The integration of Artificial Intelligence (AI) and advanced imaging technologies is reshaping the landscape of cardiovascular medicine, offering transformative approaches to the diagnosis, management, and prognosis of complex cardiac conditions. The convergence of AI and cardiac magnetic resonance (CMR) imaging has enhanced diagnostic precision, automated image analysis, and personalized treatment strategies for inflammatory cardiovascular diseases like myocarditis, pericarditis, and autoimmune rheumatologic conditions with cardiac involvement conditions like sarcoidosis, and systemic lupus erythematosus (SLE). AI-driven methodologies, particularly machine learning (ML) and deep learning (DL) algorithms, have demonstrated remarkable efficacy in identifying subtle pathological changes, detecting and quantifying myocardial inflammation, and predicting disease outcomes with unprecedented accuracy. Innovations such as convolutional neural networks (CNNs) and hybrid models like CNN-KCL significantly enhance CMR’s capabilities, enabling early detection and reducing diagnostic variability. By analyzing complex imaging datasets, AI supports comprehensive tissue characterization, advancing the understanding of inflammatory processes and myocardial remodeling. The article also explores AI’s potential in risk stratification and outcome prediction, emphasizing its role in aligning with personalized medicine principles. Despite the promise, challenges such as dataset limitations, model explainability, and the need for multicenter validation persist, underscoring the importance of collaborative efforts in AI development.