π‘ Actuaries have a composite risk score of 32/100 (Frey-Osborne probability: 21%, GenAI exposure: 88/100). With 28,340 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 28,340 workers and a median wage of $126K,actuaries represent a significant portion of the US workforce. Their GenAI exposure index is 88%, meaning a majority of their core tasks overlap with current generative AI capabilities.
Risk Score
32/100
Employment
28,340
Median Wage
$126K
GenAI Exposure
88%
β οΈ Top Risk Factors
Large language model automation of analysis tasks
AI pair-programming and code generation tools
Low-code / no-code platforms reducing custom development
π‘οΈ Tasks AI Can't Easily Replace
Cross-functional collaboration on ambiguous problems
Architecting novel systems requiring creative problem-solving
Stakeholder negotiation and requirements elicitation
Ethical AI oversight and bias auditing
π Career Transition Paths
Related occupations with lower AI risk and high skills overlap:
Advertising, Marketing, Promotions, Public Relations, and Sales Managers
57% skills overlap Β· $145K median wage
Mathematicians
81% skills overlap Β· $122K median wage
Computer and Information Research Scientists
79% skills overlap Β· $141K median wage
β Frequently Asked Questions
Will AI completely replace actuaries?
Partially. Some tasks will be automated, but the core role will likely adapt and evolve.
What is the AI risk score for actuaries?
Actuaries have a composite AI automation risk score of 32 out of 100, classified as "Moderate".
How many actuaries are there in the US?
There are approximately 28,340 actuaries employed in the United States.
What do actuaries earn?
The median annual wage for actuaries is $126K.
What skills should actuaries develop?
Focus on tasks AI can't easily replicate: cross-functional collaboration on ambiguous problems, architecting novel systems requiring creative problem-solving, stakeholder negotiation and requirements elicitation, ethical ai oversight and bias auditing. These human-centric skills will become more valuable as routine tasks are automated.