Statisticians
United States · BLS Employment Projections 2024–34 (figures for SOC 15-2041 occupational group)
AI exposure in published research
Figures below are reproduced from external datasets without modification. Where a dataset does not cover this occupation, the value is shown as — rather than as zero.
Data provider: OpenAI · "GPTs are GPTs"
Time basis: 2023 baselineex-ante estimate
Scored against GPT-4-generation capability.
- Human rater basis
- 71.1%
- GPT-4 rater basis
- 78.9%
β = direct exposure (E1) + 0.5 × exposure when tools are available (E2), per the source repository's definition.
19 rated tasks · 19 tasks with β ≥ 0.5 (100.0%)
- Version:
- gh-main-0471612
- License:
- MIT License · Copyright (c) 2024 OpenAI
Data provider: Anthropic Economic Index
Time basis: Published 2026-03-05composite index
- Observed exposure
- 21.1%
Theoretical exposure index weighted by measured Claude usage, per the original report's definition.
47 tasks · usage observed in 15 · mean 28.4%
Data: Anthropic Economic Index — labor_market_impacts, CC-BY, https://huggingface.co/datasets/Anthropic/EconomicIndex
AI Changing Work uses Anthropic Economic Index data under CC-BY; Anthropic does not endorse or sponsor this site or its analyses.
- Version:
- hf-lmi-2026-03
- License:
- CC BY 4.0
- Observation period:
- — (not applicable to this release)
- Model:
- — (not stated by the source)
- Definition source:
- https://www.anthropic.com/research/labor-market-impacts
2023 prediction vs observation-based index published 2026-03-05
One card (GPTs are GPTs) is a 2023 estimate of what AI could theoretically do; the other (Anthropic Economic Index) is built from observed usage and was published on 2026-03-05 — that is its publication date, not the period it observed. They measure different things, so the two figures cannot be added, averaged, or ranked against each other. The older figure is kept here as a baseline for comparison rather than removed.
Caution: the Anthropic figures — observed exposure and task penetration — take the Eloundou β as one of their inputs. The two sides resembling each other is therefore not evidence that the earlier prediction came true; reading it that way is circular reasoning.
The Anthropic figures are measured on Claude users, who are not the whole economy and not the whole workforce.
The mapping of O*NET tasks and occupation codes was performed by AI Changing Work. The source figures themselves were not modified.
These indices are not forecasts. Which point in time each one belongs to is stated on the badge on its card.
Task Breakdown
- Analyze statistical data
- Design surveys and experiments
- Build predictive models
- Interpret and communicate findings
About This Occupation
If you work as a Statisticians, AI is reshaping your profession. With an automation risk of 35/100 and overall exposure at 78%, this role faces very high transformation. The highest-impact area is build predictive models at 82% automation. This is classified as an 'augment' role. BLS projects +30% growth through 2034. Professionals who embrace AI tools will see their capabilities significantly amplified.
ISCO-08 classification
Mathematicians, Actuaries and Statisticians
Definition
ILO original text (English)
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.
Definition & vocabulary source
Source: International Labour Organization (ILO) — ISCO-08 Structure
License: ILO CC BY 4.0
Official occupational information
- ONET15-2011.00
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.
View original - ONET15-2021.00
Mathematicians
Conduct research in fundamental mathematics or in application of mathematical techniques to science, management, and other fields. Solve problems in various fields using mathematical methods.
View original - ONET15-2031.00
Operations Research Analysts
Formulate and apply mathematical modeling and other optimizing methods to develop and interpret information that assists management with decisionmaking, policy formulation, or other managerial functions. May collect and analyze data and develop decision support software, services, or products. May develop and supply optimal time, cost, or logistics networks for program evaluation, review, or implementation.
View original - ONET15-2041.00
Statisticians
Develop or apply mathematical or statistical theory and methods to collect, organize, interpret, and summarize numerical data to provide usable information. May specialize in fields such as biostatistics, agricultural statistics, business statistics, or economic statistics. Includes mathematical and survey statisticians.
View original - ONET15-2041.01
Biostatisticians
Develop and apply biostatistical theory and methods to the study of life sciences.
View original - ONET15-2051.02
Clinical Data Managers
Apply knowledge of health care and database management to analyze clinical data, and to identify and report trends.
View original - ONET19-3022.00
Survey Researchers
Plan, develop, or conduct surveys. May analyze and interpret the meaning of survey data, determine survey objectives, or suggest or test question wording. Includes social scientists who primarily design questionnaires or supervise survey teams.
View original
Frequently Asked Questions
The Anthropic Economic Index puts observed exposure at 21.1%. The OpenAI "GPTs are GPTs" rubric puts occupation-level β at 71.1% under human raters. Both figures are reproduced from published research without modification.
They come from two published datasets: the Anthropic Economic Index (labor_market_impacts, CC BY 4.0) and the OpenAI "GPTs are GPTs" exposure rubric (MIT License, Copyright (c) 2024 OpenAI). AI Changing Work maps them onto O*NET occupation and task codes and does not calculate exposure scores of its own. AI Changing Work uses Anthropic Economic Index data under CC-BY; Anthropic does not endorse or sponsor this site or its analyses.
No. They are a diagnosis of exposure as measured at the time each source dataset was published. AI Changing Work publishes no prediction of future automation or job displacement for this occupation.
Recent Changes Affecting This Occupation
Mar 2026: Published evergreen blog post analyzing AI impact on statistics: 78% exposure yet +30% BLS growth, causal inference and experimental design remain human.
[Source: AI Changing Work Blog]Mar 2026: Blog post on survey statisticians references statisticians data. 83% exposure, 37% risk.
[Source: ACW Blog]