AI Delegation Index

AI Delegation Index

What work could you hand off to an AI agent?

Actuaries

Strong

AI agents could handle several recurring digital workflows in this job, while people remain responsible for judgment and final decisions.

Where agents can help most

  1. 1

    Update probability tables and check results

    Use an agent to ingest historical event data, build updated probability tables, and run back-tests and outlier checks on the results.

  2. 2

    Review rates and reserve estimates

    Use an agent to review loss, mortality, and claim experience files, refresh pricing and reserve assumptions, and prepare a rate-and-reserve memo with sensitivity checks.

  3. 3

    Draft actuarial advice for client needs

    Use an agent to organize a client’s data, test the reasonableness of mortality or claim assumptions, and draft a consulting note that ties the calculations back to the source files.

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O*NET-SOC 15-2011.00 · #99 of 923

Result context

How to read this result

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. May ascertain insurance rates required and cash reserves necessary to ensure payment of future benefits.

National position
#99 of 923 occupations
Top 11% of occupations
Overall AI delegation potential
Strong
Potential of score-contributing workflows
Strong · 79/100
Meaningful work covered
72%

The overall rating combines how useful the best agent workflows are with how much of the occupation they address. It is not an estimate of job automation or replacement.

Recommended agent uses

3 workflows you could delegate to AI

1

Update probability tables and check results

How you could use an agent

Use an agent to ingest historical event data, build updated probability tables, and run back-tests and outlier checks on the results. The agent can then package the tables with notes on assumptions and any segments that look unstable so you have a ready review draft.

Where you stay involved

You decide whether the data and assumptions are sound, confirm the tables make actuarial sense, and choose whether the update is ready to use.

Review level: Medium

2

Review rates and reserve estimates

How you could use an agent

Use an agent to review loss, mortality, and claim experience files, refresh pricing and reserve assumptions, and prepare a rate-and-reserve memo with sensitivity checks. The agent can line up the calculations and highlight anything that looks inconsistent so you can focus on the insurance judgment.

Where you stay involved

You review the assumptions, decide whether any proposed change is acceptable, and approve the final rate or reserve recommendation.

Review level: High

3

Draft actuarial advice for client needs

How you could use an agent

Use an agent to organize a client’s data, test the reasonableness of mortality or claim assumptions, and draft a consulting note that ties the calculations back to the source files. It can also flag missing data or unclear points so you can shape the final advice without starting from scratch.

Where you stay involved

You decide what advice is appropriate, handle any legal or contract questions, and deliver the final professional judgment.

Review level: High

Documentation and coordination support

AI can assist without owning the physical outcome

These support steps are shown separately. They do not count as agentic workflows and do not increase this occupation's score.

Assemble testimony evidence packet

Use an agent to gather actuarial exhibits, check calculations for lifetime earnings or benefit liability estimates, and assemble a clean support file for a case or hearing. The agent can cross-check citations and consistency across documents so the designated professional has an organized record to work from.

Supporting analysis

Why this occupation's AI delegation potential is Strong

Underlying methodology score

75 / 100

This technical score determines the qualitative rating; it is not an estimate of the share of the occupation that can be automated.

Importance & frequency74
AI capability89
Digital actionability93
End-to-end leverage87
Safety & reversibility55
Meaningful-work coverage
72%
Physical-work modifier
Limited
Safety modifier
Moderate
Qualitative judgment
No material constraint
O*NET task evidence
15 tasks

O*NET 31.0 · methodology 3.3.0. Every workflow passes an action-level physical-execution and protected human-and-veterinary clinical-action gate. Documentation workflows must own a complete digital loop and use digital task evidence only; support-only workflows are disclosed separately and excluded from scoring. Artistic, editorial, normative, and policy-dependent work receives a transparent human-judgment constraint. National ranking within 923 scored O*NET occupations under methodology 3.3.0.

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