In today's digital age where health data is increasingly stored, accessed, and shared electronically, ensuring the privacy and security of patient information has become a major concern. The potential risks associated with unauthorized access, data breaches, and privacy violations require innovative approaches to protect sensitive health data. This is where the power of artificial intelligence (AI) comes into play. AI innovations have emerged as a transformative force in healthcare and offer promising solutions to enhance privacy protection. This paper discusses how healthcare organizations can use artificial intelligence (AI) to protect patient privacy while extracting valuable insights from their data. It also expresses how AI techniques such as differential privacy and fused learning can help organizations collaborate, aggregate their data, and train machine learning models securely without compromising patient privacy. It emphasizes the importance of understanding the challenges and potential limitations of privacy-preserving techniques in this context and encourages stakeholders to collaborate on developing industry standards and best practices for privacy protection.