Will AI replace Actuaries?

Analyze statistical data, such as mortality, accident, sickness, disability, and retirement rates and construct probability tables to forecast risk and liability for payment of future benefits. The percentage shown is a task-exposure model, not a prediction of certain job loss.

O*NET 30.3 · 15-2011.00 · modeled exposure, not guaranteed job loss
MODERATE TASK EXPOSURE
51%
Estimated share of representative tasks exposed to current AI capabilities.
Last updatedAugust 20, 2026
Evidence confidenceMedium
Browse this risk tierModerate exposure jobs →
Task automation shareⓘ
51%Automatable
Automatable51%
Augmentable25%
Hard to automate24%
Based on analysis of representative responsibilities and current AI capability maturity.
Category#
Tech
Engineering & Product
Modeled pay midpoint$
$63,500/yr
Directional estimate — verify locally
Time until impact⌁
2–4 years
Earliest 2027 · widespread 2029–2031
Task-level replaceability ⓘ
Representative tasks ranked from highest to lowest AI exposure.
◇Ascertain premium rates required and cash reserves and liabilities necessary to ensure payment of future benefits.61%
⚙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.51%
▥Analyze statistical information to estimate mortality, accident, sickness, disability, and retirement rates.40%
✦System accountability and architecture judgment17%
✦Handling ambiguous requirements and trade-offs13%
Impact timeline ⓘ
How AI assistance may move from early support to wider adoption.
2027Next2029–2031
Early impactAI begins supporting ascertain premium rates required and cash reserves and liabilities necessary to ensure payment of future benefits..
Role reshapingRepeatable tasks become faster and more automated.
Wider adoptionThe role centers more on system accountability and architecture judgment.
2–4 yearsdirectional confidence window
HOW AI CHANGES THIS JOBtyping the logic in plain English
01>Start with the real work done by Actuaries.
02>AI can help with: Ascertain premium rates required and cash reserves and liabilities necessary to ensure payment of future benefits.
03>If a task is repetitive and easy to check, AI pressure goes up.
04>But a person is still needed for: System accountability and architecture judgment.
05>Likely result: AI is more likely to change this job than remove it.
06>Important: 51% is estimated task exposure—not a 51% chance of losing the job.
What AI can do
Ascertain premium rates required and cash reserves and liabilities necessary to ensure payment of future benefits.MEDIUM
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.MEDIUM
Analyze statistical information to estimate mortality, accident, sickness, disability, and retirement rates.LOW MATCH
How estimates work →
Your human moat
◆

System accountability and architecture judgment

MEDIUM-HIGH

Combined with handling ambiguous requirements and trade-offs, this keeps a human in the loop.

Strength8.1
Similar-role comparison
RoleRisk
Actuaries51%
Computer Systems Analysts51%
Software Developers50%
Operations Research Analysts52%
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Why this score?

✓The model evaluates 3 representative core tasks.
✓The role mixes repeatable work with human judgment.
✓Occupation and task language comes from O*NET 30.3.
✓The strongest human advantage is system accountability and architecture judgment.
Research basis

O*NET 30.3 occupation tasks plus the ILO 2025 exposure framework. Scores are directional estimates.

Read ILO research →
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Sources for this report

Official occupation tasks; timeline remains uncertain Scores are directional estimates and sources do not endorse this site’s exact percentage.

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