- O*NET-SOC code
- 15-2011.00
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.
- Data source: BLSPublished: 2026-08
Very high· relative
LowFour relative bandsVery highGroup-level value
Scale, basis and source
Four relative bands (Low / Moderate / High / Very high)
831 detailed occupations in the BLS Employment Projections table. Assigned per National Employment Matrix (NEM) code, so occupations sharing a NEM code carry the same band
- Data source: AnthropicPublished: 2026-03
0.054
0.000Range of values carried here0.745Scale, basis and source
Observed exposure index, 0–1 as published
Mapped onto O*NET tasks
Published per SOC 2018 occupation; every O*NET occupation with the same SOC 2018 code carries this value
- Data source: ILOPublished: 2025
0.56
0.09Range of values carried here0.70Group-level value
Scale, basis and source
Generative AI exposure index, 0–1 as published
Published per ISCO-08 unit group. Linked to this occupation, wholly or in part, by applying U.S. Bureau of Labor Statistics crosswalks (ISCO-08 to 2010 SOC, 2010 SOC to 2018 SOC) as published
What kind of figure this source publishes
The BLS category is a relative rank, not an absolute level, and it is not a first-hand measurement: it groups an occupation's percentile ranks across several published studies into four bands. It is not an employment or wage forecast, not a probability of adoption, and it does not separate automation from augmentation.
Task-level exposure
Show 9 hidden tasks15 rated tasks · 15 tasks with β ≥ 0.5 (100.0%)
β = direct exposure (E1) + 0.5 × exposure when tools are available (E2), per the source repository's definition.
- Source unit: O*NET 27.2 tasks → O*NET 31.0 occupation code
- 1 rated task is not in the O*NET 31.0 task list; its score is kept as published for O*NET 27.2.
- Source
- OpenAI "GPTs are GPTs" exposure rubric
- Release
- gh-main-0471612
- License
- MIT License, Copyright (c) 2024 OpenAI
| Task (O*NET 20.1) | Claude.aiRaw / share % | APIRaw / share % |
|---|---|---|
Provide advice to clients on a contract basis, working as a consultant.15-2011.00 | 0.175494.7 | 0.0132100.0 |
Design, review and help administer insurance, annuity and pension plans, determining financial soundness and calculating premiums.15-2011.00 | 0.00361.9 | —0 |
Determine or help determine company policy, and explain complex technical matters to company executives, government officials, shareholders, policyholders, or the public.15-2011.00 | 0.00281.5 | —0 |
Provide expertise to help financial institutions manage risks and maximize returns associated with investment products or credit offerings.15-2011.00 | 0.00201.1 | —0 |
Determine policy contract provisions for each type of insurance.15-2011.00 | 0.00150.8 | —0 |
Values in this tab are predicted labels, not observations. Eloundou et al. (2023) published two rating regimes — human raters and GPT-4 — and the β shown here is derived from the GPT-4 rater basis alone; the same task can take a different value under the other regime. The unit and the meaning differ from the observed shares (%) in the other tabs, so do not place them on the same axis.
| Task (O*NET 27.2) | βE1 + 0.5 × E2 |
|---|---|
Ascertain premium rates required and cash reserves and liabilities necessary to ensure payment of future benefits.O*NET Task ID 3500 | 0.5 |
Analyze statistical information to estimate mortality, accident, sickness, disability, and retirement rates.O*NET Task ID 3501 | 0.5 |
Design, review, and help administer insurance, annuity and pension plans, determining financial soundness and calculating premiums.O*NET Task ID 3502 | 0.5 |
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.O*NET Task ID 3503 | 0.5 |
Determine, or help determine, company policy, and explain complex technical matters to company executives, government officials, shareholders, policyholders, or the public.O*NET Task ID 3504 | 0.5 |
Testify before public agencies on proposed legislation affecting businesses.O*NET Task ID 3505 | 0.5 |
Provide advice to clients on a contract basis, working as a consultant.O*NET Task ID 3506 | 0.5 |
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.O*NET Task ID 3507 | 0.5 |
Construct probability tables for events such as fires, natural disasters, and unemployment, based on analysis of statistical data and other pertinent information.O*NET Task ID 3508 | 0.5 |
Determine policy contract provisions for each type of insurance.O*NET Task ID 3509 | 0.5 |
Manage credit and help price corporate security offerings.O*NET Task ID 3510 | 0.5 |
Provide expertise to help financial institutions manage risks and maximize returns associated with investment products or credit offerings.O*NET Task ID 3511 | 0.5 |
Determine equitable basis for distributing surplus earnings under participating insurance and annuity contracts in mutual companies.O*NET Task ID 3512 | 0.5 |
Explain changes in contract provisions to customers.O*NET Task ID 3513 | 0.5 |
Negotiate terms and conditions of reinsurance with other companies.O*NET Task ID 20951 | 0.5 |
β = E1 + 0.5 × E2 · E1 = tasks where direct LLM access alone cuts time by at least 50%, E2 = tasks where software built on top of an LLM cuts time by at least 50%. Values take only 0 / 0.5 / 1.0.
