The Unpredictability Problem in Healthcare AI
The rapid adoption of artificial intelligence agents and applications in healthcare settings has created a significant security challenge. Unlike traditional deterministic software, AI systems are inherently non deterministic, meaning their behavior cannot be fully predicted in advance, said Niv Braun, co founder and CEO of Noma Security. This unpredictability is especially dangerous in clinical environments where AI might influence patient care decisions, access electronic health records, or control medical devices. The pressure to deploy AI quickly often outpaces the ability of hospital security teams to assess and mitigate risks.
A Unified Security Framework for Hospital AI Stacks
Braun argues that securing AI in healthcare requires a holistic framework that integrates posture management, access controls, and runtime monitoring into a single, coherent signal. He emphasized that without observing what an AI agent does during runtime, it is impossible to provide accurate recommendations on configuration or access permissions. For a hospital CISO, this means traditional siloed security tools are insufficient. A unified AI security platform can connect how an agent is configured with what it actually does, enabling security teams to distinguish between legitimate actions, like a clinical decision support query, and anomalous behavior that could compromise patient data or safety.
What This Means for Healthcare Organizations
For healthcare delivery organizations, the implications are immediate. AI agents accessing EHRs or interacting with medical IoT devices require granular, context aware security policies. The blast radius of a misconfigured AI agent could expose protected health information or disrupt clinical operations. Noma Security has grown rapidly since late 2024, reflecting demand for tools that can manage AI specific risks while supporting compliance with regulations like HIPAA and FDA guidance on machine learning in medical devices. Braun recommends that hospital security leaders prioritize solutions that offer deep contextualization of AI behavior across development and production environments, not just at the posture scanning level.
Source: Healthcareinfosecurity
