Often handed to AI
Task areas most often handled directively in observed AI conversations — candidates to delegate with light review.
- Read and interpret blueprints, schematics, work specifications, drawings, or charts. · 0.4%
Automotive Engineering Technicians
Occupation · SOC 17-3027.01
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.
Also called: Laboratory Technician (Lab Technician) · Research Technician · Automotive Design Checker (Auto Design Checker) · Automotive Engineering Technician · Automotive Technician (Auto Technician) · Automotive Test Technician (Auto Test Technician) · Durability Technician · Performance Technician · Transportation Engineering Technician
Job family: Architecture and Engineering Occupations
Take this to your AI
A source-stamped Markdown brief of this occupation — paste it into an agent, or fetch
/roles/role-17-3027-01/context.md directly.
AI work map
A fast read on where AI already shows up in this occupation, where it stays a copilot, where humans remain in the loop, and what the labor market is doing. Built from observed Claude.ai conversations mapped to O*NET tasks and from published research — measures of usage and exposure, not advice or predictions that the job is going away.
Keep a human in the loop
Task areas where a human was still judged necessary in a large share of observed conversations — not a safety ruling, an observed-need signal.
- Read and interpret blueprints, schematics, work specifications, drawings, or charts. · 100.0% need a human
Skills it runs on
The capabilities O*NET rates most important for this occupation — the human ground the work is built on.
See all skills →Market signal
Independent published positions, read together — not a forecast.
- About average employment outlook (0.0% by 2034)
- 3,200 openings/yr
- High AI exposure
- Median pay $68,730/yr
- Work is mostly on-site (not teleworkable)
- A reversal from 2013 — rated low automation risk then (43rd), high AI task-overlap now (54th)
54th-percentile task overlap — yet about 3,200 openings a year (+0% projected, BLS) . What exposure means →
AI & job outlook
What today's research says about this occupation's exposure to AI, how AI is actually being used in it, and where employment is headed. These are positions within published studies — measures of exposure and usage, not predictions that this job will disappear.
Exposure to current AI
Each study uses its own scale, so the raw scores are not comparable across rows — the percentile (this job's rank among all U.S. occupations with data) is the comparable figure, and sizes the bars.
| Measure | Rank vs all occupations | Percentile | Score |
|---|---|---|---|
| Overall AI exposure (Felten et al.) Moderate | 46th | -0.1 | |
| LLM task exposure, γ (OpenAI / Eloundou) Moderate | 44th | 0.5 | |
| AI assistant applicability (Microsoft) High | 75th | 0.2 |
OpenAI's exposure study scores tasks three ways: with a language model alone (α 0.1), with simple added tooling (β 0.3), and including AI-powered software (γ 0.5). Higher means more of the job's tasks could be done at least twice as fast — not that they will be automated away.
This job mostly cannot be done remotely (Dingel–Neiman) — its hands-on tasks sit outside what software-based AI reaches.
Historical automation estimate (2013)
A pre-LLM (2013) estimate of how automatable this job is by computerization and robotics. Shown for historical context only — it is not part of any current AI ranking.
Frey–Osborne probability 0.4 · 43rd percentile among occupations · Moderate
How AI is actually used in this job
Among measured AI assistant conversations mapped to this occupation (Anthropic Economic Index, 2026-01-15), these task types came up most. These are shares of observed AI conversations — not shares of the job, of worker time, or of what could be automated.
| Document test results, using cameras, spreadsheets, documents, or other tools. | 1.4% | |
| Analyze test data for automotive systems, subsystems, or component parts. | 0.6% | |
| Read and interpret blueprints, schematics, work specifications, drawings, or charts. | 0.3% | |
| Set up mechanical, hydraulic, or electric test equipment in accordance with engineering specifications, standards, or test procedures. | 0.2% | |
| Participate in research or testing of computerized automotive applications, such as telemetrics, intelligent transportation systems, artificial intelligence, or automatic control. | 0.2% |
Job outlook
Independent U.S. Bureau of Labor Statistics employment projection for 2024–2034 — a labor-market forecast, not an AI-impact forecast.
| Outlook | About average · 0.0% by 2034 |
| Projected annual openings | 3,200 |
| Employment 2024 → 2034 | 38,300 → 38,300 |
“Annual openings” counts new jobs plus replacements for workers who leave the occupation, so it can be large even when growth is modest.
