Often handed to AI
Task areas most often handled directively in observed AI conversations — candidates to delegate with light review.
- Develop, test, or program new robots. · 0.5%
Occupation · SOC 17-3024.00
Operate, test, maintain, or adjust unmanned, automated, servomechanical, or electromechanical equipment. May operate unmanned submarines, aircraft, or other equipment to observe or record visual information at sites such as oil rigs, crop fields, buildings, or for similar infrastructure, deep ocean exploration, or hazardous waste removal. May assist engineers in testing and designing robotics equipment.
Also called: Electro-Mechanic · Electromechanical Technician (EM Technician) · Electronics Technician (Electronics Tech) · Mechanical Technician (Mechanical Tech) · Automation Technician (Automation Tech) · Electromechanical Assembler (EM Assembler) · Process Control Tech · Product Test Specialist · Test Engineering Technician (Test Engineering Tech) · Test Technician (Test Tech) · Automation Test Specialist · Calibration Technician
Job family: Architecture and Engineering Occupations
A source-stamped Markdown brief of this occupation — paste it into an agent, or fetch
/roles/role-17-3024-00/context.md directly.
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.
Task areas most often handled directively in observed AI conversations — candidates to delegate with light review.
Task areas where people work with AI — iterating, learning, or checking — staying in the loop rather than handing the task off.
Task areas where a human was still judged necessary in a large share of observed conversations — not a safety ruling, an observed-need signal.
The capabilities O*NET rates most important for this occupation — the human ground the work is built on.
See all skills →Independent published positions, read together — not a forecast.
47th-percentile task overlap — yet about 1,300 openings a year (+1.1% projected, BLS), and observed AI use leans 2570% copilot, not hand-off (AEI) . What exposure means →
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.
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 | 40th | -0.3 | |
| LLM task exposure, γ (OpenAI / Eloundou) Moderate | 46th | 0.5 | |
| AI assistant applicability (Microsoft) Moderate | 58th | 0.2 |
OpenAI's exposure study scores tasks three ways: with a language model alone (α 0.2), with simple added tooling (β 0.4), 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.
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 0.8 · 65th percentile among occupations · Moderate
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.
| Select and use laboratory, operational, or diagnostic techniques or test equipment to assess electromechanical circuits, equipment, processes, systems, or subsystems. | 1.3% | |
| Develop, test, or program new robots. | 0.9% | |
| Test performance of electromechanical assemblies, using test instruments such as oscilloscopes, electronic voltmeters, or bridges. | 0.6% | |
| Translate electromechanical drawings into design specifications, applying principles of engineering, thermal or fluid sciences, mathematics, or statistics. | 0.3% | |
| Conduct statistical studies to analyze or compare production costs for sustainable and nonsustainable designs. | 0.2% | |
| Repair, rework, or calibrate hydraulic or pneumatic assemblies or systems to meet operational specifications or tolerances. | 0.2% |
Independent U.S. Bureau of Labor Statistics employment projection for 2024–2034 — a labor-market forecast, not an AI-impact forecast.
| Outlook | About average · +1.1% by 2034 |
| Projected annual openings | 1,300 |
| Employment 2024 → 2034 | 15,000 → 15,100 |
“Annual openings” counts new jobs plus replacements for workers who leave the occupation, so it can be large even when growth is modest.
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 2 occupations below. Exposure here means how much of the work's tasks today's AI can attempt — task overlap, not automation, adoption, or jobs lost.
| International occupation (ISCO-08) | Task exposure (2025) | Most tasks fall in |
|---|---|---|
| Electrical Engineering Technicians · 3113 | 27% | Not exposed |
| 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.
