Artificial intelligence in oncology: empowering clinicians for responsible integration

Artificial intelligence (AI) is rapidly reshaping oncology, from diagnosis to treatment planning and clinical research. This perspective defines the oncologist in the era of AI as a clinician able to critically interpret, supervise, and communicate AI outputs, while understanding the principles, limitations, and ethical implications of these tools. We ground this discussion in a survey of 475 UK-based participants, including cancer patients and survivors, members of the public and healthcare staff. Acceptance of AI was substantial but conditional: it increased sharply with self-reported understanding and depended on assurances of clinician involvement, transparency and data security. These findings motivate the three concerns around which we structure the perspective: 'AI will replace the clinician', 'AI may be biased and unfair', and 'AI does not safeguard data'. Using the example of an AI system for cancer treatment recommendation, we illustrate how these concerns can be addressed through practical, technically grounded approaches, including concept-based modelling, uncertainty quantification, and federated learning. Finally, we argue that AI skills development must become an integral part of oncology education, enabling oncologists not only to use AI safely, but also to explain, contextualise, and critically shape its integration into patient-centred cancer care.