Artificial Intelligence (AI) technologies are revolutionizing not only administrative health care tasks, but also clinical patient care when it comes to diagnostics. As healthcare organizations implement digital technologies, they are also increasingly exposed to cybersecurity risks that compromise not only health data but also patient trust and privacy. This article focuses on how AI-driven tools can bring about an overall better security posture, but with a particular emphasis on the distinctive vulnerabilities unique to healthcare, by means of cybersecurity and healthcare innovations. Predictive analytics, personalised medicine and automated diagnostic support provide striking improvement for patientsbytechnical AI capabilities. However, despite this mantra healthcare weathers some of the highest data breaches in the industry, and ransomware continues to be a principal threat to patient safety and organizational reputation during an already tumultuous time. In this post, we take a look at AI-based cybersecurity measures and how threat detection using machine learning algorithms protect us from these threats. Second we look into network activity driven behaviour-based frameworks to detect smart overlooking hazards. It outlines use cases to demonstrate how these technologies can be used within healthcare organizations, strengthening security measures. Finally, we talk about the future of AI in healthcare cybersecurity which introduces a host of patient data security possibilities with blockchain and how advanced AI models can be applied to predict threats far before they come knocking at our doors. A main point of this article is the necessity to work with healthcare providers, technologists and cybersecurity specialist in order to innovate as well as keep patient information safe.