Where this work sits on the global GenAI gradient
The ILO's 2025 global study scores generative-AI exposure on the international ISCO-08 occupation system, not US SOC. Bridged through the published (and approximate, many-to-many) IBS O*NET-SOC ↔ ISCO-08 crosswalk, this US occupation corresponds to the international occupation below. Exposure here means how much of the work's tasks today's AI can attempt — task overlap, not automation, adoption, or jobs lost.
Automotive Engineering Technicians sits at the 48th percentile of 427
occupations on the global GenAI task-exposure gradient
— exposure eased from 2023 to 2025. Each dot is one occupation; the
ringed one is this work. Exposure is task overlap, not automation or jobs lost.
26% mean task exposure (2025)
48th percentile of 427 placed occupations
−7 pts shift 2023 → 2025
| International occupation (ISCO-08) | Task exposure (2025) | Most tasks fall in |
|---|---|---|
| Mechanical Engineering Technicians · 3115 | 26% | Not exposed |
Read the whole six-band gradient on the GenAI exposure gradient page. The crosswalk is approximate: a US occupation can map to several international ones, and the ILO scores describe the international occupation, not this exact US role.
Working with AI in this job
How people actually apply AI to this occupation's tasks, from Claude.ai (Free and Pro) conversations in the Anthropic Economic Index, 2026-01-15. This is one AI assistant's consumer sample — not all AI, not the whole workforce. Autonomy and the collaboration mix are model-rated estimates; figures below the sample floor are hidden.
| Most common way people use AI here | Directive · AI does it; you give the instruction |
| Typical AI autonomy | 3.0 / 5 · higher = AI acts more independently |
| Used for work (vs. personal / coursework) | 53.9% |
What people delegate to AI
The role's most common tasks in AI conversations, each tagged with how people work with the AI on it. “Usage” is the share of observed conversations, not of the job.
| Task | How | Usage |
|---|---|---|
| Read and interpret blueprints, schematics, work specifications, drawings, or charts. | Directive | 0.4% |
Where a human is still needed
Tasks where the model most often judged that a person remained necessary — a useful read on the current boundary, not a guarantee.
| Read and interpret blueprints, schematics, work specifications, drawings, or charts. | 100.0% |
What people most often hand AI here
Example prompts phrased from the tasks people most often delegate to AI in this occupation (Anthropic Economic Index). Each shows the underlying measured task and its share of observed AI use. They are suggested phrasings of real tasks — starting points, not endorsed instructions.
-
Help me read and interpret blueprints, schematics, work specifications, drawings, or charts.From: Read and interpret blueprints, schematics, work specifications, drawings, or charts. · 0.4% of measured AI use · directive
Tasks
All 18 tasks O*NET lists for this occupation, ordered by importance. Each links to its own page with AI-exposure and observed-use detail.
- Document test results, using cameras, spreadsheets, documents, or other tools. Core · importance 4.3
- Set up mechanical, hydraulic, or electric test equipment in accordance with engineering specifications, standards, or test procedures. Core · importance 4.2
- Read and interpret blueprints, schematics, work specifications, drawings, or charts. Core · importance 4.2
- Inspect or test parts to determine nature or cause of defects or malfunctions. Core · importance 4.2
- Analyze test data for automotive systems, subsystems, or component parts. Core · importance 4.1
- Monitor computer-controlled test equipment, according to written or verbal instructions. Core · importance 4.1
- Install equipment, such as instrumentation, test equipment, engines, or aftermarket products, to ensure proper interfaces. Core · importance 4.0
- Perform or execute manual or automated tests of automotive system or component performance, efficiency, or durability. Core · importance 4.0
- Maintain test equipment in operational condition by performing routine maintenance or making minor repairs or adjustments as needed. Core · importance 3.9
- 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. Core · importance 3.8
- Improve fuel efficiency by testing vehicles or components that use lighter materials, such as aluminum, magnesium alloy, or plastic. Core · importance 3.6
- Fabricate new or modify existing prototype components or fixtures. Core · importance 3.5
- Order new test equipment, supplies, or replacement parts. Core · importance 3.5
- Recommend product or component design improvements, based on test data or observations. Core · importance 3.5
- Recommend tests or testing conditions in accordance with designs, customer requirements, or industry standards to ensure test validity. Core · importance 3.4
- 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. Core · importance 3.4
- Participate in research or testing of computerized automotive applications, such as telemetrics, intelligent transportation systems, artificial intelligence, or automatic control. Core · importance 3.4
- Build instrumentation or laboratory test equipment for special purposes. Core · importance 3.4
Work activities
- Design electronic or computer equipment or instrumentation.
