AI Automation Index

Will AI Replace Actuaries?

Task-level automation exposure for Actuaries: 15 O*NET tasks scored against their work activities, plus the simulator.

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Developed & audited by Gini Loh

Automation Exposure

49% weighted task index

15 of 15 tasks scored

Median Salary

$130,000 / year

BLS OEWS, May 2025 — this exact occupation

Employment Level

Medium

26,670 people hold this job — size, not growth

Projected 2025–35

+9.2% employment change

1,500 openings a year · BLS line item

Pay by state

BLS OEWS publishes 37 state estimates for this occupation. Each is its own survey estimate, not the national median adjusted for local prices.

$68,100 – $166,800

Highest medians

Connecticut $166,800

District of Columbia $166,230

New York $156,480

New Jersey $142,800

Alabama $136,950

Lowest medians

Puerto Rico $68,100

Louisiana $80,860

Michigan $100,640

Indiana $100,690

Nebraska $102,790

State figures come from the 15-2011 row in the May 2025 state panel. States where the estimate was suppressed or too small to publish are absent.

What the score is made of

Each task is mapped to its work activities, scored for AI automation potential, and weighted by how important those activities are to the job. These are the components.

Automation potential 49%

Importance-weighted mean of the scored tasks. This is the headline index.

Physical work 0%

Share of weighted tasks in hands-on or machine-operating work activities.

Judgment & influence 73%

Share in analysis, decisions, teaching, directing, advising, or caring for others.

Routine administration 0%

Share in documenting, recording, and administrative activities.

Rewritten by O*NET 0%

Share of weighted tasks O*NET rewrote in a recent update. Reported, not folded into the score.

Consequence of error 6/100 Low

O*NET's own rating of how serious an uncorrectable mistake would be here — respondents, not us. Deliberately not in the index: the score measures what AI can do with the task content, and multiplying it by stakes would be our judgment dressed as data.

Constituent Task Mix

15 tasks for this occupation, weighted by work-activity importance. Shares below are of total task weight, not task count.

High exposure (≥ 60% of the task is automatable) 33%

4 tasks

Medium exposure (≥ 35%) 58%

9 tasks

Low exposure (below 35%) 8%

2 tasks

How would you survive?

Move your week away from the high-exposure tasks and toward the ones that need judgment. The simulator recalculates the index as you shift the mix.

Simulate Upskilling →

Emerging & rewritten tasks

Tasks O*NET added or rewrote for this occupation in its recent updates (05/2025 – 08/2026), with who proposed them. Additions are not in the scored task inventory — they are new work O*NET is still measuring, so they appear here and nowhere in the index. A Revision replaces a task that is scored, which is why only those move the "Rewritten by O*NET" share.

New 08/2026 · Occupational Expert

Develop and maintain projection models.

Constituent Tasks

#24015 · Core · 62% automatable

Analyze data to determine premium rates required and cash reserves and liabilities necessary to ensure payment of future benefits.

data analysis — Operational/research data analysis; human interprets

Analyze operational or research data. Analyze data to inform operational decisions or activities. Manage financial activities of the organization.

#3501 · Core · 72% automatable

Analyze statistical information to estimate mortality, accident, sickness, disability, and retirement rates.

data analysis — Statistical analysis of health data; clinician verifies

Analyze health-related data.

#3502 · Core · 40% automatable

Design, review, and help administer insurance, annuity and pension plans, determining financial soundness and calculating premiums.

decision support — Broad financial stewardship; accountability stays with humans

Manage financial activities of the organization.

#3503 · Core · 50% automatable

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.

interpersonal — Strategy collaboration needs human buy-in and judgment

Collaborate with others to develop or implement marketing strategies.

#3506 · Core · 60% automatable

Provide advice to clients on a contract basis, working as a consultant.

decision support — Technical advice needs product-specific human judgment

Advise customers on technical or procedural issues. Advise others on legal or regulatory compliance matters.

#3504 · Core · 58% automatable

Determine, or help determine, company policy, and explain complex technical matters to company executives, government officials, shareholders, policyholders, or the public.

text generation — Goals drafted; leadership accountability human

Develop organizational goals or objectives.

#3508 · Core · 82% automatable

Construct probability tables for events such as fires, natural disasters, and unemployment, based on analysis of statistical data and other pertinent information.

data analysis — Trend and relationship detection in data

Analyze data to identify trends or relationships among variables.

#3512 · Core · 40% automatable

Determine equitable basis for distributing surplus earnings under participating insurance and annuity contracts in mutual companies.

decision support — Broad financial stewardship; accountability stays with humans

Manage financial activities of the organization.

#3509 · Core · 40% automatable

Determine policy contract provisions for each type of insurance.

decision support — Broad financial stewardship; accountability stays with humans

Manage financial activities of the organization.

#3511 · Core · 40% automatable

Provide expertise to help financial institutions manage risks and maximize returns associated with investment products or credit offerings.

decision support — Broad financial stewardship; accountability stays with humans

Manage financial activities of the organization.

#20951 · Core · 35% automatable

Negotiate terms and conditions of reinsurance with other companies.

interpersonal — Contract negotiation needs mandate and accountability

Negotiate contracts with clients or service providers.

#3505 · Core · 15% automatable

Testify before public agencies on proposed legislation affecting businesses.

interpersonal — Testimony carries legal accountability and live presence

Testify at legal or legislative proceedings.

#3513 · Supplemental · 45% automatable

Explain changes in contract provisions to customers.

interpersonal — Customer service is relational and accountability-bearing

Provide customer service to clients or users.

#3510 · Supplemental · 40% automatable

Manage credit and help price corporate security offerings.

decision support — Broad financial stewardship; accountability stays with humans

Manage financial activities of the organization.

#3507 · Supplemental · 15% automatable

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.

interpersonal — Testimony carries legal accountability and live presence

Testify at legal or legislative proceedings.

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Community Sentiment

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Method

How this was scored

1. Tasks. O*NET task statements for this occupation, from a release whose newest record is dated 08/2026.
2. Work activities. Each task maps to 1–5 Detailed Work Activities; each activity belongs to one of 41 Generalized Work Activities that O*NET rates for importance (1–5) in this occupation.
3. Automation potential. Every work activity carries one score for how far current AI can perform it end-to-end. Tasks inherit the mean of their activities.
4. Weighting. Task weight = 0.35 + 0.65 × (importance − 1)/4, scaled by how often the task is performed and by 0.7 for Supplemental tasks. Importance is the task's own O*NET rating where it exists (18,369 of 18,838 tasks); the rest inherit their work activities' importance. The index is the weighted mean.

Check: across the 910 occupations where O*NET also rates how far machine speed sets the pace, this index moves opposite to it (Spearman ρ = -0.49). The more a job is paced by equipment, the less of its task content AI can address — the relationship you would expect if the scoring is working.

Sources · O*NET 31.0 (task records to 08/2026) · BLS OEWS May 2025 · BLS projections 2025-2035 · rubric v2.1 · tasks for O*NET, not a forecast

See the full method →

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