Artificial intelligence (AI) is revolutionizing many industries and medicine. This paper provides   an overview of AI's current and future role in medicine. Currently, AI is used in many ways to improve healthcare including reducing costs, improving patient outcomes, increasing efficiency, early disease detection, diagnostics, medical imaging, drug discovery development, outbreak prediction and modeling, surveillance monitoring, and response, contact tracing applications such as proximity information, GPS data, vaccine distribution and predictive analytics. These applications can potentially improve diagnosis accuracy, identify patients at risk for certain diseases, and personalize treatment plans. For example, AI algorithms can analyze medical images to identify subtle abnormalities that human radiologists may miss. In the future, AI is expected to play a more important role in medicine. It has the potential to help physicians make more informed decisions by analyzing large amounts of data and providing personalized treatment recommendations. Additionally, AI-powered virtual assistants could help patients manage chronic conditions, such as diabetes and hypertension, by providing real-time feedback and guidance. However, there are also challenges to the widespread adoption of AI in medicine. One major concern is the potential for AI algorithms to perpetuate biases in healthcare, diagnosis, histopathology, and microbiota. Additionally, there is security and privacy of patient data. Despite these challenges, the potential benefits of AI in medicine are highly significant. Electrode implantation and microchips can be used as a treatment option for certain medical conditions.  As AI technology continues to advance, we will see more applications in healthcare, leading to better patient outcomes and more efficient healthcare delivery.