Put the data in context.
A press and research kit for citing the Replaceability Index accurately. Find the dataset, understand its limits, and get in touch.
A task-based view of changing work.
The Replaceability Index is an independent project from GmanCreations, founded by Shawn Geeman. It provides relative AI exposure scores for 709 US occupations, a free personal assessment, and optional paid reports.
Occupation scores belong to this project's model. O*NET, BLS, OECD, and the researchers we cite do not endorse the product or issue these personal scores.
Read the methodology and limitations ↗Inspect the numbers.
Download the public occupation dataset under CC BY 4.0. Cite the Index and link to the methodology when using its scores. Dates and source context matter: this is not a live labor-market feed.
| Occupation | Exposure /100 |
|---|---|
| Registered Nurses | 6 |
| Electricians | 12 |
| Software Developers | 32 |
| Graphic Designers | 58 |
| Accountants and Auditors | 69 |
Report exposure, not certainty.
Suggested description: “The Replaceability Index models relative task exposure to AI on a 0 to 100 scale. A score is not the probability that a worker will lose their job.”
Avoid converting scores into a share of jobs eliminated, a deadline for automation, or a promise about earnings. The Index does not establish those outcomes.
For a specific occupation, its profile includes citation tools. For general coverage, cite “The Replaceability Index, GmanCreations,” include your access date, and link to replaceabilityindex.com/about.
Explore the research library ↗Questions, corrections, interviews.
Contact hi@replaceabilityindex.com. Include your outlet, topic, and deadline. If a number looks wrong, send the page and the source you are comparing it with.