In this episode of the AI in Healthcare and Life Sciences podcast, host Matthew DeMello speaks with John-Clark Levin, Fellow at the Yorktown Institute and researcher at Kurzweil Research, about the intersection of U.S. politics, AI development, and biosecurity. Levin outlines why the coming years may prove decisive for artificial general intelligence (AGI) and how political volatility under the current administration could directly impact AI safety and regulation. He explains the unique risks of authoritarian tendencies in shaping AI policy, particularly when it comes to epistemics—how governments decide what’s true and which advisors they trust. Want to share your AI adoption story with executive peers? Click emerj.com/ex2 for more information and to be a potential future guest on Emerj’s flagship’ AI in Business’ podcast! If you’ve enjoyed or benefited from some of the insights of this episode, consider leaving us a five-star review on Apple Podcasts, and let us know what you learned, found helpful, or liked most about this show!

Today’s guest is John-Clark Levin, Research Lead at Kurzweil Technologies. Kurzweil Technologies, Inc. (KTI) is a research and development company developing and marketing technologies in pattern recognition and artificial intelligence. In this episode, John-Clark unpacks the challenges of deploying AI in healthcare, focusing on reliability, risk tolerance, and the gap between model performance and real-world trust. He explores why even small error rates can derail adoption in high-stakes settings and how legal, institutional, and educational barriers often slow progress more than the technology itself. Want to share your AI adoption story with executive peers? Click emerj.com/ex2 for more information and to be a potential future guest on Emerj’s flagship’ AI in Business’ podcast! If you’ve enjoyed or benefited from some of the insights of this episode, consider leaving us a five-star review on Apple Podcasts, and let us know what you learned, found helpful, or liked most about this show!

Today’s guest is Francesco Tisiot, Field CTO at Aiven. Aiven provides fully managed, open-source data infrastructure on all major clouds. Their platform enables organizations to scale quickly, securely, and cost-effectively — freeing teams to focus on delivering AI applications and business outcomes. Francesco returns to the program to share a pragmatic perspective on AI adoption in highly regulated industries. He outlines how generative AI can eliminate repetitive tasks, accelerate decision-making, and improve employee engagement — without compromising trust or compliance. From co-pilot interfaces to human-in-the-loop models, Francesco emphasizes where AI can provide value while keeping clinicians and analysts at the center of critical decisions. The conversation also covers the pitfalls of scaling AI too quickly. Francesco breaks down the technical and economic challenges that arise when moving from small pilots to enterprise-wide deployment. He explains why foundational data architecture, clearly defined KPIs, and regulatory foresight are essential for sustainable adoption. Want to share your AI adoption story with executive peers? Click emerj.com/ex2 for more information and to be a potential future guest on Emerj’s flagship’ AI in Business’ podcast! If you’ve enjoyed or benefited from some of the insights of this episode, consider leaving us a five-star review on Apple Podcasts, and let us know what you learned, found helpful, or liked most about this show!

Today’s guest is Francesco Tisiot, Field CTO at Aiven. Aiven provides fully managed, open-source data infrastructure on all major clouds. Their platform enables organizations to scale quickly, securely, and cost-effectively—freeing teams to focus on delivering AI applications and business outcomes. Francesco joins Emerj Senior Editor Matthew DeMello on today’s show to discuss what it takes to responsibly adopt AI in highly regulated sectors like life sciences. Francesco shares insights from working across verticals and explains why starting with a clear understanding of data boundaries is more critical than ever. Throughout the conversation, he outlines the three most important data infrastructure steps companies must take before deploying AI solutions at scale and how organizations can avoid the costly mistake of treating AI as a plug-and-play solution. Want to share your AI adoption story with executive peers? Click emerj.com/expert2 for more information and to be a potential future guest on the ‘AI in Business’ podcast! If you’ve enjoyed or benefited from some of the insights of this episode, consider leaving us a five-star review on Apple Podcasts, and let us know what you learned, found helpful, or liked most about this show!