- Purchase materials, equipment, or other resources.
- Operate industrial equipment.
- Recommend technical design or process changes to improve efficiency, quality, or performance.
- Monitor the productivity or efficiency of industrial operations.
- Review technical documents to plan work.
- Maintain test equipment.
- Install instrumentation or electronic equipment or systems.
- Inspect finished products to locate flaws.
- Test performance of electrical, electronic, mechanical, or integrated systems or equipment.
- Document design or operational test results.
- Create physical models or prototypes.
- Analyze test or validation data.
- Analyze operational data to evaluate operations, processes or products.
- Test products for functionality or quality.
- Research advanced engineering designs or applications.
- Test green technologies or processes.
Knowledge, skills & abilities
O*NET importance rating, from 1 (not important) to 5 (extremely important).
Knowledge
| Engineering and Technology | 4.5 | |
| Mechanical | 4.2 | |
| Computers and Electronics | 4.1 | |
| Mathematics | 3.9 | |
| English Language | 3.8 | |
| Physics | 3.7 | |
| Transportation | 3.1 | |
| Design | 3.1 |
Abilities
| Written Comprehension | 3.9 | |
| Deductive Reasoning | 3.9 | |
| Problem Sensitivity | 3.8 | |
| Inductive Reasoning | 3.8 | |
| Near Vision | 3.8 | |
| Oral Comprehension | 3.6 | |
| Oral Expression | 3.5 | |
| Information Ordering | 3.5 | |
| Written Expression | 3.4 | |
| Category Flexibility | 3.4 | |
| Finger Dexterity | 3.4 | |
| Speech Recognition | 3.4 | |
| Speech Clarity | 3.4 | |
| Selective Attention | 3.3 | |
| Arm-Hand Steadiness | 3.3 | |
| Flexibility of Closure | 3.1 | |
| Perceptual Speed | 3.1 | |
| Visualization | 3.1 | |
| Manual Dexterity | 3.1 | |
| Far Vision | 3.1 |
Essential skills
| Reading Comprehension | 3.6 | |
| Speaking | 3.5 | |
| Critical Thinking | 3.5 | |
| Active Listening | 3.3 | |
| Writing | 3.3 | |
| Mathematics | 3.1 | |
| Monitoring | 3.1 |
Transferable skills
| Complex Problem Solving | 3.3 | |
| Operations Monitoring | 3.3 | |
| Quality Control Analysis | 3.3 | |
| Repairing | 3.1 | |
| Judgment and Decision Making | 3.1 |
Skills in demand
Skills employers ask for in job postings for this occupation (Lightcast), with whether each is a common or specialized skill.
Tools & technology
Work context
How characteristic each condition is of the job, on O*NET's 1–5 context scale (higher = more present in day-to-day work). Each condition links to how it varies across all occupations.
How to get in
- Job zone
- Zone 3 — Job Zone Three: Medium Preparation Needed
- Education
- Most occupations in this zone require training in vocational schools, related on-the-job experience, or an associate's degree.
- Typical entry-level education
- Associate's degree · BLS, the typical path — not a requirement
- Related experience
- Previous work-related skill, knowledge, or experience is required for these occupations. For example, an electrician must have completed three or four years of apprenticeship or several years of vocational training, and often must have passed a licensing exam, in order to perform the job.
- Preparation level
- SVP (6.0 to < 7.0) — total schooling plus on-the-job experience.
What to study: Engineering/Engineering-Related Technologies/Technicians . Fields of study crosswalked to this occupation (NCES CIP–SOC), not a requirement.
Education of current workers
Share of people in this occupation at each level of education.
| Associate's Degree (or other 2-year degree) | 37.0% | |
| Bachelor's Degree | 29.6% | |
| Post-Secondary Certificate | 14.8% | |
| Master's Degree | 11.1% | |
| High School Diploma | 3.7% | |
| Some College Courses | 3.7% |
Interests & work styles
The interests and personal qualities O*NET associates with people who do this work.
