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.
- Adjust safety controls, counterweights, door mechanisms, and components such as valves, ratchets, seals, and brake linings.68
- Check that safety regulations and building codes are met, and complete service reports verifying conformance to standards.68
- Connect electrical wiring to control panels and electric motors.66
- Locate malfunctions in brakes, motors, switches, and signal and control systems, using test equipment.63
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.
- Assemble, install, repair, and maintain elevators, escalators, moving sidewalks, and dumbwaiters, using hand and power tools, and testing devices such as test lamps, ammeters, and voltmeters.01
- Disassemble defective units, and repair or replace parts such as locks, gears, cables, and electric wiring.02
- Assemble electrically powered stairs, steel frameworks, and tracks, and install associated motors and electrical wiring.03
- Assemble elevator cars, installing each car's platform, walls, and doors.04
- Maintain log books that detail all repairs and checks performed.05
Related occupations
Occupations O*NET links to this one. Relatedness reflects shared work, not a claim that these roles are safer.
Maintenance and Repair Workers, General
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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.
