Artificial Intelligence (AI) is revolutionizing healthcare by enhancing patient care, improving treatment protocols, and transforming medical research. This review explores the contributions of three advanced language models—ChatGPT, Gemini Advanced, and Co-pilot—in healthcare. ChatGPT excels in providing personalized mental health support and chronic condition management through its natural language processing capabilities. Gemini Advanced enhances data analytics, aiding in early disease detection and medical decision-making. Co-pilot integrates seamlessly with healthcare systems, optimizing clinical workflows and fostering innovation among healthcare professionals. AI is accelerating medical research, particularly in genomics and drug discovery, paving the way for personalized medicine. It also plays a crucial role in epidemiology, especially in managing infectious diseases like COVID-19. However, the integration of AI in healthcare presents challenges, including data privacy, security, and the need for robust cybersecurity measures. Ethical considerations, such as algorithmic bias and transparency, are also critical. The review emphasizes the importance of regulatory compliance, transparent consent management, and maintaining AI systems' reliability and accuracy. Despite these challenges, AI holds significant potential to improve healthcare delivery, making it more accessible, personalized, and efficient. The integration of AI requires a holistic approach, considering both technological and organizational dimensions. Continuous validation, adaptation, and governance of AI systems are essential to ensure they align with evolving medical knowledge and clinical practices. The review underscores the need for collaboration among technologists, healthcare professionals, and policymakers to responsibly harness AI's capabilities, ensuring that these advancements lead to tangible improvements in patient care and medical research.Artificial Intelligence (AI) is revolutionizing healthcare by enhancing patient care, improving treatment protocols, and transforming medical research. This review explores the contributions of three advanced language models—ChatGPT, Gemini Advanced, and Co-pilot—in healthcare. ChatGPT excels in providing personalized mental health support and chronic condition management through its natural language processing capabilities. Gemini Advanced enhances data analytics, aiding in early disease detection and medical decision-making. Co-pilot integrates seamlessly with healthcare systems, optimizing clinical workflows and fostering innovation among healthcare professionals. AI is accelerating medical research, particularly in genomics and drug discovery, paving the way for personalized medicine. It also plays a crucial role in epidemiology, especially in managing infectious diseases like COVID-19. However, the integration of AI in healthcare presents challenges, including data privacy, security, and the need for robust cybersecurity measures. Ethical considerations, such as algorithmic bias and transparency, are also critical. The review emphasizes the importance of regulatory compliance, transparent consent management, and maintaining AI systems' reliability and accuracy. Despite these challenges, AI holds significant potential to improve healthcare delivery, making it more accessible, personalized, and efficient. The integration of AI requires a holistic approach, considering both technological and organizational dimensions. Continuous validation, adaptation, and governance of AI systems are essential to ensure they align with evolving medical knowledge and clinical practices. The review underscores the need for collaboration among technologists, healthcare professionals, and policymakers to responsibly harness AI's capabilities, ensuring that these advancements lead to tangible improvements in patient care and medical research.