Artificial intelligence transforms healthcare security by providing sophisticated defenses against evolving cyber threats targeting medical organizations. As healthcare institutions increasingly digitize patient records and clinical workflows, traditional security measures are inadequate against advanced persistent threats and ransomware attacks targeting medical facilities. AI-driven security solutions offer superior capabilities through behavioral analytics, anomaly detection, and automated response mechanisms that adapt to emerging threats without manual reconfiguration. From insider threat detection to fraud prevention in telemedicine, AI applications demonstrate effectiveness across various healthcare security domains. The integration of AI security tools presents both technical challenges and ethical considerations, particularly regarding regulatory compliance, privacy protection, and algorithm transparency. Case studies from academic medical centers, regional providers, and telemedicine platforms illustrate successful implementation approaches that balance security requirements with clinical workflows. By combining technical controls with contextual awareness of healthcare operations, AI security frameworks represent a fundamental advancement in protecting sensitive patient data and ensuring clinical operations remain uninterrupted despite increasing threat sophistication.
Keywords: Artificial Intelligence, healthcare cybersecurity, insider threat detection, ransomware mitigation, regulatory compliance