Data sources & licenses — O*NET®, Anthropic Economic Index, Eloundou et al. (2023): see full notices on the Credits page
All O*NET 31.0 task statements (15)
All O*NET 31.0 task statements for this occupation (English, as published; task type core or supplemental). Exposure values are not listed here; they are in the table above, next to each task statement as worded in the O*NET version each source used.
| Task (O*NET 31.0) | Type |
|---|---|
| Analyze statistical information to estimate mortality, accident, sickness, disability, and retirement rates. | Core |
| Design, review, and help administer insurance, annuity and pension plans, determining financial soundness and calculating premiums. | Core |
| 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 |
| Determine, or help determine, company policy, and explain complex technical matters to company executives, government officials, shareholders, policyholders, or the public. | Core |
| Testify before public agencies on proposed legislation affecting businesses. | Core |
| Provide advice to clients on a contract basis, working as a consultant. | Core |
| Construct probability tables for events such as fires, natural disasters, and unemployment, based on analysis of statistical data and other pertinent information. | Core |
| Determine policy contract provisions for each type of insurance. | Core |
| Provide expertise to help financial institutions manage risks and maximize returns associated with investment products or credit offerings. | Core |
| Determine equitable basis for distributing surplus earnings under participating insurance and annuity contracts in mutual companies. | Core |
| Negotiate terms and conditions of reinsurance with other companies. | Core |
| Analyze data to determine premium rates required and cash reserves and liabilities necessary to ensure payment of future benefits. | Core |
| 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 |
| Manage credit and help price corporate security offerings. | Supplemental |
| Explain changes in contract provisions to customers. | Supplemental |
0.00/ 3· Robot exposure index
Scale, basis and source
Each physical task is graded 0–3 by the setting in which robots that have been deployed, sold or demonstrated could do it (0 none · 1 purpose-built robot settings such as a fenced machine cell or a bottling line · 2 structured facilities such as a hospital pharmacy or a container port · 3 unstructured settings such as a private home or a construction site), and the grades are averaged by share of working time
Physical tasks among this occupation's O*NET 29.3 tasks
Anthropic estimated the grades and time shares with Claude Opus 5 using web search, as of 2026.
The robot exposure index is a different measure from the AI exposure figures on this site and cannot be added to or compared with them. It does not measure actual adoption or cost, and 0 also covers occupations with no physical tasks.
Tier of each physical task
None of this occupation's O*NET 29.3 tasks is classified as a physical task.
Occupation information
Employment outlook (BLS)
- Employment, 2025
- 31K
- Projected employment, 2035
- 34K
- Change (2025–35)
- +9.2%
- Median annual wage, 2025
- $130,000
- Typical education needed for entry
- Bachelor's degree
Korea classification links (KSCO)
Links from the current release of the Korea Occupation Direct Crosswalk v1.1, made by AI Changing Work. Relation values are read from the O*NET-SOC occupation side.
| KSCO code | KSCO title | Relation | Status |
|---|---|---|---|
| 28231 | 보험 상품 개발자 | This occupation is narrower | confirmed |
Relation and status definitions(kr-direct v1.1)
ILO occupational description
AI Changing Work links the ISCO-08 unit groups below to this occupation by applying the U.S. Bureau of Labor Statistics crosswalks (2018 SOC to 2010 SOC, 2010 SOC to ISCO-08) as published, without case-by-case selection; each link may be whole or partial.
- ISCO-08 2120Mathematicians, Actuaries and Statisticians
The definition, tasks and examples below are the ILO's description of that unit group, not of this occupation.
Mathematicians, actuaries and statisticians conduct research and improve or develop mathematical, actuarial and statistical concepts, theories and operational methods and techniques and advise on or engage in their practical application in such fields as engineering, business and social and other sciences.
Tasks
- (a) studying, improving and developing mathematical, actuarial and statistical theories and techniques;
- (b) advising on or applying mathematical principles, models and techniques to a wide range of tasks in the fields of engineering, natural, social or life sciences;
- (c) conducting logical analyses of management problems, especially in terms of input-output effectiveness, and formulating mathematical models of each problem usually for programmeming and solution by computer;
- (c) designing and putting into operation pension schemes and life, health, social and other types of insurance systems;
- (e) applying mathematics, statistics, probability and risk theory to assess potential financial impacts of future events;
- (f) planning and organizing surveys and other statistical collections, and designing questionnaires;
- (g) evaluating, processing, analysing, and interpreting statistical data and preparing them for publication;
- (h) advising on or applying various data collection methods and statistical methods and techniques, and determining reliability of findings, especially in such fields as business or medicine as well as in other areas of natural, social or life sciences;
- (i) preparing scientific papers and reports;
- (j) supervising the work of mathematical, actuarial and statistical assistants and statistical clerks.
