Abstract
The rapid advancements in artificial intelligence (AI) technology have broad implications for the clinical practice of oncology. AI methods enable us to analyze unstructured patient data in a quantitative way, at scale. AI can also help to manage the exponentially growing amount of specialist knowledge, for example, by parsing information from medical guidelines. As oncologists, we will increasingly interact with AI systems in clinical routine and research. These technical developments will require a reshaping of oncology education, which needs to include the development of 'AI literacy' as a core aim. Henceforth, oncologists require an understanding of the principles of AI, and the capabilities to adapt and use AI for clinical and research tasks. They should also be able to interpret AI-generated data effectively, especially when communicating with patients who will increasingly use AI tools. Oncologists who understand the fundamental concepts of AI, its limitations, and capabilities will be able to come up with new ideas and use cases, for example, in designing clinical trials. Currently, postgraduate oncology education lacks comprehensive curricula addressing AI integration. We propose that the scientific community, in particular academic institutions, professional societies, and policymakers, should prioritize implementing AI literacy within oncology curricula.