The word “precision medicine,” often referred to as “personalized medicine,” is a relatively new concept in the world of healthcare, but the principle has been around in the industry for many years. It helps physicians recognize more tailored therapies for people and need individualized solutions rather than a blanketed strategy for all patients. To evaluate a therapeutic plan of action, physicians do this by looking at the genetic history, place, environmental factors, behavior and behaviors of a person. This pushes predictive medicine to the next stage for artificial intelligence and improves clinicians ‘ reliability and result forecasting. Others actually believe that precision medicine is not entirely possible to assist in the process without the introduction of machine learning algorithms. Not only can AI interpret and evaluate large sets of medical data even better than a person, it can assess findings more reliably and come to conclusions on treatment options for a condition and future treatment outcomes. Machine learning can also help improve test, drug and pharmaceutical partnership FDA regulations to assist in supporting treatments. Effectively pursuing total precision medicine involves the cooperation of pharmaceutical companies, biotech companies, universities, testing firms, and others to drive innovation forward. Precision medicine can really improve the lives of many people and even save their lives, and the use of artificial intelligence can dramatically increase those results. It can also allow care more affordable and accessible to those who may not be able to receive these services at this period because of expenses and health insurance. Of precision medicine to be successful, there are many challenges ahead, but artificial intelligence will also bring us closer to those targets.