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.
| Augmentation vs. automation | 25.7% working with AI · 21.5% handed to AI |
| Most common way people use AI here | Directive · AI does it; you give the instruction |
| Typical AI autonomy | 4.0 / 5 · higher = AI acts more independently |
| Used for work (vs. personal / coursework) | 13.2% |
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 |
|---|---|---|
| Test performance of electromechanical assemblies, using test instruments such as oscilloscopes, electronic voltmeters, or bridges. | Learning | 0.6% |
| Develop, test, or program new robots. | Directive | 0.5% |
| Repair, rework, or calibrate hydraulic or pneumatic assemblies or systems to meet operational specifications or tolerances. | — | 0.4% |
Tasks where the model most often judged that a person remained necessary — a useful read on the current boundary, not a guarantee.
| Repair, rework, or calibrate hydraulic or pneumatic assemblies or systems to meet operational specifications or tolerances. | 94.4% | |
| Test performance of electromechanical assemblies, using test instruments such as oscilloscopes, electronic voltmeters, or bridges. | 86.9% | |
| Develop, test, or program new robots. | 61.7% |
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 test performance of electromechanical assemblies, using test instruments such as oscilloscopes, electronic voltmeters, or bridges. From: Test performance of electromechanical assemblies, using test instruments such as oscilloscopes, electronic voltmeters, or bridges. · 0.6% of measured AI use · learning
Help me develop, test, or program new robots. From: Develop, test, or program new robots. · 0.5% of measured AI use · directive
Help me repair, rework, or calibrate hydraulic or pneumatic assemblies or systems to meet operational specifications or tolerances. From: Repair, rework, or calibrate hydraulic or pneumatic assemblies or systems to meet operational specifications or tolerances. · 0.4% of measured AI use
All 29 tasks O*NET lists for this occupation, ordered by importance. Each links to its own page with AI-exposure and observed-use detail.
Newer responsibilities O*NET has flagged as growing for this occupation.
O*NET importance rating, from 1 (not important) to 5 (extremely important).
| Computers and Electronics | 4.1 | |
| Mechanical | 3.7 | |
| Engineering and Technology | 3.6 | |
| English Language | 3.2 | |
| Production and Processing | 3.1 | |
| Mathematics | 3.1 |
| Operations Monitoring | 4.0 | |
| Troubleshooting | 3.9 | |
| Repairing | 3.8 | |
| Quality Control Analysis | 3.6 | |
| Operation and Control | 3.5 | |
| Judgment and Decision Making | 3.4 | |
| Complex Problem Solving | 3.3 | |
| Equipment Selection | 3.1 | |
| Installation | 3.1 | |
| Equipment Maintenance | 3.1 | |
| Systems Analysis | 3.1 | |
| Systems Evaluation | 3.1 |
| Control Precision | 4.0 | |
| Near Vision | 3.9 | |
| Problem Sensitivity | 3.8 | |
| Deductive Reasoning | 3.8 | |
| Inductive Reasoning | 3.8 | |
| Information Ordering | 3.8 | |
| Arm-Hand Steadiness | 3.8 | |
| Finger Dexterity | 3.8 | |
| Perceptual Speed | 3.5 | |
| Manual Dexterity | 3.5 | |
| Far Vision | 3.5 | |
| Oral Comprehension | 3.4 | |
| Visual Color Discrimination | 3.4 | |
| Written Comprehension | 3.3 | |
| Written Expression | 3.3 |
| Monitoring | 3.8 | |
| Critical Thinking | 3.6 | |
| Reading Comprehension | 3.3 | |
| Active Listening | 3.1 | |
| Writing | 3.1 | |
| Speaking | 3.1 | |
| Active Learning | 3.1 |
Skills employers ask for in job postings for this occupation (Lightcast), with whether each is a common or specialized skill.
Showing the top 40 of 44.
Showing the top 40 of 41.
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.
What to study: Engineering/Engineering-Related Technologies/Technicians . Fields of study crosswalked to this occupation (NCES CIP–SOC), not a requirement.
Share of people in this occupation at each level of education.
| Post-Secondary Certificate | 31.7% | |
| Associate's Degree (or other 2-year degree) | 29.8% | |
| Bachelor's Degree | 11.0% | |
| High School Diploma | 9.9% | |
| Some College Courses | 7.3% | |
| Master's Degree | 5.6% | |
| Doctoral Degree | 3.7% | |
| Less than a High School Diploma | 1.0% |
The interests and personal qualities O*NET associates with people who do this work.
