The Replaceability Index

One score. Wider context.

AI job exposure data / 709 occupations

Explore AI task exposure, pay, and projected growth across occupations. The dataset is public; interactive charts are included with The Index subscription.

Read the data in context.

The score is a relative index of task exposure from 0 to 100. It is not a percentage chance of losing a job or a forecast of layoffs. Individual tasks, employer choices, adoption, and regulation all matter.

Pay and projected growth add context. Neither is a personal forecast or proof of an AI effect.

The source snapshot does not record the wage-survey year or employment-projection window. Check the original BLS release before treating these figures as current. Editorial changes and export dates do not establish data freshness.

Explore the relationships.

The interactive chart collection is part of The Index. Public occupation pages and the downloadable dataset remain available for reference.

Compare plans · Open the occupation data table

Keep the evidence close.

Use the public export to inspect values. Cite the Index for its exposure estimates and original sources for their underlying research. A comparison between model outputs is not predictive validation.

Download the occupation dataset as CSV · Read the dataset guide · Sources and limitations

Sources and methodology

The score is a relative index of task exposure from 0 to 100. It is not a percentage chance of losing a job or a forecast of layoffs. Individual tasks, employer choices, adoption, and regulation all matter.

The Index uses stored BLS-based occupation data. O*NET, OECD capability indicators, and task-exposure research are contextual references. The derivation of the stored occupation scores is not reproducibly documented in the published dataset.

The source snapshot does not record the wage-survey year or employment-projection window. Check the original BLS release before treating these figures as current. Editorial changes and export dates do not establish data freshness.

Read the methodology and limitations