Career interests (Holland / RIASEC)
| Realistic | 7.0 | |
| Investigative | 5.4 | |
| Conventional | 4.5 |
Interest areas
| Engineering | 6.5 | |
| Mechanics/Electronics | 6.2 | |
| Physical Science | 3.3 | |
| Mathematics/Statistics | 3.0 | |
| Information Technology | 2.8 | |
| Transportation/Machine Operation | 2.6 | |
| Physical/Manual Labor | 2.5 |
Work styles
| Attention to Detail | 2.6 | |
| Dependability | 2.5 | |
| Cautiousness | 1.9 | |
| Intellectual Curiosity | 1.9 | |
| Innovation | 1.8 | |
| Integrity | 1.7 |
Wages & employment
U.S. · annual wages (BLS OEWS)
| 10th percentile | $46,940 |
| 25th percentile | $57,330 |
| Median (50th) | $68,730 |
| 75th percentile | $82,980 |
| 90th percentile | $100,890 |
| People employed | 37,450 |
Wages and employment are reported by BLS for the broader occupation group this specialty belongs to (SOC 17-3027), not for the specialty alone.
Industries that employ this occupation
Where these workers are employed, by number of jobs (national, BLS OEWS). Pay shown is the occupation's national median, not industry-specific.
| Industry | Workers | National median pay |
|---|---|---|
| Manufacturing · Sector | 19,270 | $69,640 |
| Professional, Scientific, and Technical Services · Sector | 10,280 | $72,560 |
| Engineering Services · National industry | 4,410 | $74,340 |
| Wholesale Trade · Sector | 2,350 | $59,350 |
| Administrative and Support and Waste Management and Remediation Services · Sector | 1,790 | $61,960 |
| Temporary Help Services · National industry | 1,290 | $58,240 |
| Testing Laboratories and Services · National industry | 1,020 | $64,670 |
| Management of Companies and Enterprises · Sector | 930 | $76,360 |
| Mining, Quarrying, and Oil and Gas Extraction · Sector | 590 | $78,390 |
| Educational Services · Sector | 430 | $54,750 |
| Utilities · Sector | 250 | $94,270 |
| Machine Shops · National industry | 210 | $58,250 |
Where this work is most concentrated
Industries where this occupation is far more common than in the economy as a whole. The location quotient is how many times more concentrated it is here (a value of 5 means five times its economy-wide share).
| Industry | Concentration | Workers |
|---|---|---|
| Testing Laboratories and Services · National industry | 24.64× | 1,020 |
| Engineering Services · National industry | 15.7× | 4,410 |
| Manufacturing · Sector | 6.22× | 19,270 |
| Mining, Quarrying, and Oil and Gas Extraction · Sector | 4.24× | 590 |
| Professional, Scientific, and Technical Services · Sector | 3.93× | 10,280 |
| Machine Shops · National industry | 3.33× | 210 |
| Temporary Help Services · National industry | 2× | 1,290 |
| Utilities · Sector | 1.78× | 250 |
Related occupations
Part of the Advanced Manufacturing and Supply Chain & Transportation career clusters.
- Calibration Technologists and Technicians · 17-3028.00 Compare →
- Aerospace Engineering and Operations Technologists and Technicians · 17-3021.00 Compare →
- Mechanical Engineering Technologists and Technicians · 17-3027.00 Compare →
- Electrical and Electronic Engineering Technologists and Technicians · 17-3023.00 Compare →
- Robotics Technicians · 17-3024.01 Compare →
- Automotive Service Technicians and Mechanics · 49-3023.00 Compare →
- Electrical and Electronics Installers and Repairers, Transportation Equipment · 49-2093.00 Compare →
- Industrial Engineering Technologists and Technicians · 17-3026.00 Compare →
- Avionics Technicians · 49-2091.00 Compare →
- Electro-Mechanical and Mechatronics Technologists and Technicians · 17-3024.00 Compare →
- Automotive Engineers · 17-2141.02 Compare →
- Mechanical Engineers · 17-2141.00 Compare →
Side-by-side comparisons place two occupations’ pay, preparation, skills, and AI exposure on the same page — same data, same scale, no forecast.
What you can do with this
Options the data surfaces for Automotive Engineering Technicians — not advice or a forecast. Each is a real cross-link you can follow into the evidence.
Skills that travel
Capabilities this work builds that are used across many other occupations.
Adjacent roles
Occupations O*NET rates as related — the nearby moves on the map.
- Calibration Technologists and Technicians Compare →
- Aerospace Engineering and Operations Technologists and Technicians Compare →
- Mechanical Engineering Technologists and Technicians Compare →
- Electrical and Electronic Engineering Technologists and Technicians Compare →
- Robotics Technicians Compare →
Paths in
How people typically prepare for this work.
