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A Nordic survey on artificial intelligence in the radiography profession – Is the profession ready for a culture change?

Pedersen, M. R. V., Kusk, M. W., Lysdahlgaard, S. , Mork-Knudsen, H., Malamateniou, C. ORCID: 0000-0002-2352-8575 & Jensen, J. (2024). A Nordic survey on artificial intelligence in the radiography profession – Is the profession ready for a culture change?. Radiography, 30(4), pp. 1106-1115. doi: 10.1016/j.radi.2024.04.020


The impact of artificial intelligence (AI) on the radiography profession remains uncertain. Although AI has been increasingly used in clinical radiography, the perspectives of the radiography professionals in Nordic countries have yet to be examined. The primary aim was to examine views of Nordic radiographers ‘on AI, with focus on perspectives, engagement, and knowledge of AI.

Radiographers from Denmark, Norway, Sweden, Iceland, Greenland, and the Faroe Island were invited through social media platforms to participate in an online survey from March to June 2023. The survey encompassed 29-items and included 4 sections a) demographics, b) barriers and enablers on AI, c) perspectives and experiences of AI and d) knowledge of AI in radiography. Edgars Schein's model of organizational culture was employed to analyse Nordic radiographers' perspectives on AI.

Overall, a total of 421 respondents participated in the survey. A majority were positive/somewhat positive towards AI in radiography e.g., 77.9 % (n = 342) thought that AI would have a positive effect on the profession, and 26% thought that AI would reduce the administrative workload. Most radiographers agreed or strongly agreed that clinicians may have access to AI generated reports (76.8 %, n = 297). Nevertheless, a total of 86 (20.1%) agree or somewhat agreed that AI a potential risk for radiography.

Nordic radiographers are generally positive towards AI, yet uncertainties regarding its implementation persist. The findings underscore the importance of understanding these challenges for the responsible integration of AI systems. Carefully weighing the expected influence of AI against key incentives will support a seamless integration of AI for the benefit not just of the patients, but also of the radiography profession.

Implications for practice
Understanding incentives factors and barriers can help address uncertainties during implementation of AI in clinical practice.

Publication Type: Article
Additional Information: This is an open access article distributed under the terms of the Creative Commons CC-BY license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Publisher Keywords: Artificial intelligence, Radiography, Survey, Profession, Motivation
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
R Medicine > RC Internal medicine
Departments: School of Health & Psychological Sciences
School of Health & Psychological Sciences > Midwifery & Radiography
SWORD Depositor:
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