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Statistical Assistants

Office & Administrative Support
Projected change 2024–34: -2.5%
Median annual wage (2024): $51,440
Employment (2024): 7K

United States · BLS Employment Projections 2024–34 (figures for SOC 43-9111 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
67.4%
GPT-4 rater basis
89.1%

β = direct exposure (E1) + 0.5 × exposure when tools are available (E2), per the source repository's definition.

14 rated tasks · 13 tasks with β ≥ 0.5 (92.9%)

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
51.0%

Theoretical exposure index weighted by measured Claude usage, per the original report's definition.

31 tasks · usage observed in 14 · mean 42.9%

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)

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

  • Compile and tabulate statistical data from source documents
  • Verify accuracy and completeness of data entries
  • Perform routine calculations using statistical formulas
  • Prepare charts, graphs, and statistical reports

About This Occupation

If you work as a Statistical Assistant, AI is reshaping your profession at a rapid pace. With an automation risk of 74/100 and overall exposure at 71%, this role faces very high transformation. The highest-impact area is performing routine calculations using statistical formulas at 92% automation, where AI tools can execute complex computations instantly and without error. Data compilation and tabulation (88%) and report generation (85%) are also heavily automated. This is classified as an 'automate' role, meaning most core tasks can be fully performed by AI systems. BLS projects -4% decline through 2034, as organizations increasingly rely on automated data pipelines. The median annual wage is $48,800. Workers who transition toward data analysis, interpretation, and quality assurance will find stronger long-term career prospects.

ISCO-08 classification

Unit group 3314ILO official

Statistical, Mathematical and Related Associate Professionals

Definition

ILO original text (English)

Statistical, mathematical and related associate professionals assist in planning the collection, processing and presentation of statistical, mathematical or actuarial data and in carrying out these operations, usually working under the guidance of statisticians, mathematicians and actuaries.

Definition & vocabulary source

Source: International Labour Organization (ILO) — ISCO-08 Structure

License: ILO CC BY 4.0

View original

Official occupational information

  • ONET15-2051.00

    Data Scientists

    Develop and implement a set of techniques or analytics applications to transform raw data into meaningful information using data-oriented programming languages and visualization software. Apply data mining, data modeling, natural language processing, and machine learning to extract and analyze information from large structured and unstructured datasets. Visualize, interpret, and report data findings. May create dynamic data reports.

    View original
  • ONET15-2099.01

    Bioinformatics Technicians

    Apply principles and methods of bioinformatics to assist scientists in areas such as pharmaceuticals, medical technology, biotechnology, computational biology, proteomics, computer information science, biology and medical informatics. Apply bioinformatics tools to visualize, analyze, manipulate or interpret molecular data. May build and maintain databases for processing and analyzing genomic or other biological information.

    View original
  • ONET43-9111.00

    Statistical Assistants

    Compile and compute data according to statistical formulas for use in statistical studies. May perform actuarial computations and compile charts and graphs for use by actuaries. Includes actuarial clerks.

    View original

Source: O*NET 30.2, U.S. DOL/ETA

License: CC BY 4.0

View original

Frequently Asked Questions

The Anthropic Economic Index puts observed exposure at 51.0%. The OpenAI "GPTs are GPTs" rubric puts occupation-level β at 67.4% 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.