The integration of artificial intelligence (AI) in CT-guided and MR-guided interventions holds tremendous potential to revolutionize the field of interventional radiology. Through advanced image analysis, real-time decision support, and personalized interventional planning, AI has the capacity to enhance visualization, navigation, and overall clinical outcomes. Furthermore, AI-driven augmented reality technologies are poised to create immersive and effective learning environments for medical professionals, fostering the development of critical skills in the next generation of practitioners. Despite the promising advancements, several challenges must be addressed before widespread implementation of AI solutions in clinical settings can be achieved. These challenges include data quality and quantity, algorithm validation and generalizability, integration with existing clinical workflows, regulatory and ethical considerations, physician acceptance and trust, and cost and infrastructure. By fostering collaboration among institutions, engaging in multidisciplinary research, and investing in education and training, the medical community can work together to overcome these obstacles and pave the way for the successful integration of AI technologies in CT-guided and MR-guided interventions. Ultimately, the collaborative efforts of AI developers, medical professionals, and researchers will be essential for harnessing the power of artificial intelligence to improve patient care and outcomes in the rapidly evolving field of interventional radiology.