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Electromechanical Equipment Assemblers

Occupation · SOC 51-2023.00

Assemble or modify electromechanical equipment or devices, such as servomechanisms, gyros, dynamometers, magnetic drums, tape drives, brakes, control linkage, actuators, and appliances.

Also called: Assembler · Electronic Assembler · Electronic Technician · Mechanical Assembler · Electrical Assembler · Electromechanical Assembler · Electromechanical Equipment Assembler · Electronics Assembler · Production Associate · Wiring Technician · Air-Conditioning Coil Assembler (AC Coil Assembler) · Appliance Assembler

Job family: Production Occupations

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Download .md

A source-stamped Markdown brief of this occupation — paste it into an agent, or fetch /roles/role-51-2023-00/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.

Often handed to AI

Task areas most often handled directively in observed AI conversations — candidates to delegate with light review.

  • Measure parts to determine tolerances, using precision measuring instruments such as micrometers, calipers, and verniers. · 0.7%
See how AI is used here →

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.

  • Measure parts to determine tolerances, using precision measuring instruments such as micrometers, calipers, and verniers. · 95.6% need a human
See the boundary tasks →

22nd-percentile task overlap — yet observed AI use leans 2353% copilot, not hand-off (AEI) . 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 35th -0.5
LLM task exposure, γ (OpenAI / Eloundou) Low 13th 0.1

OpenAI's exposure study scores tasks three ways: with a language model alone (α 0.0), with simple added tooling (β 0.0), and including AI-powered software (γ 0.1). 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.

Mixed signals. Today's AI/LLM studies show relatively low exposure for this job, but the older (2013) Frey–Osborne work rated it higher for computerization and robotics. Different eras, different technologies — the AI measures above reflect the current state.

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 1.0 · 94th percentile among occupations · High

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.

Measure parts to determine tolerances, using precision measuring instruments such as micrometers, calipers, and verniers. 0.2%

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.

28% mean task exposure (2025)
52nd percentile of 427 placed occupations
−8 pts shift 2023 → 2025
International occupation (ISCO-08) Task exposure (2025) Most tasks fall in
Electrical and Electronic Equipment Assemblers · 8212 28% Minimal

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.

Augmentation vs. automation 23.5% working with AI · 45.6% handed to AI
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) 29.4%

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
Measure parts to determine tolerances, using precision measuring instruments such as micrometers, calipers, and verniers. Directive 0.7%

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.

Measure parts to determine tolerances, using precision measuring instruments such as micrometers, calipers, and verniers. 95.6%

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 measure parts to determine tolerances, using precision measuring instruments such as micrometers, calipers, and verniers.

    From: Measure parts to determine tolerances, using precision measuring instruments such as micrometers, calipers, and verniers. · 0.7% of measured AI use · directive

Tasks

All 14 tasks O*NET lists for this occupation, ordered by importance. Each links to its own page with AI-exposure and observed-use detail.

Work activities

Knowledge, skills & abilities

O*NET importance rating, from 1 (not important) to 5 (extremely important).

Abilities

Arm-Hand Steadiness 3.6
Finger Dexterity 3.6
Near Vision 3.6
Manual Dexterity 3.5
Problem Sensitivity 3.3
Information Ordering 3.3
Control Precision 3.3
Deductive Reasoning 3.1
Visualization 3.1
Oral Comprehension 3.0
Written Comprehension 3.0
Oral Expression 3.0
Inductive Reasoning 3.0
Category Flexibility 3.0
Flexibility of Closure 3.0
Far Vision 3.0
Visual Color Discrimination 3.0
Speech Recognition 3.0
Speech Clarity 3.0
Written Expression 2.9
Perceptual Speed 2.9
Selective Attention 2.9
Multilimb Coordination 2.8

Knowledge

Production and Processing 3.3
Mechanical 3.2
Computers and Electronics 3.1
English Language 3.0
Engineering and Technology 2.9

Transferable skills

Operations Monitoring 3.3
Quality Control Analysis 3.3
Troubleshooting 3.0
Judgment and Decision Making 2.9
Time Management 2.9
Equipment Maintenance 2.8
Repairing 2.8

Essential skills

Reading Comprehension 3.0
Speaking 3.0
Critical Thinking 3.0
Active Listening 2.9
Monitoring 2.9

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

Example Category
Autodesk AutoCAD Computer aided design CAD software Hot technology
Microsoft Excel Spreadsheet software Hot technology
Microsoft Office software Office suite software Hot technology
Microsoft Word Word processing software Hot technology
SAP software Enterprise resource planning ERP software Hot technology
Blueprint display software Graphics or photo imaging software
Timekeeping software Time accounting software

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.

