Artificial Intelligence (AI) has already started to transform many sectors of the medical imaging workforce, and its use in healthcare is promising, since it can harness digital data to enhance patient experience and improve the existing clinical workflows [1]. There has been an exponential increase in the usage and diversity of accredited AI-enabled clinical applications in medical imaging and radiotherapy [2]. This has resulted, in most cases, in improved efficiency and efficacy. The medical radiation technologists’ (MRTs) profession, known as radiographers in most of Europe and other continents, is central to the rapid growth of AI in this field, since AI is transforming clinical workflows, and it augments certain operational tasks performed by MRTs. Currently, there are many AI-enabled tools which can provide automated patient positioning, protocol optimisation or slice prescription, more efficient image post-processing techniques, reduced image acquisition times, optimal radiation protection [3], image quality enhancement, and many more.

To achieve a safe, successful, and smooth implementation of AI in clinical practice, it is imperative to ensure optimal AI education and training for all clinical practitioners [4]. Professional societies have already embedded AI education and training in their career frameworks, while AI digital competences are now a requirement for radiographer registration in countries like the UK. In the United States, the American Society of Radiologic Technologists (ASRT) was the first of all radiographer/MRT professional bodies globally to publish a white paper on the role of MRTs in the AI era, exploring the perspectives of MRTs, recognizing the upcoming changes for the profession and highlighting the need to optimally train the workforce to overcome any challenges associated with the use of AI technology in this space [5].

Educational curricula for MRT professionals should aim to provide high-quality AI courses to ensure that future graduates are adequately educated to meet the demand for highly skilled professionals working in an AI-driven environment. Therefore, it is vital for all educators teaching MRT students to integrate AI education and training in academic curricula, and to develop optimal learning and assessment strategies for their students. This study [6] aims to explore educators’ level of AI knowledge, provision of AI education, perceived challenges and future priorities.