The use of Artificial Intelligence (AI) technology in the domain of healthcare is transforming the diagnosis of disease, genomics, drug discovery, population health management, and patient care in a rapid pace. AI, mainly Machine Learning (ML) and Deep Learning (DL) based techniques, has displayed significant potential in enhancing the accuracy and efficiency of diagnosis. Various fields like early detection of cancer with ML/DL techniques have emerged as most dominant research topic. Furthermore, ML/DL techniques have been applied extensively in research related to chronic diseases such as diabetes and cardiovascular conditions, for providing advanced diagnostic capabilities and decision support systems. In addition, in field like genomics, AI plays a crucial role in analyzing genetic variations and thereby contributing towards development of personalized medicine. By leveraging next-generation sequencing (NGS) and high-throughput genomic technologies, AI facilitates the identification of disease-related mutations and supports the development of targeted therapies. AI also assists in the study of non-coding regions of the genome, which are important for understanding of various genetic disorders. ML/DL based techniques through its predictive power may enhance the ability to forecast health risks of a population thereby may help in population health management and contribute towards optimize interventions, and manage resources effectively in a society. These ML/DL based systems has the potential to transform patient care service by providing virtual health assistants, to improve accessibility as well as support mental health, and offer continuous monitoring of the patient. In spite of all these advantages, there are various challenges associated with it. As the AI based approaches are data driven, the reliability of data is of prime concern. Collaborative interdisciplinary research has to be done for generating these data which can facilitate the development of such real time application. Additionally, data privacy is another important aspect that needs to be handled well. This chapter underscores AI’s transformative potential in healthcare, advocating for responsible use and continuous innovation to enhance patient outcomes and care efficiency.