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The AI Resilience Report helps you understand how AI is likely to impact your current or future career. Drawing on data from over 1,500 occupations, it provides a clear snapshot to support informed career decisions.
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Last Update: 5/19/2026
Your role’s AI Resilience Score is
Median Score
Meaningful human contribution
Measures the parts of the occupation that still require a human touch. This score averages data from up to four AI exposure datasets, focusing on the role’s resilience against automation.
Med
Long-term employer demand
Predicts the health of the job market for this role through 2034. Using Bureau of Labor Statistics data, it balances projected annual job openings (60%) with overall employment growth (40%).
Med
Sustained economic opportunity
Measures future earning potential and career flexibility. This score is a blend of total projected labor income (67%) and the role’s inherent ability to adapt to economic and technological shifts (33%).
Med
This reflects the reliability of your score based on the number of data sources available for this career and how closely those sources agree on the outlook. A higher confidence means more consistent evidence from labor experts and AI models.
Most data sources align, with only minor variation. This is a well-supported result.
Contributing sources
Actuaries are somewhat more resilient to AI impacts than most occupations, according to our analysis of 6 sources.
Actuaries are holding up really well against AI because their work goes beyond crunching numbers — it requires human judgment, client-specific problem solving, and the ability to explain complex risks to real people making high-stakes decisions. AI is actually becoming a helpful teammate here, automating the repetitive and time-consuming tasks so actuaries can focus on the more meaningful work of interpreting results and giving strategic advice.
Read full analysisLearn more about how you can thrive in this position
Learn more about how you can thrive in this position
This role is mostly resilient
Actuaries are holding up really well against AI because their work goes beyond crunching numbers — it requires human judgment, client-specific problem solving, and the ability to explain complex risks to real people making high-stakes decisions. AI is actually becoming a helpful teammate here, automating the repetitive and time-consuming tasks so actuaries can focus on the more meaningful work of interpreting results and giving strategic advice.
Read full analysisAnalysis of Current AI Resilience
Actuaries
Updated Quarterly • Last Update: 5/14/2026

Right now, AI is mostly augmenting actuaries—helping them work faster—rather than replacing them. According to the Society of Actuaries, machine learning tools that seemed experimental a few years ago are increasingly being embedded in pricing, reserving, underwriting, claims and reporting processes, and generative AI is helping actuaries draft reports, improve communications, automate documentation, and enhance modeling by creating synthetic datasets. In property and casualty insurance, machine-learning methods like gradient boosting and neural networks can outperform traditional models [1] at spotting complex risk patterns.
A March 2026 article in Contingencies notes that repetitive analyst tasks are most at risk of being automated, so fewer roles may exist at junior levels while demand grows for mid-level interpretation and decision-making. Tellingly, Microsoft's viral list of jobs most likely to be replaced by AI included mathematicians and data scientists—but not actuaries [2], because human judgment and client-specific problem solving still matter.

Adoption is happening quickly in some areas and cautiously in others. Industry publication Digital Insurance reports that AI has emerged as a transformative force in actuarial practices, with insurers using it to automate routine tasks, build predictive models, and boost fraud detection accuracy. But several brakes slow things down: the SOA highlights obstacles including model transparency, a scarcity of actuaries with advanced ML skills, integration with legacy systems, and regulatory uncertainty, plus strict rules like the EU's AI Act demanding explainability.
The good news for students: the U.S. Bureau of Labor Statistics projects 22% growth for actuaries from 2023 to 2033 [3], far above average, and recruiters note that actuarial unemployment stayed under 1% throughout 2025. As one industry leader puts it, those who courageously adapt will shape the future of actuarial science—so learning AI tools, communication, and ethics now is the smartest move.

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They analyze data and use math to predict financial risks, helping companies plan for the future and make smart decisions about money.
Median Wage
$125,770
Jobs (2024)
33,600
Growth (2024-34)
+21.8%
Annual Openings
2,400
Education
Bachelor's degree
Experience
None
Source: Bureau of Labor Statistics, Employment Projections 2024-2034
AI-generated estimates of task resilience over the next 3 years
Testify before public agencies on proposed legislation affecting businesses.
Construct probability tables for events such as fires, natural disasters, and unemployment, based on analysis of statistical data and other pertinent information.
Provide advice to clients on a contract basis, working as a consultant.
Determine or help determine company policy, and explain complex technical matters to company executives, government officials, shareholders, policyholders, or the public.
Testify in court as expert witness or to provide legal evidence on matters such as the value of potential lifetime earnings of a person who is disabled or killed in an accident.
Collaborate with programmers, underwriters, accounts, claims experts, and senior management to help companies develop plans for new lines of business or improvements to existing business.
Explain changes in contract provisions to customers.
Tasks are ranked by their AI resilience, with the most resilient tasks shown first. Core tasks are essential functions of this occupation, while supplemental tasks provide additional context.

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