AI exposure: 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. May ascertain insurance rates required and cash reserves necessary to ensure payment of future benefits.
Reading this score
computed38.9% of this occupation's weighted task load is exposed, which puts Actuaries at the 69th percentile of 923 occupations. The capability is largely there. Its average task scores 2.5 out of 4 on what a current system can produce, and the frictions that hold other jobs in place are comparatively weak here.
What holds the line here is context. Across this occupation's 15 tasks it averages 2.49 out of 3, the highest of the five friction dimensions. In plain terms, the work depends on knowledge the model cannot hold. Much of this job runs on things that were never written down: what this particular organisation does, what happened last week, what the person across the table actually meant. That context is the barrier, and it erodes as systems are given more access.
The most exposed thing this job does is Construct probability tables for events such as fires, natural disasters, and unemployment,..., at 86.7%. The least is Testify in court as expert witness or to provide legal evidence on matters such as the value of..., at 0.0%. A gap of 86.7% between two parts of the same job is the reason this index publishes at task level. An occupation-wide number would have hidden both.
Within computer and mathematical occupations, this one is less exposed than the median of 57.8% across the group's 36 roles, with 35 scoring higher. Being in an exposed family does not make a particular job exposed, and the reverse holds too.
What would move this score. Of 15 tasks, 7 are currently banded exposed, 6 assisted and 2 untouched. For that distribution to shift materially would take a change in who is permitted to sign the work, which is a question for regulators rather than for engineers. The score is re-computed every quarter against a fresh capability reference, and the change is published rather than quietly applied.
Task by task
15 tasks, O*NET 31.0| Task | Exposed | Assisted | Untouched | Importance | Band |
|---|---|---|---|---|---|
| Construct probability tables for events such as fires, natural disasters, and unemployment, based on analysis of statistical data and other pertinent information. | 86.7% | 13.3% | 0.0% | 3.67 | exposed |
| Explain changes in contract provisions to customers. | 66.7% | 33.3% | 0.0% | 3.30 | exposed |
| Analyze data to determine premium rates required and cash reserves and liabilities necessary to ensure payment of future benefits. | 55.6% | 27.8% | 16.7% | 4.76 | exposed |
| Analyze statistical information to estimate mortality, accident, sickness, disability, and retirement rates. | 53.3% | 46.7% | 0.0% | 4.42 | exposed |
| Provide advice to clients on a contract basis, working as a consultant. | 52.5% | 35.0% | 12.5% | 4.03 | exposed |
| 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. | 45.0% | 30.0% | 25.0% | 4.21 | exposed |
| Determine, or help determine, company policy, and explain complex technical matters to company executives, government officials, shareholders, policyholders, or the public. | 40.0% | 35.0% | 25.0% | 3.97 | exposed |
| Design, review, and help administer insurance, annuity and pension plans, determining financial soundness and calculating premiums. | 23.3% | 26.7% | 50.0% | 4.34 | assisted |
| Determine equitable basis for distributing surplus earnings under participating insurance and annuity contracts in mutual companies. | 23.3% | 26.7% | 50.0% | 3.64 | assisted |
| Determine policy contract provisions for each type of insurance. | 23.3% | 26.7% | 50.0% | 3.57 | assisted |
| Provide expertise to help financial institutions manage risks and maximize returns associated with investment products or credit offerings. | 23.3% | 26.7% | 50.0% | 3.53 | assisted |
| Negotiate terms and conditions of reinsurance with other companies. | 23.3% | 26.7% | 50.0% | 3.37 | assisted |
| Manage credit and help price corporate security offerings. | 23.3% | 26.7% | 50.0% | 2.73 | assisted |
| Testify before public agencies on proposed legislation affecting businesses. | 0.0% | 0.0% | 100.0% | 3.09 | untouched |
| 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. | 0.0% | 0.0% | 100.0% | 2.40 | untouched |
Task text and importance ratings sourced from O*NET 31.0. Shares computed. The occupation score is the importance-weighted mean.
Where the score comes from
judgedEvery task is scored through the standardised work activities it maps to. These are this occupation’s averages on the six rubric dimensions. Capability is what AI can do; the other five are what stands in the way.
| Dimension | Mean | Scale |
|---|---|---|
| Capability | 2.46 | 0-4 |
| Embodiment | 0.27 | 0-3 |
| Presence | 1.16 | 0-3 |
| Accountability | 1.73 | 0-3 |
| Context | 2.49 | 0-3 |
| Verification cost | 1.96 | 0-3 |
What this means in practice
Where most of a role's weighted task load is exposed, the work that survives is usually the part of the job nobody wrote into the job description: deciding what should be produced rather than producing it, and being answerable for the result. The tasks lowest on this page are a better guide to where to spend your time than any general advice about the future of work.
Occupations either side of this one
The four closest scores in the same occupational family, then the four closest anywhere in the index.
Read this carefully. Exposure is not displacement. A high score means current AI systems can produce this work, not that anyone will stop paying a person to do it. Adoption depends on economics, regulation and inertia that this index deliberately does not model. How the score is built.