AbstractPurpose The rapid integration of artificial intelligence (AI) into imaging-intensive fields like radiation oncology (RO) is transforming the clinical workforce from manual operators to supervisory validators, yet the baseline competencies required for safe oversight remain undefined. Here we present the first consensus-built, validated international knowledge assessment of AI literacy to quantify the RO knowledge profile. Methods A multidisciplinary, international panel from clinical practice, academia, and industry developed a 22-item knowledge assessment mapped to core AI-in-radiotherapy concepts. Items underwent a three-round consensus process with blinded initial voting, achieving > 80% panel agreement. The instrument was deployed worldwide via a multilingual web application, and demonstrated excellent internal consistency (Cronbach's α = 0.90) and strong discrimination (mean: 0.63). Results 760 individuals engaged with the assessment; 528 completed all items. Significant role-specific disparities emerged: Medical Physicists demonstrated higher scores than Radiation Oncologists and Radiation Therapists (p Conclusions These results establish a global benchmark for AI readiness. While clinical staff may not require AI development expertise, our findings demonstrate significant value in targeted training to build shared AI vocabulary, ensuring clinical adoption does not outpace safe oversight.
Malone et al. (Mon,) studied this question.