Radiographers' role in the age of AI: A qualitative comparative multi case study.
Authors
Affiliations (5)
Affiliations (5)
- Department of Radiology in Norrköping, and Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden; Center for Medical Image Science and Visualization, Linköping University, Linköping, Sweden. Electronic address: [email protected].
- Department of Health, Education and Technology Technology, Division of Nursing and Medical Technology, Luleå University of Technology University of Technology, Sweden.
- Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden; Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden.
- Division of Diagnostics and Specialist Medicine, Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden; Department of Radiology, Linköping University Hospital, Linköping, Sweden; Center for Medical Image Science and Visualization (CMIV), Linköping, Sweden.
- Department of Radiology in Linköping and Department of Health Medicine and Caring Sciences, Linköping University, Linköping, Sweden; Center for Medical Image Science and Visualization, Linköping University, Linköping, Sweden.
Abstract
Artificial intelligence (AI) is increasingly integrated into radiology workflows, supporting tasks such as image reconstruction, patient positioning, and administrative processes. While these developments promise efficiency and improved diagnostic quality, their impact on radiographers' professional roles remains unclear, particularly in Sweden, where formal AI training is absent, and staffing shortages persist. Understanding radiographers' perspectives is essential for safe implementation and workforce sustainability. This study aims to explore how the professional role of radiographers is influenced by the current and future implementation of AI in radiology. A qualitative multi-case study was conducted across three Swedish university hospitals. Semi-structured interviews were carried out with 18 strategically selected participants, including section leaders, researchers, and department managers. Data were analysed using thematic analysis, focusing on perceptions of AI, its impact on professional identity, and anticipated future tasks. Five themes emerged in each of the 18 cases and were compared across hospitals. Participants reported a lack of training and uncertainty about the future, as radiographers' roles are rarely considered in technology implementation. Maintaining competence and professional development was highlighted as critical when introducing AI. AI is present in workflows such as image reconstruction, protocol optimisation and patient positioning, but formal training remains limited. Participants viewed AI as both a facilitator of daily work and a potential threat to core tasks, raising concerns about deskilling and loss of identity. Maintaining responsibility for patient safety was emphasised. Thoughtful implementation, structured training, and inclusive planning could enable radiographers to assume advanced roles, including oversight of AI outputs. Including radiographers in the implementation of AI models and formalising AI education, both in undergraduate education and postgraduate courses, are essential for strengthening the profession.