ANTHROPIC
Labor market impacts of AI: A new measure and early evidence
We introduce a new measure of AI displacement risk, observed exposure, combining theoretical LLM capability and real-world usage data. While AI is far from reaching its full theoretical capability, occupations with higher observed exposure are projected to grow less. We observe no systematic increase in unemployment for highly exposed workers since late 2022, but suggestive evidence points to a slowdown in hiring of younger workers in exposed occupations.
Executive Summary: Key AI-Driven Labor Insights
Our research reveals critical trends in AI's interaction with the labor market, offering insights into exposure, growth, and demographic impacts.
0%
Actual AI Task Coverage (Computer & Math)
0%
Job Growth Drop per 10% AI Exposure
0%
Younger Worker Hiring Rate Decrease
Deep Analysis & Enterprise Applications
Select a topic to dive deeper, then explore the specific findings from the research, rebuilt as interactive, enterprise-focused modules.
Understanding AI's Reach and Impact
Our analysis begins by defining and measuring AI exposure, contrasting theoretical capabilities with observed real-world application across various occupations.
Measuring Observed AI Exposure
O*NET Database (Tasks)
→
Anthropic Usage Data
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Eloundou et al. (Theoretical Exposure)
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Observed Exposure (Occupations)
33%
Actual AI Task Coverage in Computer & Math (vs. 94% theoretical)
| Occupation | Observed Exposure | Leading Automated Task |
|---|---|---|
| Computer programmers | 74.5% | Write, update, and maintain software programs |
| Customer service representatives | 70.1% | Confer with customers to provide info, take orders, handle complaints |
| Data entry keyers | 67.1% | Read source documents and enter data into systems |
| Medical record specialists | 66.7% | Compile, abstract, and code patient data |
| Market research analysts and marketing specialists | 64.8% | Prepare reports of findings, illustrating data graphically and translating complex findings into written text |
AI Exposure and Worker Demographics
Explore how AI exposure correlates with various demographic characteristics, including age, gender, ethnicity, education, and wage.
| Characteristic | No Exposure | Top Quartile | Difference |
|---|---|---|---|
| AI coverage (%) | 0.0% | 38.8% | +38.8 pp |
| Age | 41.0 | 42.9 | +1.9 |
| Female | 38.8% | 54.4% | +15.5 pp |
| Hispanic | 24.8% | 13.8% | -11.0 pp |
| White, non-Hispanic | 54.5% | 65.1% | +10.6 pp |
| Black, non-Hispanic | 13.2% | 9.7% | -3.5 pp |
| Asian, non-Hispanic | 4.7% | 9.1% | +4.4 pp |
| Married | 44.6% | 54.9% | +10.4 pp |
| Less than HS | 13.2% | 2.3% | -10.9 pp |
| HS diploma | 38.9% | 17.7% | -21.2 pp |
| Some college / assoc. | 30.0% | 25.5% | -4.6 pp |
| Bachelor's degree | 13.3% | 37.1% | +23.8 pp |
| Graduate degree | 4.5% | 17.4% | +12.8 pp |
| Hours / week | 37.5 | 38.7 | +1.2 |
| Hourly wage ($) | $22.23 | $32.69 | +$10.45 |
| Union member | 11.7% | 5.3% | -6.4 pp |
| Observations | 42,546 | 32,301 |
AI's Impact on Job Growth and Workforce Dynamics
Examine the observable effects of AI on projected job growth, unemployment rates, and hiring trends, particularly for younger workers.
-0.6%
Job growth drop per 10% increase in AI exposure (BLS 2024-2034)
Unemployment Trends: Limited Impact So Far
No Systematic Increase in Unemployment for Highly Exposed Workers: Despite the rise of AI, our analysis of Current Population Survey data since late 2022 shows no significant increase in unemployment rates for highly exposed workers. While individual shifts may occur, aggregate data does not yet indicate widespread job displacement. However, this framework is designed to detect such shifts as they emerge.
-14%
Drop in job finding rate for young workers (22-25) in exposed occupations post-ChatGPT
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