Radiology plays a crucial role in modern healthcare by aiding in the diagnosis and treatment of various medical conditions. However, the interpretation of radiological imagesn can be challenging and subjective, leading to variations in diagnostic accuracy among radiologists. In recent years, artificial intelligence (AI) has emerged as a promising tool to enhance diagnostic accuracy in radiology. This review article explores the current state of AI applications in radiology and its potential to revolutionize the field. We discuss the different AI algorithms used for image analysis, such as deep learning and machine learning, and their impact on improving diagnostic accuracy. Furthermore, we examine the challenges and limitations of AI implementation in radiology, including issues related to data quality, regulatory concerns, and ethical considerations. Additionally, we highlight the potential benefits of AI in radiology, such as reducing interpretation errors, improving workflow efficiency, and enhancing patient outcomes. Overall, this review provides insights into the role of AI in transforming radiological practice and improving diagnostic accuracy.