Six reasons AI is not ready to replace radiologists

Will AI Replace Radiologists or Make Them More Efficient?

Artificial Intelligence (AI) is playing an increasing role in healthcare, especially in radiology. While some believe AI can perform just as well or even better than human radiologists, real-world use of these technologies remains limited.

In this post, we explore why AI isn't ready to replace radiologists, how it can support them, and what the future may hold for this essential medical field.

Some Say AI Can Perform Better Than Radiologists, But It's Not Being Used Widely in Radiology Practices

AI tools have shown promise in detecting certain conditions like colon cancer or strokes by analyzing medical images. These tools are often trained on massive datasets of X-rays and scans to identify patterns and suggest possible diagnoses.

However, despite more than 700 FDA-approved AI algorithms most for radiology only around 2% of radiology practices in the U.S. have adopted them.

1. No Wide Adoption of AI

One reason for low adoption is the “culture of medicine.” Radiologists and healthcare systems are cautious when it comes to changing well-established workflows, especially when it involves patient safety. Even in Europe, where the need for faster radiological review is more urgent due to staffing shortages, the use of fully automated tools is just beginning. Most AI tools still require a human radiologist to make the final decision.

2. Scepticism

Radiologists are skeptical of AI for several reasons:

  • Many tools lack real world testing.

  • It's often unclear how the algorithms work.

  • The demographics used in training datasets may not match real patient populations.

As Dr. Curtis Langlotz from Stanford University notes, radiologists are hesitant to trust AI tools if they’re unsure how or where the tools were tested.

3. Looking Over Your Shoulder

Even when AI is used, many radiologists find it more of a distraction than a help like someone pointing out everything on the road while you're trying to drive. This constant “second opinion” can slow them down instead of saving time, especially if they still need to double-check every result.

As Dr. Saurabh Jha puts it, “If you want to help me drive, then take over the driving so I can sit back and relax.” Until AI tools are fully reliable, radiologists will have to keep monitoring AI outputs closely.

4. Radiologist Is a Multifaceted Job

AI currently focuses on pattern recognition, but radiologists do much more. They:

  • Interpret findings in a clinical context.

  • Recommend further tests.

  • Communicate with patients and doctors.

  • Perform procedures like biopsies.

For example, a chest X-ray might show a lung opacity. AI may detect it, but it won’t determine if it’s due to infection, fluid, hemorrhage, or another cause especially without considering lab tests and medical history. Only a trained radiologist can do that.

5. AI’s Accuracy Is Still a Problem

AI can miss or misinterpret critical findings. In one study, AI correctly diagnosed only 27.8% of pediatric cases. In another, using AI instead of a second human reviewer for mammograms led to a 20% increase in cancer detection but also carried legal and safety concerns.

AI may also “hallucinate” (make up information) or rely too heavily on text input rather than images, especially in newer models like large vision-language models.

6. Radiological Datasets Are Hard to Access

Developing reliable AI models requires large, diverse, and high-quality datasets. However, medical imaging data is often difficult to access due to privacy regulations and institutional restrictions. Without access to varied and representative data, AI models may not perform well across different patient populations.

What Will Radiologists of the Future Look Like?

Future radiologists will likely work alongside AI, not be replaced by it. AI can assist in:

  • Reviewing normal scans.

  • Acting as a second opinion.

  • Speeding up workflows.

  • Reducing burnout.

Radiologists will remain in charge, using AI to make better and faster decisions not to replace human reasoning but to enhance it.

As one expert put it, AI in radiology may work like autopilot on airplanes: helpful for navigation but still requiring a skilled pilot.

A Long Road Ahead

AI is improving, but there’s still a long way to go before it can function independently in radiology. Legal, ethical, and technological barriers must be addressed before AI can take on a larger role.

Until then, radiologists will continue to lead diagnostics and patient care just with better tools at their side.

FAQs About Radiology and AI

What does a radiologist do? A radiologist is a doctor who interprets medical images to help diagnose and treat conditions.

Can AI read scans better than humans? Sometimes, for specific conditions but AI still needs human oversight and cannot replace full clinical reasoning.

Why isn’t AI used more in radiology? Concerns include accuracy, lack of transparency, and uncertainty about how AI tools were tested.

Will AI reduce the need for radiologists? AI will likely support radiologists by handling simple or routine tasks, but doctors will still be essential for diagnosis and treatment decisions.

Can patients trust AI in radiology? AI is an aid, not a replacement. Patients can trust results when AI is used with a radiologist's expertise.

AI holds great promise in radiology, but it's not ready to replace radiologists. Instead, it offers tools that can improve speed, accuracy, and consistency when used wisely. The future of radiology is not human or machine it’s human plus machine.


Published 7th May 2025


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