Today’s guest is Rhett Alden, Chief Technology Officer at Elsevier. Elsevier is a global leader in information analytics and academic publishing, providing trusted scientific, technical, and medical content for researchers, clinicians, and professionals. Rhett returns to the podcast to explore how AI is reshaping healthcare education by bridging the gap between emerging technologies and traditional training methods. In this episode, Rhett shares how Elsevier is applying generative AI to enhance procedural training for healthcare students and professionals while emphasizing the continued importance of human-led instruction for conceptual understanding, ethical decision-making, and patient empathy. He also discusses the increasing adoption of AI across healthcare education institutions and the need for thoughtful implementation models that preserve quality and support human connection in learning environments. Want to share your AI adoption story with executive peers? Click emerj.com/ex2 for more information and to be a potential future guest on Emerj’s flagship’ AI in Business’ podcast!

Today’s guest is Rhett Alden, Chief Technology Officer at Elsevier. Elsevier is a global leader in information analytics and academic publishing, providing trusted scientific, technical, and medical content for researchers, clinicians, and professionals. Rhett joins us on today’s show to discuss how Elsevier is tackling hallucinations in AI frameworks to deliver reliable, peer-reviewed medical and scientific information. Alden explains how retrieval-augmented generation (RAG) models differ from large language models (LLMs), ensuring that AI-generated responses are grounded in verifiable, high-quality sources. He shares how Elsevier integrates precision, completeness, bias mitigation, and harm reduction into its evaluation framework, providing transparency for clinicians who depend on AI-assisted insights. If you’ve enjoyed or benefited from some of the insights of this episode, consider leaving us a five-star review on Apple Podcasts, and let us know what you learned, found helpful, or liked most about this show!

Today’s guest is Fred Manby, CTO and Co-founder of Iambic Therapeutics. Iambic uses algorithms to drive a high-throughput experimental platform that specializes in developing new drug discovery techniques. Fred returns to the program to explore the next frontier of AI-driven drug discovery. Building on the previous discussion, this episode delves into the transformative role of automation, data generation, and predictive modeling in pharmaceutical development. This episode is sponsored by Iambic Therapeutics. Learn how brands work with Emerj and other Emerj Media options at emerj.com/ad1.

Today’s guest is Fred Manby, CTO and Co-founder of Iambic Therapeutics. Iambic uses algorithms to drive a high-throughput experimental platform that specializes in developing new drug discovery techniques. Fred joins us on today’s program to discuss the evolving landscape of drug discovery in life sciences. With AI playing an increasingly critical role, the conversation explores the biggest challenges facing drug discovery workflows and how life sciences leaders can better leverage data-driven tools to address them. If you’ve enjoyed or benefited from some of the insights of this episode, consider leaving us a five-star review on Apple Podcasts, and let us know what you learned, found helpful, or liked most about this show!

Today’s guest is Ben Coverdale, Global Account Director of Life Sciences at Patsnap. Patsnap is a healthcare technology company that provides IP and R&D teams with enhanced insights to make informed and timely decisions. Using a specialized AI model and the Hiro assistant, the platform boosts productivity and reduces inefficiencies across the innovation lifecycle. Ben returns to the show to dive deeper into the real-world applications of generative AI and large language models (LLMs) that are reshaping the drug discovery landscape. He provides a closer look at use cases where AI is not just enhancing traditional processes but enabling entirely new possibilities in drug targeting and sequencing that were previously unimaginable. If you’ve enjoyed or benefited from some of the insights of this episode, consider leaving us a five-star review on Apple Podcasts, and let us know what you learned, found helpful, or liked most about this show!

Today’s guest is Ben Coverdale, Global Account Director of Life Sciences at Patsnap. Patsnap is a healthcare technology company that provides IP and R&D teams with enhanced insights to make informed and timely decisions. Using a specialized AI model and the Hiro assistant, the platform boosts productivity and reduces inefficiencies across the innovation lifecycle. Ben joins us on today’s program to explore the transformative role of generative AI and large language models (LLMs) in life sciences. His discussion with Emerj Senior Editor Matthew DeMello covers how data silos are dissolving as companies adopt integrated LLM strategies, offering new possibilities for collaboration and efficiency. Ben provides insight into the practical applications of LLMs, the promise they hold for optimizing R&D, and the potential impact on the regulatory landscape. If you’ve enjoyed or benefited from some of the insights of this episode, consider leaving us a five-star review on Apple Podcasts, and let us know what you learned, found helpful, or liked most about this show!