The integration of AI and large language models (LLMs) in healthcare is transforming patient care and operational efficiency but also brings significant cybersecurity challenges. Healthcare systems are increasingly targeted by ransomware attacks, as evidenced by the high-profile hack of UnitedHealth Group's Change Healthcare. AI systems, due to their complex and opaque structures, may be even more vulnerable to breaches than traditional IT systems. Compromised AI can lead to inaccurate diagnoses, inappropriate treatments, and fraudulent claims, with substantial financial consequences and risks to patient safety. Healthcare leaders must adopt robust cybersecurity practices, continuously evaluate AI models, demand transparency from developers, and push for regulatory frameworks and industry-wide standards to secure AI systems. Collaborative efforts among stakeholders are crucial to harness AI's potential while safeguarding healthcare integrity.
