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.
- Analyze incident data to identify trends in injuries, illnesses, accidents, or other hazards.72
- Provide new-employee health and safety orientations and develop materials for these presentations.72
- Order suspension of activities that pose threats to workers' health or safety.72
- Recommend measures to help protect workers from potentially hazardous work methods, processes, or materials.71
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.
- Maintain inventories of hazardous materials or hazardous wastes, using waste tracking systems to ensure that materials are handled properly.01
- Collect samples of dust, gases, vapors, or other potentially toxic materials for analysis.02
- Collect samples of hazardous materials or arrange for sample collection.03
- Investigate health-related complaints and inspect facilities to ensure that they comply with public health legislation and regulations.04
- Recommend measures to help protect workers from potentially hazardous work methods, processes, or materials.05
Related occupations
Occupations O*NET links to this one. Relatedness reflects shared work, not a claim that these roles are safer.
Occupational Health and Safety Technicians
Closely related work
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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.
