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.
- Program and use computers to store, process, and analyze data.76
- Collect and analyze biological data about relationships among and between organisms and their environment.76
- Review reports and proposals, such as those relating to land use classifications and recreational development, for accuracy, adequacy, or adherence to policies, regulations, or scientific standards.76
- Write grant proposals to obtain funding for biological research.76
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.
- Measure salinity, acidity, light, oxygen content, and other physical conditions of water to determine their relationship to aquatic life.01
- Develop methods and apparatus for securing representative plant, animal, aquatic, or soil samples.02
- Program and use computers to store, process, and analyze data.03
- Supervise biological technicians and technologists and other scientists.04
- Study basic principles of plant and animal life, such as origin, relationship, development, anatomy, and function.05
Related occupations
Occupations O*NET links to this one. Relatedness reflects shared work, not a claim that these roles are safer.
Molecular and Cellular Biologists
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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.
