What this occupation does
Actuaries use mathematics, statistics, and financial theory to measure and price the economic cost of risk and uncertainty, chiefly in insurance and pensions. The role spans building mortality and morbidity models, setting reserves and premium rates, designing insurance and pension products, enterprise risk management, and explaining technical findings to executives, regulators, and boards, with professional accountability carried through actuarial credentialing.
The exposure score in context
The ILO 2025 refined Generative AI Occupational Exposure Index places actuaries in the high exposure gradient. ILO 2025 places mathematicians, actuaries and statisticians (ISCO 2120) in the high exposure gradient (gradient 3, mean task-exposure score 0.56), reflecting significant but uneven exposure. Statistical estimation, data aggregation, and standard reporting are exposed and heavily augmented by generative AI; assumption-setting, reserving judgement, regulatory sign-off, and the professional accountability the credential carries are augmentation-prone but not displaceable at task level.
The mapping uses ISCO-08 code 2120 (BLS-published SOC-to-ISCO crosswalk). The full methodology, including the dominant-match rule for one-to-many crosswalks, is at /methodology/#algorithm.
The top five tasks, classified
The top five O*NET 30.2 tasks for this occupation, each tagged Displaceable / Changing / Growing per the Brookings 2024 task-level rubric. The tag definitions are at /glossary/#displaceable-task, /glossary/#changing-task, and /glossary/#growing-task.
- Changing: Ascertain premium rates required and cash reserves and liabilities necessary to ensure payment of future benefits. AI augments the modelling and computation behind rate-setting; the choice of assumptions and accountability for reserve adequacy remain human and are regulated.
- Growing: 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. Cross-functional judgement about new business is augmentation-prone per Brookings 2024 and grows in importance as AI handles the underlying computation.
- Changing: Analyze statistical information to estimate mortality, accident, sickness, disability, and retirement rates. Generative AI and machine learning heavily accelerate rate estimation from data; validating the estimates and defending the assumptions stay with the actuary.
- Changing: Design, review, and help administer insurance, annuity and pension plans, determining financial soundness and calculating premiums. Product-design analysis is AI-augmented; the financial-soundness determination and its professional sign-off remain human-led.
- Growing: Determine, or help determine, company policy, and explain complex technical matters to company executives, government officials, shareholders, policyholders, or the public. Communicating technical findings to executives and regulators, and the judgement behind policy, are augmentation-prone and grow as routine analysis is automated.
What is growing in this role
The BLS Employment Projections 2024-2034 outlook for actuaries is much faster than average (+22% projected change, no published absolute figure). Source: BLS Employment Projections 2024-2034.
Per the WEF Future of Jobs Report 2025, the top three growing skills relevant to this role are: Analytical thinking, AI and big data, Technological literacy. The skills are mapped to the occupation's O*NET skills profile.
Brookings 2024 places actuarial work across the spectrum: statistical estimation, modelling, and standard reporting are exposed, while assumption-setting, reserving judgement, product design, and regulatory communication are augmentation-prone.
AI's impact on actuary jobs: augmented modelling and the reserving-accountability premium
Actuarial work is quantitative and model-heavy, which is exactly the kind of work generative AI and machine learning now reach into: rate estimation from historical data, scenario modelling, document summarisation, and the routine reporting that fills much of an actuarial workflow. That is why the estimation-and-reporting core of the role tags changing rather than growing. Even so, the US Bureau of Labor Statistics projects employment of actuaries to grow 22 percent from 2024 to 2034, much faster than the roughly 3 percent average across all occupations, from a 2024 base of about 33,600 jobs and a median wage of $125,770 in May 2024.
The reason automation has not shrunk the occupation is the part the models cannot own: choosing the assumptions, defending them to regulators, judging reserve adequacy, and carrying the professional accountability that actuarial credentialing exists to certify. BLS projects about 2,400 openings for actuaries each year over the decade and attributes the growth to developing, pricing, and evaluating insurance products and to enterprise risk management as companies address new and evolving risks. Actuaries who lean into assumption-setting, product design, and enterprise risk management sit on the resilient side of the split; those whose work is mostly routine computation and standard reporting carry the higher exposure the ILO 2025 gradient-3 rating reflects.
Sources: BLS Occupational Outlook Handbook, Actuaries; O*NET OnLine 15-2011.00 (Actuaries).
Similar occupations
O*NET 30.2 lists the following related roles. Each links to its own deep dive where one is published.
Industry context
This role sits primarily in the Finance industry. The industry-level rollup includes the cross-occupation exposure profile and the BLS-published industry-level outlook.
How this assessment was made
The full methodology is at /methodology/: ILO 2025 refined index for the gradient, Brookings 2024 rubric for the task tags, BLS 2024-2034 for the growth outlook, WEF 2025 for the skills demand. The pre-empted critiques are at /how-to-argue-with-this/.