Cancer diagnosis confronts patients with an immediate and urgent need for reliable, comprehensible, and personalised information. Yet across Europe, and acutely in Greece, access to high-quality oncology information remains profoundly unequal, shaped by geography, language, socioeconomic status, digital literacy, and the time constraints of overstretched healthcare systems. This paper examines how artificial intelligence (AI), and specifically Retrieval-Augmented Generation (RAG) architectures, can address this inequity by delivering dynamically personalised, evidence-grounded patient information at scale - built by patients and for patient needs, not for hospital workflows. Beyond the technical dimension, the paper argues that the true transformative potential of AI in oncology communication lies not in replacing the human relationship between patients, informal carers, and medical professionals, but in strengthening it to create synergies of collaboration. When patients arrive at clinical encounters better informed, their capacity for shared decision-making is enhanced, their autonomy is respected, and the therapeutic alliance is deepened. The paper additionally draws on neuroscientific evidence on the cognitive burden imposed by cancer diagnosis, arguing that information systems must be designed for the compromised cognitive state of their recipients, not for the idealised attentive reader. Drawing on the Greek oncology context as a specific case within the broader European landscape, and grounding the analysis in established frameworks for patient rights, health literacy, and co-design, this paper presents a principled framework for deploying AI-RAG systems in cancer care in ways that prioritise equity, empowerment, and trust.