TY - JOUR
T1 - R-AI-diographers
T2 - a European survey on perceived impact of AI on professional identity, careers, and radiographers’ roles
AU - Stogiannos, Nikolaos
AU - Walsh, Gemma
AU - Ohene-Botwe, Benard
AU - McHugh, Kevin
AU - Potts, Ben
AU - Tam, Winnie
AU - O’Sullivan, Chris
AU - Quinsten, Anton Sheahan
AU - Gibson, Christopher
AU - Gorga, Rodrigo Garcia
AU - Sipos, David
AU - Dybeli, Elona
AU - Zanardo, Moreno
AU - Sá dos Reis, Cláudia
AU - Mekis, Nejc
AU - Buissink, Carst
AU - England, Andrew
AU - Beardmore, Charlotte
AU - Cunha, Altino
AU - Goodall, Amanda
AU - John-Matthews, Janice St
AU - McEntee, Mark
AU - Kyratsis, Yiannis
AU - Malamateniou, Christina
N1 - Publisher Copyright:
© The Author(s) 2025.
PY - 2025/12
Y1 - 2025/12
N2 - Objectives: Radiographers use advanced medical imaging and radiotherapy (MIRT) equipment. They are also a digitally mature and digitally resilient workforce in healthcare. Artificial intelligence is already changing their clinical practice and roles in data acquisition, post-processing, and workflow management. It is therefore vital to understand the impact of AI on the careers, roles and professional identity of radiographers, as key stakeholders of the digital transformation of healthcare within the medical imaging ecosystem. Methods: A European radiographer survey, endorsed by the European Federation of Radiographer Societies (EFRS), was distributed online. It was piloted with twelve radiographers and translated into eight languages. Although this study included both qualitative and quantitative results, this paper emphasises the quantitative aspect. Results: A total of 2206 European radiographers have responded from 37 different countries. Despite some concerns around workforce deskilling, future professional identity, and job prospects, participants showed overall optimistic views about the use of AI in healthcare. This was particularly strong for those with prior AI education (mean: 2.15 vs. 1.89; p-value: < 0.001), hands-on experience with AI (correlation: 0.047; p-value: 0.038), from countries with higher digital literacy (mean: 2.00 vs.1.93; p-value: 0.027) and a higher academic level of radiography education (mean: 3.28 vs. 3.15; p-value: 0.002). Men appeared slightly more enthused about the development of technological skills and women about the honing of patient-centred care skills. Finally, interprofessional collaboration was seen as essential not only for the seamless clinical integration of AI but also for supporting patient benefit. Conclusion: While AI implementation advances, AI education needs to keep at pace to ensure acceptability, trust, and safe use of this technology by healthcare professionals, minimising their concerns around professional role changes and enabling them to see the opportunities of service transformation. Critical relevance statement: This paper aims to map out the perceived impact of AI on the professional identity and careers of European radiographers. Key Points: AI is impacting radiographers’ clinical practice and changing their professional identity. Despite increasing AI awareness, AI education is still lacking across Europe. AI education is key for AI acceptability and trust by radiographers, which facilitates AI implementation and service transformation.
AB - Objectives: Radiographers use advanced medical imaging and radiotherapy (MIRT) equipment. They are also a digitally mature and digitally resilient workforce in healthcare. Artificial intelligence is already changing their clinical practice and roles in data acquisition, post-processing, and workflow management. It is therefore vital to understand the impact of AI on the careers, roles and professional identity of radiographers, as key stakeholders of the digital transformation of healthcare within the medical imaging ecosystem. Methods: A European radiographer survey, endorsed by the European Federation of Radiographer Societies (EFRS), was distributed online. It was piloted with twelve radiographers and translated into eight languages. Although this study included both qualitative and quantitative results, this paper emphasises the quantitative aspect. Results: A total of 2206 European radiographers have responded from 37 different countries. Despite some concerns around workforce deskilling, future professional identity, and job prospects, participants showed overall optimistic views about the use of AI in healthcare. This was particularly strong for those with prior AI education (mean: 2.15 vs. 1.89; p-value: < 0.001), hands-on experience with AI (correlation: 0.047; p-value: 0.038), from countries with higher digital literacy (mean: 2.00 vs.1.93; p-value: 0.027) and a higher academic level of radiography education (mean: 3.28 vs. 3.15; p-value: 0.002). Men appeared slightly more enthused about the development of technological skills and women about the honing of patient-centred care skills. Finally, interprofessional collaboration was seen as essential not only for the seamless clinical integration of AI but also for supporting patient benefit. Conclusion: While AI implementation advances, AI education needs to keep at pace to ensure acceptability, trust, and safe use of this technology by healthcare professionals, minimising their concerns around professional role changes and enabling them to see the opportunities of service transformation. Critical relevance statement: This paper aims to map out the perceived impact of AI on the professional identity and careers of European radiographers. Key Points: AI is impacting radiographers’ clinical practice and changing their professional identity. Despite increasing AI awareness, AI education is still lacking across Europe. AI education is key for AI acceptability and trust by radiographers, which facilitates AI implementation and service transformation.
KW - Artificial intelligence
KW - Europe
KW - Impact
KW - Professional identity
KW - Radiographers
UR - http://www.scopus.com/inward/record.url?scp=85218425612&partnerID=8YFLogxK
U2 - 10.1186/s13244-025-01918-6
DO - 10.1186/s13244-025-01918-6
M3 - Article
AN - SCOPUS:85218425612
SN - 1869-4101
VL - 16
JO - Insights into Imaging
JF - Insights into Imaging
IS - 1
M1 - 43
ER -