AI Uses in Healthcare System

Abstract Healthcare institutes achieve revolution in their diagnostics and treatment planning along with patient management through artificial intelligence (AI) which works together with machine learning (ML) anddeep learning (DL) in addition to natural language processing (NLP) and robotics systems. AI analyzes medical images, which allows early diagnosis of cancer along with diabetic retinopathy and cardiovascular problemswith detection accuracy equal to or above human medical expertise. Virtual health assistants, together with predictive analytics and robotic process automation (RPA), work to optimize healthcare operations by improving both administrative efficiency and individual patient care plans. Healthcare AI implementation contains obstacles because of ethical conflicts and operational implementation issues and legal problems, which include privacy protection challenges, biased algorithm programs, restrictive regulatory needs and the high expense of deployment. Responsible AI integration requires transparent systems alongside robust regulations and equal representation of data to maintain responsible functionality. The chapter studies primal AI technologies together with their medical applications and the obstacles delaying their universal healthcareintegration, with a focus on future healthcare improvements through enhanced efficiency and accuracy and expanded accessibility.