How much of this occupation’s work can be materially affected by current AI systems.
How likely exposure is to translate into reduced human demand.
Includes provisional estimates for AI adoption pressure and labour-market resilience. How this is measured
Confidence reflects task coverage, mapping and capability-evidence quality, and how much of the score rests on provisional inputs.
What is driving the score?
Occupation scores are built from the task mix—not a single prediction about a job title.
Where AI can do more
Routine, digitized, and highly repeatable tasks face the greatest pressure.
- Position, align, or adjust workpieces or electrical parts to facilitate wiring or assembly.80
- Mark and tag components so that stock inventory can be tracked and identified.80
- Distribute materials, supplies, or subassemblies to work areas.80
- Complete, review, or maintain production, time, or component waste reports.80
Where people still matter
These tasks score lowest on automation feasibility—physical presence, judgement, accountability and real-world variability all resist end-to-end automation.
- Fabricate or form parts, coils, or structures according to specifications, using drills, calipers, cutters, or saws.01
- Assemble electrical or electronic systems or support structures and install components, units, subassemblies, wiring, or assembly casings, using rivets, bolts, soldering or micro-welding equipment.02
- Adjust, repair, or replace electrical or electronic components to correct defects and to ensure conformance to specifications.03
- Clean parts, using cleaning solutions, air hoses, and cloths.04
- Inspect or test wiring installations, assemblies, or circuits for resistance factors or for operation, and record results.05
Related occupations
Occupations O*NET links to this one. Relatedness reflects shared work, not a claim that these roles are safer.
Electromechanical Equipment Assemblers
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Compare these careers →Adoption and labour-market outlook
Structural factors are kept separate from raw capability so you can see what actually resists automation. Adoption pressure and labour-market resilience are still provisional models—25% of this occupation’s replacement-risk weight rests on them.
O*NET 30.3 occupational data interpreted through the JobsVsAI capability, automation and structural-constraint models.
