<p>Artificial intelligence (AI) offers a powerful means to accelerate precision oncology by individualizing care in an era of rapidly evolving treatment paradigms. However, there is limited regulatory oversights for safe clinical implementation of AI, and concerns surrounding data bias, ownership, and privacy have hindered broad integration into healthcare practice. In this perspective, we offer a forward-looking roadmap for the dissemination of AI in oncology. We discuss the role for AI in guiding biomarker-driven patient selection for clinical trials and in facilitating both personalized drug selection and de novo drug design by the potential to predict therapeutic response. We highlight the capabilities, and current limitations, of AI to inform realistic pathways for practical implementation.</p>