Through better diagnosis accuracy, treatment plan optimization, and patient outcomes improvement, artificial intelligence (AI) is transforming world healthcare. Predictive analytics, deep learning applications, natural language processing (NLP), and robotic-assisted surgeries are among the newly developing artificial intelligence themes driving healthcare transformation investigated in this paper. Clinical decision-making is much advanced by the incorporation of artificial intelligence into automated disease detection, real-time monitoring, and tailored treatment. Furthermore changing patient care are AI-driven drug discovery and telemedicine technologies, thereby improving access to and efficiency of healthcare. Adoption of artificial intelligence in healthcare faces difficulties including data privacy issues, algorithmic bias, legislative restrictions, and the requirement of strong ethical frameworks notwithstanding its transforming power. This paper guarantees that AI-driven healthcare solutions are both efficient and fair by offering a thorough evaluation of these obstacles together with techniques to overcome them. Furthermore under discussion is how federated learning, explainable artificial intelligence, and AI-enabled electronic health records (EHRs) help to create a data-driven healthcare ecosystem. Through an analysis of present trends and future opportunities, this study emphasizes how important artificial intelligence is in forming the next generation of medical systems. For those working in healthcare, legislators, and artificial intelligence researchers trying to fully utilize AI for world healthcare transformation, the results provide insightful analysis.