Somewhat Resilient
Last Update: 8/30/2026
AI Resilience Score for Radiologists:
49.5%
Median Score
Meaningful human contribution
Measures the parts of the occupation that still require a human touch. This score averages data from up to four AI exposure datasets, focusing on the role’s resilience against automation.
Med
Long-term employer demand
Predicts the health of the job market for this role through 2034. Using Bureau of Labor Statistics data, it balances projected annual job openings (60%) with overall employment growth (40%).
Low
Sustained economic opportunity
Measures future earning potential and career flexibility. This score is a blend of total projected labor income (67%) and the role’s inherent ability to adapt to economic and technological shifts (33%).
High
This reflects the reliability of your score based on the number of data sources available for this career and how closely those sources agree on the outlook. A higher confidence means more consistent evidence from labor experts and AI models.
There are a reasonable number of sources for this result, but there is some disagreement between them.
Contributing sources
AI Resilience Report forRadiologists
$420,860 median salary•700 annual openings•SOC Code: 29-1224.00
Radiologists are somewhat less resilient to AI impacts than most occupations, according to our analysis of 8 sources.
Radiology is labeled "Somewhat Resilient" because AI is already doing a lot of the heavy lifting in this field, with tools that flag urgent scans, measure tumors, and even draft parts of reports, meaning the day-to-day workflow is genuinely changing in big ways. That said, radiologists are not being replaced because AI and humans catch different kinds of mistakes, and the strongest outcomes come from working together rather than one replacing the other.
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Radiology is labeled "Somewhat Resilient" because AI is already doing a lot of the heavy lifting in this field, with tools that flag urgent scans, measure tumors, and even draft parts of reports, meaning the day-to-day workflow is genuinely changing in big ways. That said, radiologists are not being replaced because AI and humans catch different kinds of mistakes, and the strongest outcomes come from working together rather than one replacing the other.
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Radiologists
Updated Quarterly
How is AI changing Radiologists jobs?
Good news first: AI is already changing radiology, but it's mostly working alongside radiologists rather than replacing them. Radiology is the single biggest area for medical AI — as of March 2026, 1,163 of the FDA's 1,524 cleared AI algorithms were for radiology, about 76% of all clinical AI [1], and 68 new radiology algorithms were cleared in just the first three months of 2026. These tools do things like flag urgent scans, measure tumors, and now even draft parts of the report itself.
In June 2026, the FDA gave "breakthrough" status to generative AI tools from Aidoc and Cognita that can read chest X-rays and draft findings that a human radiologist then reviews [2]. Even so, the field is growing, not shrinking — Stanford's Curtis Langlotz explains that AI and radiologists catch different kinds of errors, so the strongest results come from teamwork [3], and the number of radiologists is expected to keep expanding for decades.
Sources
How fast is AI adoption growing for Radiologists?
Adoption is moving fast because hospitals face a real staffing crunch: imaging volumes keep climbing while burnout and subspecialty shortages worsen [4], giving AI a clear business case. But it isn't a plug-and-play upgrade — the same reporting notes many organizations still struggle to prove a return on investment because AI requires workflow redesign and governance. Safety and trust also slow things down: in May 2026, the ACR released its first-ever practice parameter for imaging AI, including an "Assess-AI" framework to monitor performance over time [5].
If you're curious about this career, the human side — talking with patients, handling complications, and judging when the AI is wrong — is exactly what stays valuable.
Sources
Will AI replace Radiologists?
Not entirely. We think AI will take over some tasks, but not the whole job.
Radiology is already one of the most AI-saturated fields in medicine. As of early 2026, about 76% of all FDA-cleared clinical AI algorithms were built for radiology [1], and new tools can now draft report findings for a human radiologist to review [2]. That is real automation of real work, and it is happening now. Our 49.5% AI Resilience Score reflects that honestly.
But the job is not disappearing, it is shifting. Research shows that AI and radiologists catch different kinds of errors, which means the best outcomes come from working together rather than from AI working alone [3]. The human tasks that remain, like talking with patients, catching the cases where the AI is wrong, and making judgment calls in complicated situations, are exactly the parts that are hardest to automate.
The economic picture is also worth noting. Wages and career flexibility score well for this field, even as long-term employer demand faces pressure. Hospitals are adopting AI partly because imaging volumes keep climbing and staffing is stretched [4], which means radiologists who learn to work with these tools stay relevant. The role changes. The need for skilled humans in it does not disappear.
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Latest AI news for Radiologists
These articles highlight how AI will shape the future of radiology careers. For instance, the analysis shows a potential 33% reduction in the need for radiologists due to AI advancements, emphasizing the importance of adaptability. However, AI tools can significantly enhance diagnosis speed and accuracy, allowing radiologists to focus on complex cases. Embracing AI can lead to improved patient outcomes and job satisfaction, positioning future radiologists as essential team members in a tech-driven healthcare landscape. Understanding AI's role is crucial for building resilience in this evolving field.
Automation, not replacement: the true promise of AI in radiology
healthcare-in-europe.com • 7/2/2026
Will artificial intelligence (AI) render radiologists obsolete? What seemed a likely scenario only nine years ago, has now given way to a...
Radiology in the age of AI
rochesterbeacon.com • 5/28/2026
Use of artificial intelligence can accelerate patient diagnoses in a health system under stress, but it's not risk-free. Radiologists remain...
Between automation and alienation: rethinking AI’s role in radiologist well-being
link.springer.com • 3/20/2026
Radiology has the highest degree of AI exposure across clinical specialties. As of late 2025, approximately 80% of FDA-cleared AI-enabled...
What effect will AI have on the radiologist workforce?
www.auntminnie.com • 1/9/2026
Overall, the analysis shows that AI will likely cause an up to 33% reduction in the need for radiologists over the next five years, with a range...
AI in radiology: three keys to real-world impact
www.philips.com • 11/20/2025
Beyond segmentation, AI is transforming how imaging data is interpreted and acted upon. By analyzing vast volumes of medical imaging data in seconds, AI tools...
More Career Info
Career: Radiologists
They help diagnose medical issues by examining X-rays and scans, then work with doctors to decide on the best treatment for patients.
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Employment & Wage Data
Median Wage
$420,860
Jobs (2025)
28,700
Growth (2025-35)
+3.4%
Annual Openings
700
Education
Doctoral or professional degree
Experience
None
Source: Bureau of Labor Statistics, Employment Projections 2025-2035
Task-Level AI Resilience Scores
AI-generated estimates of task resilience over the next 3 years
1
Perform interventional procedures such as image-guided biopsy, percutaneous transluminal angioplasty, transhepatic biliary drainage, or nephrostomy catheter placement.
2
Recognize or treat complications during and after procedures, including blood pressure problems, pain, oversedation, or bleeding.
3
Administer radioisotopes to clinical patients or research subjects.
4
Establish or enforce standards for protection of patients or personnel.
5
Establish and enforce radiation protection standards for patients and staff.
6
Participate in continuing education activities to maintain and develop expertise.
7
Participate in quality improvement activities including discussions of areas where risk of error is high.
Tasks are ranked by their AI resilience, with the most resilient tasks shown first. Core tasks are essential functions of this occupation, while supplemental tasks provide additional context.
