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The Effect of AI on the Radiologist Workforce: A Task-Based Analysis.
1Professor of Radiology, Medicine, and Biomedical Data Science, Senior Associate Vice Provost for Research, Senior Fellow, Institute for Human-Centered Artificial Intelligence, Stanford University.
Medrxiv : the Preprint Server for Health Sciences
|January 2, 2026
Summary
Artificial intelligence (AI) may reduce radiologist hours by 33% in five years, primarily impacting report drafting and study delegation. Despite this, job loss is unlikely due to increasing imaging volumes.
Area of Science:
- Radiology
- Artificial Intelligence
- Workforce Analysis
Background:
- The impact of artificial intelligence (AI) on the radiology workforce is debated.
- Sufficient evidence now exists for quantitative analysis of AI's effects on radiologists.
Purpose of the Study:
- To develop a quantitative, task-based model predicting AI's impact on the radiology workforce.
- Utilize the best available evidence for accurate predictions.
Main Methods:
- Literature review to identify radiologist tasks and AI applications affecting them.
- Estimation of AI's impact on each task over a 5-year horizon using published data and expert judgment.
Main Results:
- The model projects a 33% reduction in radiologist work hours within 5 years (14%-49% range).
- Key impacts identified in radiology report drafting across all modalities and study delegation for radiography and mammography.
Conclusions:
- AI applications are expected to significantly decrease radiologist hours.
- Radiologist job loss is unlikely in the near future due to static workforce numbers and growing imaging volumes.