| Realistic | 7.0 | |
| Conventional | 4.6 | |
| Investigative | 4.4 |
| Mechanics/Electronics | 6.6 | |
| Engineering | 6.3 | |
| Information Technology | 3.3 | |
| Mathematics/Statistics | 2.8 | |
| Physical/Manual Labor | 2.6 | |
| Transportation/Machine Operation | 2.3 | |
| Physical Science | 2.0 |
| Dependability | 3.0 | |
| Attention to Detail | 2.7 | |
| Cautiousness | 2.0 | |
| Intellectual Curiosity | 1.9 | |
| Achievement Orientation | 1.7 | |
| Perseverance | 1.6 |
U.S. · annual wages (BLS OEWS)
| 10th percentile | $47,770 |
| 25th percentile | $58,570 |
| Median (50th) | $70,760 |
| 75th percentile | $87,320 |
| 90th percentile | $109,580 |
| People employed | 14,680 |
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 | 7,230 | $66,680 |
| Professional, Scientific, and Technical Services · Sector | 3,410 | $78,790 |
| Engineering Services · National industry | 1,390 | $73,340 |
| Wholesale Trade · Sector | 950 | $64,390 |
| Transportation and Warehousing · Sector | 900 | $67,640 |
| Administrative and Support and Waste Management and Remediation Services · Sector | 660 | $62,450 |
| Temporary Help Services · National industry | 450 | $65,230 |
| Mining, Quarrying, and Oil and Gas Extraction · Sector | 320 | $99,200 |
| Other Services (except Public Administration) · Sector | 290 | $54,090 |
| Educational Services · Sector | 210 | $74,060 |
| Construction · Sector | 140 | $78,890 |
| Testing Laboratories and Services · National industry | 140 | $67,600 |
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 |
|---|---|---|
| Engineering Services · National industry | 12.63× | 1,390 |
| Testing Laboratories and Services · National industry | 8.63× | 140 |
| Manufacturing · Sector | 5.95× | 7,230 |
| Mining, Quarrying, and Oil and Gas Extraction · Sector | 5.86× | 320 |
| Professional, Scientific, and Technical Services · Sector | 3.33× | 3,410 |
| Utilities · Sector | 1.81× | 100 |
| Temporary Help Services · National industry | 1.78× | 450 |
| Wholesale Trade · Sector | 1.65× | 950 |
Part of the Advanced Manufacturing career cluster.
Side-by-side comparisons place two occupations’ pay, preparation, skills, and AI exposure on the same page — same data, same scale, no forecast.
Options the data surfaces for Electro-Mechanical and Mechatronics Technologists and Technicians — not advice or a forecast. Each is a real cross-link you can follow into the evidence.
Capabilities this work builds that are used across many other occupations.
Occupations O*NET rates as related — the nearby moves on the map.
How people typically prepare for this work.
On the global GenAI exposure gradient this work sits around the 49th percentile of 427 international occupations.
Electro-Mechanical and Mechatronics Technologists and Technicians show 47th-percentile AI task overlap — and about 1,300 annual U.S. openings
Electro-Mechanical and Mechatronics Technologists and Technicians show 47th-percentile AI task overlap — and about 1,300 annual U.S. openings • Electro-Mechanical and Mechatronics Technologists and Technicians rank in the 47th 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 1,300 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 (+1.1%) from 2024 to 2034. (BLS Employment Projections 2024–34) • Median annual pay is $70,760, across about 14,680 U.S. workers. (BLS OEWS (May 2024)) • Of the AI use actually observed for this work, 26% looks like augmentation (drafting, iterating, checking) rather than hands-off automation — from a Claude.ai usage sample, not a census. (2026-01-15-v4-plus-2025-03-27-v2) Source: Singulariki — "Electro-Mechanical and Mechatronics Technologists and Technicians". https://singulariki.com/roles/role-17-3024-00 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.
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.
Data compiled June 2, 2026. Figures are estimates, not advice.
Singulariki. "Electro-Mechanical and Mechatronics Technologists and 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-17-3024-00
Singulariki. (2026). Electro-Mechanical and Mechatronics Technologists and Technicians. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-17-3024-00
@misc{singulariki-role-17-3024-00,
title = {Electro-Mechanical and Mechatronics Technologists and 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-17-3024-00}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.