In the field of 3D medical image processing, artificial intelligence (AI) has emerged as a disruptive tool. This chapter discusses the use of artificial intelligence algorithms in evaluating complicated volumetric medical images, emphasizing its potential to improve diagnosis accuracy, treatment planning, and patient outcomes. AI systems, particularly deep learning models like convolutional neural networks, have demonstrated amazing success in automating tasks like segmentation, classification, and abnormality detection in 3D medical images. AI-based analysis of images can give quantitative and objective measures by leveraging massive amounts of data, decreasing human error and variability. However, challenges such as the availability of high-quality data, the interpretability of AI models, and ethical concerns must be addressed before widespread adoption can occur. To overcome these obstacles and realize the full potential of AI in 3D medical image processing, researchers, doctors, regulatory agencies, and industrial partners must work together. AI has the potential to revolutionize healthcare by enhancing diagnosis accuracy and tailored treatment methods through continual innovation and responsible use.