How Has the Use of AI and Technology Impacted Healthcare Today? Opportunities and Challenges in the Digital Transformation of Cardiovascular Care

Anishka Jain, high school student, authored a response to the question above for a recent course in Artificial Intelligence.  We have edited it together for our Linked In audience, but the concepts and opinions remain hers and reflective of the next generation’s reaction to AI in current and future systems of healthcare.  

Artificial intelligence (AI) and digital technology are reshaping healthcare at a pace few could have imagined. For the field of cardiology in particular, these innovations offer transformative potential: improving clinical efficiency, advancing early detection, enabling more personalized treatments, and redefining how care is delivered.

One of the most compelling opportunities AI presents is the ability to detect disease earlier and more precisely. Algorithms trained on large datasets can identify subtle patterns in imaging, ECGs, genomics, and wearable sensor data—patterns that might otherwise go unnoticed. In oncology, AI tools have already demonstrated value in identifying cancer cells in biopsies and predicting treatment response. In cardiovascular care, AI-enhanced electrocardiography and imaging platforms are beginning to identify subclinical disease, such as early-stage left ventricular dysfunction, years before symptoms appear. These insights can support timely interventions and ultimately improve outcomes.

AI also holds promise in tailoring therapies to individual patients. By integrating genetic, phenotypic, and lifestyle data, AI can support precision medicine strategies, including selecting optimal drug regimens or anticipating adverse reactions. This kind of tailored care aligns with the next generation’s expectations of patient-centered, value-based care.

Beyond clinical decision-making, AI offers significant improvements in operational efficiency. From automating prior authorizations to optimizing patient flow and appointment scheduling, AI can reduce administrative burdens. At my own physician’s office, I overheard a conversation where a doctor explained how AI tools would soon generate visit notes by transcribing recorded conversations. This kind of “ambient documentation” could give clinicians more time to connect with patients, mitigating burnout and enhancing satisfaction on both sides of the care experience. (Anishka is absolutely right, the adoption of ambient documentation is one of the early AI success stories). 

However, these exciting advancements come with real challenges—scientific, ethical, legal, and logistical—that must be addressed before AI can be responsibly and widely adopted.

One critical concern is algorithmic bias. If the data used to train AI systems do not include adequate representation of all demographic groups, these systems may reinforce existing healthcare disparities. For example, AI that performs well in detecting heart failure in one population may not perform as well in a different one. 

There are also regulatory and legal questions to navigate. If AI contributes to a diagnostic error or adverse outcome, who is held accountable—the clinician, the software developer, or the healthcare institution? Without clear guidance, clinicians may be hesitant to fully integrate AI tools into practice, especially if malpractice liability remains ambiguous. 

Ethically, we must ask how much autonomy should be granted to AI in decision-making. Should an AI tool be allowed to recommend end-of-life interventions without physician override? (I love that these are the questions a high school student already knows to ask - and from my (Bhatt) perspective, the answer is no, the clinician will always understand context, nuance, edge cases and human values in a way that is nearly impossible for a non-sentient system to mimic).  What happens if AI recommendations conflict with a clinician’s judgment—or a patient’s values? As digital tools become more embedded in care delivery, we will need thoughtful frameworks to balance automation with the human aspects of healing.

Despite these concerns, the future of AI in healthcare—and especially in cardiovascular medicine—is bright. The ACC has emphasized the need for a proactive, clinician-led approach to AI integration, ensuring that digital health tools augment, rather than replace, the vital work of the healthcare team.

As someone deeply interested in the intersection of medicine and technology, I am optimistic that when designed thoughtfully and deployed equitably, AI can be a powerful partner to clinicians. By continuing to emphasize trust, transparency, and team-based innovation, we can harness AI not just to improve care, but to reimagine what’s possible in healthcare.