Navigating Cybersecurity Challenges of Agentic AI in Healthcare CISOs are increasingly grappling with how organizations govern systems that can autonomously access data, make decisions, and trigger actions across enterprise environments. Security frameworks were traditionally built for rule-based software — not for systems that take independent actions, as agents do. Healthcare is becoming an especially useful test case because AI agents increasingly interact with highly sensitive data, regulated workflows, and mission-critical operations. Data collaboration platform, Datavant, recently announced its membership in the AIUC-1 Consortium, a group developing standards for the safety, security, and reliability of agentic AI. Healthcare Innovation chatted with Datavant’s CISO, Dan Walsh, about the new cybersecurity realities in the agentic AI world. Could you tell me about your organization? We are a healthcare tech company. Our mission centers around what we refer to as longitudinal health record, providing the healthcare data pipelines for the medical records across the healthcare continuum. We’re embedded in a good portion of the US healthcare system, I think 70 percent of the US health systems. Could you talk a bit about the AIUC-1 Consortium? The AIUC-1 is an organization whose mission is to create a security compliance framework for agentic AI. The traditional security measures and compliance frameworks that we have are falling a bit short. The AIUC-1 brings together industry leaders across various industries and ecosystems to put together a framework that is open, but also that will work for all as this field continues to evolve. Could you discuss the new cybersecurity challenges healthcare organizations are facing now? If we think about how current controls within the healthcare space are designed, there are new questions around whether an agent should have the same ability to do something as a human. How do we make sure that we manage them? It's different