Quantitative Analysts

Business & Financial Operations

AI exposure

  • Data source: BLSPublished: 2026-08

    Very high· relative

    LowFour relative bandsVery high

    Group-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

    Source dataset (XLSX download)

  • Data source: AnthropicPublished: 2026-03

    0.461

    0.000Range of values carried here0.745
    Scale, basis and source

    Observed exposure index, 0–1 as published

    Mapped onto O*NET tasks

    Source dataset

  • Data source: ILOPublished: 2025

    0.44

    0.09Range of values carried here0.70

    Group-level value

    Scale, basis and source

    Generative AI exposure index, 0–1 as published

    ISCO-08 unit group — every occupation sharing the code gets this value

    Computed by this site, not published by the ILO: of the 1,012 occupations this site links to the ILO dataset, 28% score at or above this value.

    Source dataset

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 28 hidden tasks
TaskClaude.aiRaw / share %
Evaluate sources of information to determine any limitations in terms of reliability or usability.

15-2041

0.399527.4
Read technical literature and participate in continuing education or professional associations to maintain awareness of current database technology and best practices.

15-2041

0.13999.6
Examine theories, such as those of probability and inference, to discover mathematical bases for new or improved methods of obtaining and evaluating numerical data.

15-2041

0.09986.8
Develop an understanding of fields to which statistical methods are to be applied to determine whether methods and results are appropriate.

15-2041

0.09396.4
Draw conclusions or make predictions based on data summaries or statistical analyses.

15-2041

0.08375.7
Prepare appropriate formatting to data sets as requested.

15-2041

0.07595.2
Report results of statistical analyses, including information in the form of graphs, charts, and tables.

15-2041

0.07585.2
Process large amounts of data for statistical modeling and graphic analysis, using computers.

15-2041

0.05743.9
Identify relationships and trends in data, as well as any factors that could affect the results of research.

15-2041

0.05343.7
Prepare data for processing by organizing information, checking for any inaccuracies, and adjusting and weighting the raw data.

15-2041

0.05053.5

Data sources & licenses — O*NET®, Anthropic Economic Index, Eloundou et al. (2023): see full notices on the Credits page

Occupation information