- Associate's degree · typical entry level
- Job zone 3 — Job Zone Three: Medium Preparation Needed · preparation tier
- Engineering/Engineering-Related Technologies/Technicians · field of study
Zoom out
On the global GenAI exposure gradient this work sits around the 48th percentile of 427 international occupations.
Write a report on thisheadline · factoids · citation
Automotive Engineering Technicians show 54th-percentile AI task overlap — and about 3,200 annual U.S. openings
- Automotive Engineering Technicians rank in the 54th percentile (Moderate band) for AI task overlap across U.S. occupations — a measure of how much of the work today's AI can attempt, not how much is automated.Eloundou et al. (GPTs are GPTs) + Felten AIOE
- The occupation is projected to see about 3,200 U.S. job openings per year (2024–34), counting growth and replacement — a labor-demand projection made independently of AI.BLS Employment Projections 2024–34
- BLS projects employment to be about average (0%) from 2024 to 2034.BLS Employment Projections 2024–34
- Median annual pay is $68,730, across about 37,450 U.S. workers.BLS OEWS (May 2024)
Copy the whole kit
Automotive Engineering Technicians show 54th-percentile AI task overlap — and about 3,200 annual U.S. openings • Automotive Engineering Technicians rank in the 54th percentile (Moderate band) for AI task overlap across U.S. occupations — a measure of how much of the work today's AI can attempt, not how much is automated. (Eloundou et al. (GPTs are GPTs) + Felten AIOE) • The occupation is projected to see about 3,200 U.S. job openings per year (2024–34), counting growth and replacement — a labor-demand projection made independently of AI. (BLS Employment Projections 2024–34) • BLS projects employment to be about average (0%) from 2024 to 2034. (BLS Employment Projections 2024–34) • Median annual pay is $68,730, across about 37,450 U.S. workers. (BLS OEWS (May 2024)) Source: Singulariki — "Automotive Engineering Technicians". https://singulariki.com/roles/role-17-3027-01 Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.
AssetsShare imageMethodology & sourcesPress & newsroomThe newsroom
Every line is built only from figures this page already shows and cites. AI task overlap means what today's AI can attempt — not automation, job loss, or a forecast.
Sources for this page
Every figure above traces to a named public dataset and the exact release below — not hand-written opinion. See the full methodology for what each measure does and does not mean.
- O*NET 30.3 U.S. Department of Labor / National Center for O*NET Development
- BLS Occupational Employment and Wage Statistics (OEWS) May 2024 U.S. Bureau of Labor Statistics
- BLS Employment Projections 2024–2034 U.S. Bureau of Labor Statistics
- Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27) Anthropic
- Microsoft “Working with AI” working-with-ai Microsoft Research
- “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130 OpenAI / academic
- AI Occupational Exposure (AIOE) Felten, Raj & Seamans academic
- ILO / Gmyrek et al. GenAI exposure gradient 2025 International Labour Organization
- IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022 Institute for Structural Research (IBS)
- Frey & Osborne (2013) frey-osborne-automation academic
- Dingel & Neiman (2020) dingel-neiman-workathome academic
Data compiled June 2, 2026. Figures are estimates, not advice.
Cite this page
Plain
Singulariki. "Automotive Engineering Technicians." Singulariki: a source-backed encyclopedia of work. Built from O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); Microsoft “Working with AI” working-with-ai; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans; ILO / Gmyrek et al. GenAI exposure gradient 2025; IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022; Frey & Osborne (2013) frey-osborne-automation; Dingel & Neiman (2020) dingel-neiman-workathome. Accessed June 7, 2026. https://singulariki.com/roles/role-17-3027-01
APA
Singulariki. (2026). Automotive Engineering Technicians. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-17-3027-01
BibTeX
@misc{singulariki-role-17-3027-01,
title = {Automotive Engineering Technicians},
author = {{Singulariki}},
year = {2026},
note = {O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); Microsoft “Working with AI” working-with-ai; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans; ILO / Gmyrek et al. GenAI exposure gradient 2025; IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022; Frey & Osborne (2013) frey-osborne-automation; Dingel & Neiman (2020) dingel-neiman-workathome. Accessed June 7, 2026},
url = {https://singulariki.com/roles/role-17-3027-01}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.