Example occupations
Actuary · Demographer · Mathematician · Operations research analyst · Statistician
Sources: ILO ISCO-08 — details: Credits
ESCO occupational vocabulary
Each entry below is matched to this occupation in the published ESCO-O*NET Crosswalk (version 1, 2022). The match types are that crosswalk's; the wording is AI Changing Work's.
- actuarial consultantESCO 2120.1Same scope
Actuarial consultants analyse, manage and provide guidance on financial impact of risks. They can work in fields related to insurance, pension, investment, banking, healthcare etc. Actuarial consultants apply technical and statistical models and theories to give strategic, commercial, and financial advice.
- actuarial assistantESCO 3314.1This occupation is broader
Actuarial assistants perform statistical data research in order to set premium rates and insurance policies. They review the possibility of accidents, injuries and property damage by using statistical formulas and models.
- insurance rating analystESCO 2413.1.2This occupation is broader
Insurance rating analysts analyse information related to insurance markets and their credit rating, prepare rating reports and invoices, compile financial data and present and explain credit rating opinions to stakeholders, clients and external parties. They work for insurance companies and calculate the insurance premium and rates for the company’s clients using both manual and automated methods.
- insurance risk consultantESCO 3321.2This occupation is broader
Insurance risk consultants prepare reports for insurance underwriters. For this purpose, they undertake surveys in order to determine the potential financial risk for personal products, properties or sites.
Source: European Commission, DG EMPL — ESCO API 2026-08-08 (bridge v1.2.1)
License: CC BY 4.0 (EU Reuse Notice)
ESCO reuse terms and the modification notice are in Credits.
France classification links (ROME)
AI Changing Work's links between this occupation and ROME 4.0 job profiles, judged with AI models. Relations are read from this occupation's side. Links marked “provisional” were adopted on the judgments of two judges from the same model family (Claude) alone, or by an operator rule applied to their judgments, so they rest on weaker evidence than confirmed links.
| ROME code | ROME title (French) | Relation |
|---|---|---|
| C1105 | Actuaire en assurances | This occupation is broaderprovisional |
| C1120 | Conseiller / Conseillère en études actuarielles | This occupation is broaderprovisional |
| C1106 | Expert / Experte risques en assurances | Related, not a matchprovisional |
Source: France Travail — Répertoire Opérationnel des Métiers et des Emplois (ROME 4.0), version 61, last updated 15 June 2026 (https://www.data.gouv.fr/datasets/repertoire-operationnel-des-metiers-et-des-emplois-rome). Licence Ouverte 2.0.
ROME codes and titles are reproduced unchanged; the links to O*NET-SOC occupations are AI Changing Work's own judgment and are not a France Travail correspondence.
(AI Changing Work link release: fr-direct v1)
Spain classification links (CNO-11)
AI Changing Work's links between this occupation and CNO-11 occupations, judged with AI models. Relations are read from this occupation's side.
| CNO-11 code | CNO-11 title (Spanish) | Relation |
|---|---|---|
| 2415 | Matemáticos y actuarios | This occupation is narrower |
Source: Instituto Nacional de Estadística (INE), National Classification of Occupations 2011 (CNO-11, Royal Decree 1591/2010) — www.ine.es · Licensed CC BY 4.0. CNO-11 codes and Spanish titles are reproduced unchanged; the links to O*NET occupations are AI Changing Work's own judgment and are not an INE correspondence.
(AI Changing Work link release: es-direct v1)
Germany classification links (KldB)
AI Changing Work's links between this occupation and KldB occupations, judged with AI models. Relations are read from this occupation's side.
| KldB code | KldB title (German) | Relation |
|---|---|---|
| 41184 | Berufe in der Mathematik (sonstige spezifische Tätigkeitsangabe) - hoch komplexe Tätigkeiten | This occupation is narrower |
| 41114 | Berufe in der Statistik - hoch komplexe Tätigkeiten | Related, not a match |
Source: © Statistik der Bundesagentur für Arbeit — Klassifikation der Berufe 2010 – überarbeitete Fassung 2020, https://statistik.arbeitsagentur.de. KldB codes and titles are reproduced unchanged; the links to O*NET occupations are AI Changing Work's own mapping (eigene Zuordnung) and are not a Bundesagentur für Arbeit correspondence.
(AI Changing Work link release: de-direct v1)
Japan classification links (JSCO)
AI Changing Work's links between this occupation and JSCO occupations, judged with AI models. Relations are read from this occupation's side.
| JSCO code | JSCO title (Japanese) | Relation |
|---|---|---|
| 184 | 金融・保険専門職業従事者 | This occupation is narrower |
Source: Ministry of Internal Affairs and Communications (MIC), Japan Standard Occupational Classification (Dec. 2009, MIC Notification No. 555). JSCO codes and Japanese titles are reproduced unchanged; the links to O*NET occupations are AI Changing Work's own judgment and are not a MIC correspondence.
(AI Changing Work link release: jp-direct v1)
Sources, licenses and AI Changing Work's modification and translation notices for this page: Credits & sources