π‘ Political Scientists have a composite risk score of 25/100 (Frey-Osborne probability: 4%, GenAI exposure: 87/100). With 5,950 workers in the US, this occupation remains well-protected against automation. Full occupation profile β
π― The Verdict
Partially. Some tasks will be automated, but the core role will likely adapt and evolve.
With 5,950 workers and a median wage of $139K,political scientists represent a significant portion of the US workforce. Their GenAI exposure index is 87%, meaning a majority of their core tasks overlap with current generative AI capabilities.
Risk Score
25/100
Employment
5,950
Median Wage
$139K
GenAI Exposure
87%
β οΈ Top Risk Factors
Machine learning models replacing manual hypothesis testing
Automated data interpretation and insight generation
AI summarization replacing manual report compilation
π‘οΈ Tasks AI Can't Easily Replace
Collaborative scientific discourse and peer review
Designing novel experiments and research methodologies
Interpreting ambiguous results with domain expertise
Fieldwork in unstructured natural environments
Ethical oversight of research involving human subjects
π Career Transition Paths
Related occupations with lower AI risk and high skills overlap:
Dentists, All Other Specialists
69% skills overlap Β· $226K median wage
Social Scientists and Related Workers
78% skills overlap Β· $93K median wage
Dentists, General
67% skills overlap Β· $173K median wage
β Frequently Asked Questions
Will AI completely replace political scientists?
Partially. Some tasks will be automated, but the core role will likely adapt and evolve.
What is the AI risk score for political scientists?
Political Scientists have a composite AI automation risk score of 25 out of 100, classified as "Moderate".
How many political scientists are there in the US?
There are approximately 5,950 political scientists employed in the United States.
What do political scientists earn?
The median annual wage for political scientists is $139K.
What skills should political scientists develop?
Focus on tasks AI can't easily replicate: collaborative scientific discourse and peer review, designing novel experiments and research methodologies, interpreting ambiguous results with domain expertise, fieldwork in unstructured natural environments, ethical oversight of research involving human subjects. These human-centric skills will become more valuable as routine tasks are automated.