π‘ Life Scientists have a composite risk score of 32/100 (Frey-Osborne probability: 40%, GenAI exposure: 35/100). With 374,670 workers in the US, this occupation faces moderate but manageable AI pressure. Full occupation profile β
π― The Verdict
Partially. Some tasks will be automated, but the core role will likely adapt and evolve.
With 374,670 workers and a median wage of $91K,life scientists represent a significant portion of the US workforce. Their GenAI exposure index is 35%, meaning a minority of their core tasks overlap with current generative AI capabilities.
Risk Score
32/100
Employment
374,670
Median Wage
$91K
GenAI Exposure
35%
β οΈ Top Risk Factors
AI-accelerated data analysis and pattern recognition
Automated laboratory instrumentation and workflows
Machine learning models replacing manual hypothesis testing
π‘οΈ Tasks AI Can't Easily Replace
Designing novel experiments and research methodologies
Interpreting ambiguous results with domain expertise
Fieldwork in unstructured natural environments
Collaborative scientific discourse and peer review
π Career Transition Paths
Related occupations with lower AI risk and high skills overlap:
Dentists, All Other Specialists
63% skills overlap Β· $226K median wage
Social Scientists and Related Workers
82% skills overlap Β· $93K median wage
Political Scientists
74% skills overlap Β· $139K median wage
β Frequently Asked Questions
Will AI completely replace life scientists?
Partially. Some tasks will be automated, but the core role will likely adapt and evolve.
What is the AI risk score for life scientists?
Life Scientists have a composite AI automation risk score of 32 out of 100, classified as "Moderate".
How many life scientists are there in the US?
There are approximately 374,670 life scientists employed in the United States.
What do life scientists earn?
The median annual wage for life scientists is $91K.
What skills should life scientists develop?
Focus on tasks AI can't easily replicate: designing novel experiments and research methodologies, interpreting ambiguous results with domain expertise, fieldwork in unstructured natural environments, collaborative scientific discourse and peer review. These human-centric skills will become more valuable as routine tasks are automated.