AI in the Healthcare Industry: Interview Highlights

Dr. Bernardo Perez-Villa, Senior Innovations Engagement Partner at the Cleveland Clinic, shares grounded insights into the true drivers of successful innovation in healthcare. Drawing on his global background in biodesign and commercialization, he discusses the real-world challenges of bringing AI technologies from concept to clinic. From assessing unmet clinical needs to understanding payer dynamics and regulatory bottlenecks, Perez-Villa emphasizes frameworks that distinguish viable solutions from hype. Hosted by Dr. Sanjay Juneja, this conversation unpacks the realities of product-market fit, digital health business models, and how to responsibly scale innovation without compromising on patient safety or financial sustainability.

Rajeev Ronanki, CEO of Lyric, explores how the FDA’s evolving stance on artificial intelligence could reshape the future of drug development and healthcare delivery. In this compelling exchange, he unpacks the promise of Elsa—a tech-forward initiative by the FDA—and why it signals a paradigm shift from bureaucratic bottlenecks to data-driven decisions. Rajeev emphasizes how AI can accelerate therapeutic innovation, reduce inefficiencies, and make regulatory processes more transparent and predictive. His insights speak directly to healthcare executives, clinicians, and digital health innovators eager to understand federal AI adoption and its implications for clinical practice and pharma R&D.

In this in-depth interview, Rajiv Haravu, SVP of Product Management at IMO Health, explores the complexities of healthcare data normalization and its vital role in improving data quality across clinical systems. Haravu outlines the challenges of variability in documentation, from lab results to unstructured physician notes, and shares how IMO’s Precision Normalize and Precision Sets products address these issues. He discusses the interplay between structured and unstructured data, the role of terminology management, and the importance of adapting to evolving definitions. With insights on AI and natural language processing, Haravu reveals how IMO is integrating advanced tools while maintaining precision in clinical coding—empowering healthcare organizations to unlock the full potential of their data.

In this full interview, Jason Alan Snyder, Futurologist, Inventor, and Technologist, explores the urgent issues of AI in healthcare data, from privacy and ethics to ownership and monetization. Snyder highlights how digital twins—virtual representations of individuals built from lab results, biometrics, genomes, and behaviors—are being used without consent or compensation. He warns of the dangers of poor data quality, decay, and fragmentation, which lead to flawed AI-driven medical decisions. Snyder envisions a future where individuals own and control their health data, benefiting from AI’s potential while avoiding exploitation. The conversation offers a roadmap for building ethical, transparent, and patient-centered AI systems in healthcare.

In this full interview, Dr. Alister Martin, CEO of A Healthier Democracy and Assistant Professor at Harvard Medical School, shares a powerful vision for how AI can both lower healthcare costs and expand access for underserved communities. Martin discusses the concept of 'money as medicine,' showing how targeted financial investments in social determinants of health can prevent costly emergency care. He explores AI's role in identifying high-need patients, optimizing care coordination, and connecting people to the right resources before medical crises occur. This conversation blends clinical insight with public health strategy, offering actionable ideas for leaders seeking to align cost savings with better health outcomes.

In this full interview, Pelu Tran, CEO of Ferrum Health, explores the complex realities of AI governance in healthcare and how hospitals can navigate the tension between innovation, security, and regulatory compliance. Tran discusses the technical, clinical, and business barriers to AI adoption, from vendor-cloud mistrust to the high costs of deploying and maintaining AI solutions. He explains why governance platforms are essential for ensuring AI models perform safely across diverse patient populations, and how middleware infrastructure can help hospitals integrate and manage AI at scale. This conversation offers actionable insights for leaders facing AI adoption bottlenecks.

In this in-depth interview, Krish Ramadurai, Partner at AIX Ventures, shares his perspective on what's real and what's overhyped in AI development in healthcare. He explains the importance of domain expertise, the role of clinical workflow automation, and why business models must align with enterprise value creation. Ramadurai also discusses AI’s role in drug development, the challenge of regulatory compliance, and the strategic investments that drive sustainable innovation. His insights provide a roadmap for healthcare leaders navigating AI investment opportunities.

Dr. Nigam Shah, Co-Founder of Atropos Health and Chief Data Scientist at Stanford Health Care, explores how AI implementation in healthcare must shift from experimental models to scalable, sustainable solutions. Drawing on analogies from automotive safety, Dr. Shah emphasizes creating ecosystems for local validation, continuous monitoring, and defining clear context for use. He discusses how AI can increase healthcare access, avoid the 'Turing trap' of replacing humans for tasks they already do, and instead focus on reducing unnecessary visits and expanding provider capacity. With insights into AI healthcare data usage and frameworks for responsible AI lifecycle management, this conversation offers a roadmap for healthcare leaders to deploy AI effectively.

In this wide-ranging interview, Bob Battista explains how AI can speed drug repurposing—if data can flow across today’s regulatory and commercial silos. He points to untapped knowledge inside pharmaceutical call centers, patient-reported outcomes, and physician off‑label use that rarely reaches researchers. Battista argues that safe-harbor policies for pharmaceutical data sharing would unlock thousands of potential indications hiding in plain sight, while AI organizes mechanistic and clinical evidence for decision makers. The conversation also explores living clinical guidelines, earlier diagnostic staging, and the economics that slow evidence adoption. For healthcare leaders, the message is clear: pair modern analytics with governance reform to expand access, improve outcomes, and strengthen patient empowerment in healthcare.

In this in-depth interview, Dr. Debra Patt, Executive Vice President of Texas Oncology and Chair of ASCO’s Artificial Intelligence Task Force, shares her insights on how AI is revolutionizing cancer care. She discusses real-world applications, from AI-enhanced diagnostics to ambient AI for reducing physician burnout, and explores how AI can improve patient outcomes, streamline administrative tasks, and reduce healthcare costs. Dr. Patt also highlights the promise of AI in drug discovery, clinical trial design, and personalized medicine.