Takeover Tracker

The AI Anxiety Index

Media hype vs. actual job displacement risk. We cross-referenced 1,472 tagged article-occupation mentions from 124 news sources with our task-level AI risk scores and BLS employment data.

Key finding: The media fixates on software developers (76 mentions, 35% risk), but occupations like office clerks and medical records technicians — representing millions more workers — face higher actual displacement risk with a fraction of the coverage.

How to read this chart: Each bubble is an occupation. Horizontal position = AI displacement risk (higher = more at risk). Vertical position = media attention (higher = more coverage). Bubble size = number of workers employed (BLS data). Color = salary band.

The dashed lines show the median — jobs in the top-left are overhyped (lots of coverage, lower risk), while jobs in the bottom-right are underreported (high risk, little coverage).

< $50k
$50k–$80k
$80k–$120k
$120k+
No data
Lower RiskHigher Risk

Most Overhyped

Jobs getting disproportionate media attention relative to their actual risk score.

Software Developers, Applications
76 mentions35.6% risk
Computer Programmers
71 mentions34.4% risk
Lawyers
43 mentions25.8% risk

Most Underreported

Jobs with high actual risk but relatively little media coverage.

Bookkeeping, Accounting, and Auditing Clerks
11 mentions55.7% risk
Medical Secretaries
9 mentions52.4% risk
Insurance Claims Clerks
5 mentions49.3% risk
1,472
Articles Analyzed
relevant, tagged articles
141
Occupations Tracked
with 3+ mentions
66.5M
Workers Represented
BLS employment data
34.4%
Avg Risk Score
across tracked jobs

Methodology

Media mentions are counted from articles collected by our news pipeline across 124 sources (Bloomberg, TechCrunch, WSJ, healthcare and legal trade press, etc.), filtered for relevance to AI and workforce impact, then tagged to O*NET occupations using hybrid keyword + Gemini classification.

Risk scores are computed from individual task-level automation assessments for each occupation, discounted by protective factors (social intelligence, regulatory barriers, physical dexterity, etc.). See our full methodology.

Employment and salary data from the U.S. Bureau of Labor Statistics Occupational Employment and Wage Statistics (OEWS) program.

Only occupations with 3+ article mentions are shown. Bubble size uses BLS employment counts where available; occupations without BLS data use a default size.