Radiology: AI Enhances, Not Replaces, Workers, Despite Earlier Doomsday Projections

AI integration in radiology demonstrates how automation can augment, rather than replace, human workers. The field, rich with digitized imaging data, uses AI to prioritize scans, enhance image quality, and assist in report summarization. Despite early warnings, such as a 2016 claim AI would soon outperform radiologists, current practice emphasizes a "second set of eyes" reviewed by experts. Regulatory approval for medical AI can take about eight years, but over 1,357 AI-enabled devices are FDA-approved, with 1,041 designated for radiology. Despite concerns over bias and overreliance, the U.S. Bureau of Labor Statistics projects radiology employment to grow 5% from 2024 to 2034, outpacing the 3% average. Demand is driven by an aging population and expanded medical imaging use, not displacement.