Assemble or modify electromechanical equipment or devices, such as servomechanisms, gyros, dynamometers, magnetic drums, tape drives, brakes, control linkage, actuators, and appliances.
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%
↔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.
Electromechanical Equipment Assemblers sits at the 52nd 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.
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.
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.
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.
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.
Skills that travel
Capabilities this work builds that are used across many other occupations.
▸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.
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 30.3U.S. Department of Labor / National Center for O*NET Development
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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