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The AI Resilience Report helps you understand how AI is likely to impact your current or future career. Drawing on data from over 1,500 occupations, it provides a clear snapshot to support informed career decisions.
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Mostly Resilient
Last Update: 4/23/2026
Your role’s AI Resilience Score is
53.9%
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.
Most data sources align, with only minor variation. This is a well-supported result.
Contributing sources
AI Resilience Report forRadiologists
Radiologists are somewhat more resilient to AI impacts than most occupations, according to our analysis of 7 sources.
The career of a radiologist is labeled as "Mostly Resilient" because while AI tools are being developed to assist with certain tasks like analyzing scans or drafting reports, the core work still heavily relies on human skills such as judgment and empathy. AI is seen as a helpful assistant, automating repetitive or dangerous tasks, but it doesn't replace the need for radiologists to handle complex patient care and make critical decisions.
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View analysisChat with CoachLatest newsMore career infoAnalysisChatNewsMoreThis role is mostly resilient
The career of a radiologist is labeled as "Mostly Resilient" because while AI tools are being developed to assist with certain tasks like analyzing scans or drafting reports, the core work still heavily relies on human skills such as judgment and empathy. AI is seen as a helpful assistant, automating repetitive or dangerous tasks, but it doesn't replace the need for radiologists to handle complex patient care and make critical decisions.
Read full analysisAnalysis of Current AI Resilience
Radiologists
Updated Quarterly • Last Update: 2/17/2026
How is AI changing Radiologists jobs?
Right now, most radiologist tasks still need human doctors, but AI tools are being built to help. For example, AI programs can analyze things like heart stress tests. One review found machine-learning models reading stress-ECG data hit over 96% accuracy [1].
This means AI can flag problems faster, but studies say these tools still need more development before they can be safely used on real patients [1]. In general, AI in imaging today augments — not replaces — radiologists. It can automate simple steps (like measuring a tumor or drafting reports) and improve safety monitoring.
For instance, AI is being studied to track radiation exposure and alert staff to hazards [1].
Other tasks show early AI use. A “digital assistant” called MIA has patients answer health questions before an exam. Patients liked its clear communication, though they noted privacy and detail still need work [2].
In nuclear medicine, a robot named Rico has even been tested to fetch radiotracer vials, reducing staff radiation risk [3]. These examples show AI and robots can take on repetitive or dangerous parts of the job. However, tasks requiring personal judgment or care – like handling a patient’s complication during a procedure or enforcing safety rules – remain firmly human responsibilities.
Current AI for those roles is mostly experimental or theoretical [1].
Sources
How fast is AI adoption growing for Radiologists?
Radiology may use AI tools faster than some fields because hospitals are busy and radiologists are in high demand. However, adoption is cautious. Experts point out that many AI tools are still prototypes needing more testing in real clinics [1].
Setting up AI (buying software, training staff, ensuring data privacy) can be expensive, and hospitals must follow strict medical rules.
People also have concerns about AI. In trials of AI assistants, participants spoke of worries about data security and a bit of fear around new tech. For example, some early tests noted patient privacy issues and an “understandable fear” of robots taking on medical tasks [3] [2].
On the other hand, radiologists generally see AI as a useful helper rather than a threat. Many in the field emphasize that doctors will oversee AI decisions. Over time, as technology proves itself and guidelines evolve, AI is expected to become a supportive tool in radiology – improving efficiency and letting humans focus on the caring, creative parts of the job [1] [3].
Sources
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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
>=$239,200
Jobs (2024)
28,200
Growth (2024-34)
+2.7%
Annual Openings
800
Education
Doctoral or professional degree
Experience
None
Source: Bureau of Labor Statistics, Employment Projections 2024-2034
Task-Level AI Resilience Scores
AI-generated estimates of task resilience over the next 3 years
1
Interpret images using computer-aided detection or diagnosis systems.
2
Schedule examinations and assign radiologic personnel.
3
Prepare comprehensive interpretive reports of findings.
4
Implement protocols in areas such as drugs, resuscitation, emergencies, power failures, and infection control.
5
Establish or enforce standards for protection of patients or personnel.
6
Serve as an offsite teleradiologist for facilities that do not have on-site radiologists.
7
Teach nuclear medicine, diagnostic radiology, or other specialties at graduate educational level.
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.
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