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High RiskHealthcare
Accelerating

Radiologist

AI diagnostic imaging systems (Google DeepMind, Enlitic) now match or exceed radiologists in detecting cancer, fractures, and anomalies in X-rays, MRIs, and CT scans. The image-reading portion is increasingly automated.

38K current workers
Major disruption: By 2030
68%Automation Risk

High Risk

Automation Risk Trajectory

Historical progression and projected automation risk for Radiologists through 2030

What AI Is Replacing

  • Routine scan reading and flagging
  • Normal/abnormal triage
  • Standard report generation
  • Pattern recognition in imaging

What Humans Still Own

  • Complex case consultation
  • Treatment planning decisions
  • Patient communication
  • Rare disease diagnosis

Top Skills to Develop Now

AI radiology toolsInterventional radiologyClinical AI validation
Sources: NEJM (2022), Nature Medicine (2023)

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