This literature review provides a comprehensive overview of the integration of artificial intelligence (AI) into clinical practice, highlighting its transformative impact on medicine and healthcare. AI has revolutionized the field by offering innovative solutions to complex problems, particularly in diagnostic methods and various medical specialties. Key benefits include enhanced diagnostic precision, streamlined administrative tasks, and personalized treatment plans. AI can analyze extensive medical data efficiently, leading to more accurate and timely interventions, improved patient outcomes, and cost-effective healthcare solutions. The review covers several medical specialties, including cardiology, surgery, gastroenterology, pneumology, nephrology, urology, dermatology, orthopedics, neurology, gynecology, ophthalmology, pediatrics, and hematology. AI applications in these fields range from automating tasks such as image segmentation and report generation to providing insights for better patient management and treatment planning. For example, in cardiology, AI is used for advanced cardiac data analysis and interpretation, while in surgery, it aids in preoperative diagnosis and postoperative prognosis evaluation. Ethical and legal considerations are also addressed, emphasizing the need for transparency, accountability, and robust ethical guidelines. The review concludes by critically appraising the current state of AI in clinical practice and its future prospects, while advocating for cautious development and implementation to ensure ethical standards are met.This literature review provides a comprehensive overview of the integration of artificial intelligence (AI) into clinical practice, highlighting its transformative impact on medicine and healthcare. AI has revolutionized the field by offering innovative solutions to complex problems, particularly in diagnostic methods and various medical specialties. Key benefits include enhanced diagnostic precision, streamlined administrative tasks, and personalized treatment plans. AI can analyze extensive medical data efficiently, leading to more accurate and timely interventions, improved patient outcomes, and cost-effective healthcare solutions. The review covers several medical specialties, including cardiology, surgery, gastroenterology, pneumology, nephrology, urology, dermatology, orthopedics, neurology, gynecology, ophthalmology, pediatrics, and hematology. AI applications in these fields range from automating tasks such as image segmentation and report generation to providing insights for better patient management and treatment planning. For example, in cardiology, AI is used for advanced cardiac data analysis and interpretation, while in surgery, it aids in preoperative diagnosis and postoperative prognosis evaluation. Ethical and legal considerations are also addressed, emphasizing the need for transparency, accountability, and robust ethical guidelines. The review concludes by critically appraising the current state of AI in clinical practice and its future prospects, while advocating for cautious development and implementation to ensure ethical standards are met.