automatic Driving System (sold). Anthropic's rating. | 9% | 3.3 h50 min to 2.1 work days | Stays with people | |
| Install equipment, such as instrumentation, test equipment, engines, or aftermarket products, to ensure proper interfaces.Done daily by most who do it. Robots: no robot shown. Anthropic's rating. | 8% | 3.3 h50 min to 1.7 work days | Stays with people | |
| Participate in research or testing of computerized automotive applications, such as telemetrics, intelligent transportation systems, artificial intelligence, or automatic control.Done more than monthly by most who do it. Robots: in a purpose-built cell, Allion ART (AI Robotic Test Platform) Test Bench (deployed). Anthropic's rating. | 8% | 6.7 h1.7 h to 3.3 work days | Stays with people | |
| Analyze test data for automotive systems, subsystems, or component parts.Done daily by most who do it. | 8% | 2.1 h50 min to 5 h | 99%Half by now | |
| Build instrumentation or laboratory test equipment for special purposes.Done more than yearly by most who do it. Robots: no robot shown. Anthropic's rating. | 6% | 6.7 h3.3 h to 3.3 work days | Stays with people | |
| Analyze performance of vehicles or components that have been redesigned to increase fuel efficiency, such as camless or dual-clutch engines or alternative types of air-conditioning systems.Done more than monthly by most who do it. | 5% | 3.3 h1.7 h to 1.7 work days | 91%Half by now | |
| Inspect or test parts to determine nature or cause of defects or malfunctions.Done more than weekly by most who do it. Robots: in a purpose-built cell, KUKA fully automated end-of-line test bench for BMW eDrive (Dingolfing) (deployed). Anthropic's rating. | 4% | 1.3 h25 min to 5 h | Stays with people | |
| Document test results, using cameras, spreadsheets, documents, or other tools.Done daily by most who do it. AI observed on this task. | 4% | 50 min17 min to 2.5 h | Stays with people | |
| Set up mechanical, hydraulic, or electric test equipment in accordance with engineering specifications, standards, or test procedures.Done more than monthly by most who do it. Robots: no robot shown. Anthropic's rating. | 4% | 1.7 h38 min to 6.7 h | 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.
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
- Aerospace Engineering and Operations Technologists and Technicians10% now, 21% by 2028
- Mechanical Engineering Technologists and Technicians35% now, 53% by 2028
- Electrical and Electronic Engineering Technologists and Technicians39% now, 48% by 2028
- Robotics Technicians22% now, 26% by 2028
- Automotive Service Technicians and Mechanics3% now, 3% 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.
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 Automotive Engineering Technicians is within reach of AI now?
- An estimated 19% of the working time is within reach of AI models now and 19% 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 Automotive Engineering 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: Analyze test data for automotive systems, subsystems, or component parts (99% of the task's time now); Analyze performance of vehicles or components that have been redesigned to increase fuel efficiency, such as camless or dual-clutch engines or alternative types of air-conditioning systems (91% of the task's time now, 100% by the end of 2028); and Recommend product or component design improvements, based on test data or observations (100% of the task's time now).
- Which tasks of Automotive Engineering Technicians stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Test performance of vehicles that use alternative fuels, such as alcohol blends, natural gas, liquefied petroleum gas, biodiesel, nano diesel, or alternative power methods, such as solar energy or hydrogen fuel cells; Monitor computer-controlled test equipment, according to written or verbal instructions; and Improve fuel efficiency by testing vehicles or components that use lighter materials, such as aluminum, magnesium alloy, or plastic. Together such tasks are about 81% of the working time.
- Do people already use AI for the work of Automotive Engineering Technicians?
- In the Claude.ai conversations Anthropic sampled for May 2026 and tied to a work task, 0.032% went to this job's tasks, the 257th largest share of the 447 jobs that showed up; 2 of its 18 tasks appeared. Anthropic's labor market measure puts the share of the job's tasks seen in real Claude use at work at 7%. 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 Automotive Engineering Technicians?
- Anthropic's robot exposure rating (September 2026) finds 58% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 32% of the working time. Its index is 0.32 of 3. One example: HORIBA ADS-7000 Automatic Driving System (with MEXA emissions bench and VETS) for "test performance of vehicles that use alternative fuels, such as alcohol blends, natural gas, liquefied petroleum gas, biodiesel, nano diesel, or alternative power methods, such as solar energy or hydrogen fuel cells". 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 18 tasks O*NET lists for the occupation, each with an estimated length checked against GDPval and a share of the working time, each classed as desk, people or body work, 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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