Actuaries: daily tasks & AI impact
This page breaks Actuaries into the top 15 daily O*NET tasks and scores each for Generative AI automation probability. Those task scores roll up to an overall vulnerability index of 44/100 (Moderate automation risk). Struck-through rows are ≥80% automatable; highlighted safer rows are under 30% or primarily physical.
High-automation exposure
No task in this set currently exceeds the 80% threshold, so risk is spread across moderate probabilities rather than a few catastrophic duties.
Durable human work
This profile has little “safe” task mass under our thresholds. Workers should treat AI fluency as mandatory and actively map transferable skills into lower-risk roles.
Importance comes from O*NET incumbent ratings. Automation probability is model-generated for current Generative AI capability (not speculative AGI). Digital / physical / mixed labels describe the modality of the work, which strongly correlates with near-term automation potential.
| Task | Importance | AI probability | Nature |
|---|---|---|---|
| Ascertain premium rates required and cash reserves and liabilities necessary to ensure payment of future benefits. Core | 4.54 | — | — |
| 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. Core | 4.46 | — | — |
| Analyze statistical information to estimate mortality, accident, sickness, disability, and retirement rates. Core | 4.44 | — | — |
| Design, review, and help administer insurance, annuity and pension plans, determining financial soundness and calculating premiums. Core | 4.4 | — | — |
| Determine, or help determine, company policy, and explain complex technical matters to company executives, government officials, shareholders, policyholders, or the public. Core | 4.26 | — | — |
| Construct probability tables for events such as fires, natural disasters, and unemployment, based on analysis of statistical data and other pertinent information. Core | 4.17 | — | — |
| Provide advice to clients on a contract basis, working as a consultant. Core | 3.8 | — | — |
| Determine equitable basis for distributing surplus earnings under participating insurance and annuity contracts in mutual companies. Core | 3.27 | — | — |
| Negotiate terms and conditions of reinsurance with other companies. Core | 3.27 | — | — |
| Provide expertise to help financial institutions manage risks and maximize returns associated with investment products or credit offerings. Core | 3.12 | — | — |
| Testify before public agencies on proposed legislation affecting businesses. Core | 3.05 | — | — |
| Determine policy contract provisions for each type of insurance. Core | 3 | — | — |
| Testify in court as expert witness or to provide legal evidence on matters such as the value of potential lifetime earnings of a person disabled or killed in an accident. Supplemental | 2.68 | — | — |
| Explain changes in contract provisions to customers. Supplemental | 2.42 | — | — |
| Manage credit and help price corporate security offerings. Supplemental | 2.36 | — | — |
What remains human
No tasks currently fall under the safe threshold for this occupation.
FAQ
Which Actuaries tasks are most exposed to AI?
No task in this set currently exceeds the 80% threshold, so risk is spread across moderate probabilities rather than a few catastrophic duties.
Which Actuaries tasks are safest from Generative AI?
This profile has little “safe” task mass under our thresholds. Workers should treat AI fluency as mandatory and actively map transferable skills into lower-risk roles.
How should I read the Actuaries task table?
Importance comes from O*NET incumbent ratings. Automation probability is model-generated for current Generative AI capability (not speculative AGI). Digital / physical / mixed labels describe the modality of the work, which strongly correlates with near-term automation potential.