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.
- Control generator output to match the phase, frequency, or voltage of electricity supplied to panels.67
- Take regulatory action, based on readings from charts, meters and gauges, at established intervals.67
- Open and close valves and switches in sequence to start or shut down auxiliary units.67
- Adjust controls to generate specified electrical power or to regulate the flow of power between generating stations and substations.67
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.
- Clean, lubricate, or maintain equipment, such as generators, turbines, pumps, or compressors, to prevent failure or deterioration.01
- Operate, control, or monitor equipment, such as acid or gas carbon dioxide removal units, carbon dioxide compressors, or pipelines, to capture, store, or transport carbon dioxide exhaust.02
- Control power generating equipment, including boilers, turbines, generators, or reactors, using control boards or semi-automatic equipment.03
- Control generator output to match the phase, frequency, or voltage of electricity supplied to panels.04
- Start or stop generators, auxiliary pumping equipment, turbines, or other power plant equipment as necessary.05
Related occupations
Occupations O*NET links to this one. Relatedness reflects shared work, not a claim that these roles are safer.
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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.
