Ai Exposure By Major (2026 stats)
TL;DR
Snapshot of 6 labeled rows from our College Scorecard–based extract for this topic. Values run from about 8 (Healthcare) to about 52 (Business). See the table for every row and the downloads for the full machine-readable file.
Key Facts
- 6 rows in the on-page table (same universe as the CSV download).
- Minimum observed value: 8 (Healthcare).
- Maximum observed value: 52 (Business).
- Source universe and cohort notes match our methodology and Scorecard refresh dated in the page header.
Download the data
Downloads reflect the processed dataset used to generate this page’s charts and tables.
At a glance
Largest values in this extract
Bar length scales to the maximum value among the top rows shown. For ratios where lower is better, read the table and methodology—high bars here still mean “larger number in the file,” not “better outcome.”
Bars show the five largest numeric values in the processed CSV for this page. Interpret direction (higher vs lower is better) using the column name and methodology links.
Full results
Every row in this dataset appears in the table below. Use the downloads for machine-readable JSON or CSV.
| label | AI Exposure (%) |
|---|---|
| Computer Science | 45 |
| Engineering | 38 |
| Business | 52 |
| Healthcare | 8 |
| Education | 15 |
| Liberal Arts | 35 |
Analysis & insights
The table lists all 6 rows for Ai Exposure By Major (2026 stats). Use the at-a-glance bars for a quick sense of spread; use the table when you need exact labels and every row in one view.
The largest values in this file include Business, Computer Science, Engineering. Always pair headline numbers with the methodology page and with field definitions in College Scorecard ROI methodology before citing them in external work. Suppression rules and cohort windows can move medians when the Department refreshes underlying files.
FAQ
AI exposure & workforce change
What does “AI exposure” for a major typically mean?
Research-style indexes estimate how task content in occupations overlaps with current AI capabilities. They are directional signals, not forecasts that a job will disappear.
Why might exposure scores disagree across studies?
Teams differ in taxonomy mapping, data vintages, and whether they weight tasks equally. Compare methodologies before contrasting headline percentages.
How should students use these metrics?
Pair exposure indicators with licensure, human-skill demand, and regional hiring data—use them to prompt questions, not to avoid entire fields without evidence.
Using this page
What does this page cover on “Ai Exposure By Major”?
Data and analysis for ai exposure by major
Which sources power the numbers here?
Figures draw on College Scorecard, and Census ACS. Use Data Sources for exact tables, APIs, and methodology notes.
Why might these figures differ from another chart or headline?
If another outlet shows a different total, check whether the cohort (all borrowers vs undergraduates only), academic year, and data source match. Mixing definitions is the most common reason charts appear to conflict.
How often is this page updated?
We refresh when upstream federal releases change and the site rebuild ships new CSV/JSON extracts. The Last updated line points to the latest editorial pass on this HTML.
Data Sources
- College Scorecard - U.S. Department of Education
- Institutional characteristics, costs, completion rates, and enrollment data
- Data year: 2024
- Source: collegescorecard.ed.gov
- Census ACS - U.S. Census Bureau
- Demographic and workforce data
- Data year: 2023
- Source: census.gov