Indoors, Environmentally Controlled 5.0
Wear Common Protective or Safety Equipment such as Safety Shoes, Glasses, Gloves, Hearing Protection, Hard Hats, or Life Jackets 5.0
Face-to-Face Discussions with Individuals and Within Teams 4.9
Spend Time Using Your Hands to Handle, Control, or Feel Objects, Tools, or Controls 4.3
Work With or Contribute to a Work Group or Team 4.2
Importance of Being Exact or Accurate 4.2
Contact With Others 4.0
Health and Safety of Other Workers 3.9
Time Pressure 3.8
Freedom to Make Decisions 3.6
Importance of Repeating Same Tasks 3.5
Spend Time Making Repetitive Motions 3.5
Determine Tasks, Priorities and Goals 3.5
Work Outcomes and Results of Other Workers 3.3
Physical Proximity 3.3
Exposed to Contaminants 3.3
Spend Time Standing 3.3
Coordinate or Lead Others in Accomplishing Work Activities 3.2
E-Mail 3.2
Exposed to Sounds, Noise Levels that are Distracting or Uncomfortable 3.1
Exposed to Hazardous Conditions 2.9
Level of Competition 2.8
Spend Time Sitting 2.7
Written Letters and Memos 2.6
Exposed to Hazardous Equipment 2.6
Spend Time Bending or Twisting Your Body 2.5
Consequence of Error 2.5
Frequency of Decision Making 2.5
Exposed to Cramped Work Space, Awkward Positions 2.5
Spend Time Walking or Running 2.4
Deal With External Customers or the Public in General 2.4
Pace Determined by Speed of Equipment 2.3
Degree of Automation 2.3
Conflict Situations 2.3
Impact of Decisions on Co-workers or Company Results 2.3
Exposed to Extremely Bright or Inadequate Lighting Conditions 2.2
Dealing With Unpleasant, Angry, or Discourteous People 2.2
Exposed to Minor Burns, Cuts, Bites, or Stings 2.2
Spend Time Kneeling, Crouching, Stooping, or Crawling 1.8
Telephone Conversations 1.7

How to get in

Job zone
Zone 2 — Job Zone 1-2: Very Little to Some Preparation Needed
Education
Usually requires a high school diploma or GED, though some occupations may not.
Related experience
Some occupations may need little or no previous experience; others require several months to a year of experience. For example, landscaping and groundskeeping workers might require very little training or previous experience, while agricultural equipment operators can benefit from on-the job training.
Preparation level
SVP (Below 6.0) — total schooling plus on-the-job experience.

Education of current workers

Share of people in this occupation at each level of education.

High School Diploma 52.7%
Some College Courses 16.9%
Post-Secondary Certificate 10.8%
Doctoral Degree 0.6%

Interests & work styles

The interests and personal qualities O*NET associates with people who do this work.

Career interests (Holland / RIASEC)

Realistic 7.0
Conventional 5.0
Investigative 3.4
Artistic 1.4

Interest areas

Mechanics/Electronics 6.4
Engineering 4.8
Physical/Manual Labor 3.3
Information Technology 1.8
Mathematics/Statistics 1.6
Physical Science 1.5
Transportation/Machine Operation 1.5
Construction/Woodwork 1.3
Accounting 1.2

Work styles

Attention to Detail 2.6
Dependability 2.3
Cautiousness 2.0
Exposure quadrant: AI task-overlap percentile vs Median pay AI task-overlap (horizontal) versus median pay (vertical) for 11 occupations adjacent to Electromechanical Equipment Assemblers. Lower overlap · higher pay Higher overlap · higher pay Higher overlap · lower pay Lower overlap · lower pay Timing Device Assemblers and Adjusters Aircraft Structure, Surfaces, Rigging, and Systems Assemblers Electric Motor, Power Tool, and Related Repairers Robotics Technicians Electrical and Electronic Engineering Technologists and Technicians Calibration Technologists and Technicians AI task-overlap percentile → ↑ Median pay
AI task-overlap percentile (horizontal) vs. median-pay percentile (vertical), across all scored occupations. This occupation is highlighted; related occupations are plotted alongside it. Overlap measures shared tasks with AI, not automation.

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 Electromechanical Equipment Assemblers — not advice or a forecast. Each is a real cross-link you can follow into the evidence.

Write a report on thisheadline · factoids · citation

Electromechanical Equipment Assemblers sit at the 22nd percentile of AI task overlap among U.S. occupations

  • Electromechanical Equipment Assemblers rank in the 22nd percentile (Low 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
  • Of the AI use actually observed for this work, 24% 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
Copy the whole kit
Electromechanical Equipment Assemblers sit at the 22nd percentile of AI task overlap among U.S. occupations

• Electromechanical Equipment Assemblers rank in the 22nd percentile (Low 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)
• Of the AI use actually observed for this work, 24% 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 — "Electromechanical Equipment Assemblers". https://singulariki.com/roles/role-51-2023-00
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.

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.

Data compiled June 2, 2026. Figures are estimates, not advice.

Cite this page
Plain

Singulariki. "Electromechanical Equipment Assemblers." Singulariki: a source-backed encyclopedia of work. Built from O*NET 30.3; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); “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-51-2023-00

APA

Singulariki. (2026). Electromechanical Equipment Assemblers. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-51-2023-00

BibTeX
@misc{singulariki-role-51-2023-00,
  title  = {Electromechanical Equipment Assemblers},
  author = {{Singulariki}},
  year   = {2026},
  note   = {O*NET 30.3; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); “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-51-2023-00}
}

Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.

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