Cancer remains a global challenge, with traditional treatments often causing severe side effects and inconsistent outcomes. Immunotherapy offers a promising alternative but is limited by tumor heterogeneity and complex immune responses. AI is revolutionizing cancer immunotherapy by predicting patient responses, identifying biomarkers, and optimizing treatments. By analyzing genomic, transcriptomic, and proteomic data, AI enhances precision medicine, reduces side effects, and accelerates the discovery of novel targets like neoantigens. This chapter explores AI-driven predictive models using histopathology, imaging-omics, and multi-omics data while addressing key challenges like scalability, fairness, and trust. It also highlights innovations such as generative AI for biomarker discovery, quantum machine learning for drug development, and personalized mRNA vaccines. This chapter showcases AI’s potential to transform cancer treatment by bridging AI and immunotherapy, making it more precise and personalized.