Artificial intelligence (AI) is reshaping nearly every avenue of oncology, but its most meaningful applications may be less visible than headlines suggest. In this interview, Dr. Matthew Kurian, a Breast Medical Oncologist at St. Elizabeth Healthcare in Kentucky, and Dr. Jasmin Hundal, a recently graduated Hematology/Oncology Fellow from the Cleveland Clinic, discuss where AI holds the greatest promise in breast cancer care, how clinicians should respond to patients who arrive with AI-generated information, and what the field still needs to get right.

Where AI Will Have the Greatest Impact

Dr. Kurian identified drug discovery as the area where he believes AI is likely to deliver its most transformative results. He noted that AI platforms are already contributing to the identification of agents now used in breast cancer and other disease types, emphasizing that AI can compress timelines that have historically taken years. "With the use of AI, we can do this in a way that will be much more automated, with much more precision as well."

Additionally, AI-enhanced mammography screening is already demonstrating measurable results. Dr. Kurian pointed to the MASAI trial, one of the largest randomized studies in screening mammography, as evidence that AI can increase sensitivity while maintaining specificity. "I think it really tells us that we can enhance our screening methods as time goes on," he said, adding that reduced radiology workload could allow more mammograms to be read more quickly.

Expanding Precision Medicine Beyond Tumor Biology

Both physicians agreed that precision oncology has historically focused on tumor biology while underutilizing other patient-level factors. Dr. Kurian described the current state of care as "one-size-fits-all based on traditional clinical pathologic variables and now genomic variables," and argued that AI can help incorporate metabolic health, autoimmune conditions, cardiovascular disease, and social determinants of health into treatment planning.

Wearable devices and continuous data collection may further expand what is possible. " This may provide a lot of information as time goes on," Dr. Kurian noted, pointing to an area he described as untapped in breast cancer care.

AI as a Clinical Copilot

As treatment options in breast oncology multiply, synthesizing rapidly evolving evidence has become increasingly difficult. Dr. Kurian framed AI not as a replacement for clinical judgment, but as a tool to support it. "I view AI more as a copilot in my mind," he said. "Those that do utilize it in a safe manner will become faster and ultimately be able to provide better care for folks."

He urged clinicians who have not yet incorporated AI into their workflow to become familiar with it regardless. "If you're not already utilizing AI within your normal workflow, I would very much become familiar with it. Even if you don't incorporate it, I think you still need to understand it, because patients are utilizing it."

Responding to Patients Who Bring AI-Generated Information

Dr. Kurian acknowledged that patients increasingly arrive at appointments having already consulted ChatGPT, Claude, or other large language models. Rather than dismissing this behavior, he encouraged clinicians to engage with it directly. "Don't be offended," he advised. "We really need to look at that information with them and see where they're gathering that information from."

He also cautioned that AI tools do not distinguish between high-quality evidence and unreliable sources. "It does not filter out an article from People versus an article from ASCO," he said. "All of that is being smushed together into one concoction that patients can get information from."

For patients using these tools, Dr. Kurian recommended careful prompting and protecting personal health information. He encouraged patients not to ask, "What treatment should I receive?" but rather "What questions should I discuss with my oncologist about the benefits and risks of treatment?" He also advised patients against entering personal health information into public AI platforms due to unresolved privacy concerns.

Looking Ahead: Multimodal AI and Sequencing

When asked what developments excite him most, Dr. Kurian pointed to multimodal AI as the frontier with the greatest potential, describing it as “the combination of how to connect clinical factors, pathologic features, radiologic features, genomics, labs, and social determinants of health all together in one picture," he said; however, no single platform has yet achieved this successfully.

He also expressed enthusiasm for AI's role in treatment sequencing, particularly in the hormone-positive metastatic breast cancer setting where options have proliferated. Digital avatar technology and simulation tools may help identify which drug combinations are worth testing and which can be set aside, accelerating the path to more effective therapies.

Ultimately, Dr. Kurian described the central challenge of oncology as predicting individual response to treatment. "How do we truly know truly who are the hyper-responders that will go on if we continue to give the drug in a way that has minimal side effects, and who are the ones who blow through their therapies immediately?" he asked. "I do think AI has the ability to be able to understand exactly who we can deescalate from therapies and who we should escalate."

Key Takeaways

AI's greatest near-term impact in breast oncology may be in drug discovery, screening enhancement, and symptom monitoring.
Precision medicine is evolving to incorporate metabolic health, comorbidities, and social determinants of health alongside tumor biology.
Clinicians should view AI as a copilot, not a replacement, and familiarize themselves with its capabilities and limitations.
Patients using AI tools benefit most from careful prompting and guidance on protecting their personal health information.
Multimodal AI that integrates clinical, genomic, radiologic, and social data represents the most promising frontier in breast oncology.

About the Speakers

Matthew Kurian, MD, is a Medical Oncologist at St. Elizabeth Healthcare and an Assistant Professor of Medicine at the University of Kentucky College of Medicine. He specializes in the treatment of breast cancer, and he is passionate about bringing academic-level care into the community setting by enrolling patients in clinical trials and by improving access, equity, and education for both patients and medical trainees.

Jasmin Hundal, MD, MS, MPH, is a second-year Hematology/Oncology Fellow at the Cleveland Clinic in Cleveland, Ohio. Previously, she completed her Internal Medicine Residency at the University of Connecticut. Dr. Hundal’s main area of interest is the overlap between cardiometabolic health and cancer, particularly for breast cancer patients and survivors. Outside of work, she enjoys traveling, cooking, and hiking.

Beyond the Headlines: AI’s Growing Role in Breast Oncology