TY - JOUR
T1 - R-AI-diographers
T2 - investigating the perceived impact of artificial intelligence on radiographers' careers, roles, and professional identity in the UK
AU - Walsh, Gemma
AU - Stogiannos, Nikolaos
AU - Ohene-Botwe, Benard
AU - McHugh, Kevin
AU - Spurge, Alexander
AU - Potts, Ben
AU - Gibson, Christopher
AU - Tam, Winnie
AU - O’Sullivan, Chris
AU - Quinsten, Anton Sheahan
AU - Gorga, Rodrigo Garcia
AU - Sipos, Dávid
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, Amand H.
AU - St John-Matthews, Janice
AU - McEntee, Mark
AU - Kyratsis, Yiannis
AU - Malamateniou, Christina
N1 - Publisher Copyright:
2025 Walsh, Stogiannos, Ohene-Botwe, McHugh, Spurge, Potts, Gibson, Tam, O’Sullivan, Quinsten, Gorga, Sipos, Dybeli, Zanardo, Sá dos Reis, Mekis, Buissink, England, Beardmore, Cunha, Goodall, St John-Matthews, McEntee, Kyratsis and Malamateniou.
PY - 2025
Y1 - 2025
N2 - Introduction: Artificial Intelligence (AI) is being increasingly integrated into radiography, affecting daily responsibilities and workflows. Most studies focus on AI’s influence on clinical performance or workflows; fewer explore radiographers' perspectives on how AI affects their roles and the profession. This study aims to investigate the perceived impact of AI on radiographers' careers, roles and professional identity in the UK. Methods: A UK-wide, cross-sectional, online survey including 32 questions was conducted using snowball sampling to gather responses from qualified radiographers and radiography students. The survey gathered data on: (a) demographics, (b) perceived short-term impacts of AI on roles and responsibilities, (c) potential medium-to-long-term impacts, (d) opportunities and threats from AI, and (e) preparedness to work with AI. Overall perceptions (optimism, neutrality, or pessimism) were derived from cumulative answers to a subset of 6 questions. Results: A total of 322 valid responses were received, showing general optimism about medium-to-long-term impact of AI on careers, roles and professional identity (60.7% optimistic). Most respondents (70.8%) reported no formal AI education or training, with AI education emerging as the top priority for improving preparedness in clinical practice. Concerns centered around the potential deskilling of radiographers and AI inefficiencies. However, 81.2% agreed AI would not replace radiographers in the long term. Conclusion: Radiographers are broadly optimistic about AI's impact but express concerns about deskilling due to reliance on AI. While their optimism is encouraging for recruitment and retention, there is a clear need for AI-specific education to enhance preparedness to work with AI.
AB - Introduction: Artificial Intelligence (AI) is being increasingly integrated into radiography, affecting daily responsibilities and workflows. Most studies focus on AI’s influence on clinical performance or workflows; fewer explore radiographers' perspectives on how AI affects their roles and the profession. This study aims to investigate the perceived impact of AI on radiographers' careers, roles and professional identity in the UK. Methods: A UK-wide, cross-sectional, online survey including 32 questions was conducted using snowball sampling to gather responses from qualified radiographers and radiography students. The survey gathered data on: (a) demographics, (b) perceived short-term impacts of AI on roles and responsibilities, (c) potential medium-to-long-term impacts, (d) opportunities and threats from AI, and (e) preparedness to work with AI. Overall perceptions (optimism, neutrality, or pessimism) were derived from cumulative answers to a subset of 6 questions. Results: A total of 322 valid responses were received, showing general optimism about medium-to-long-term impact of AI on careers, roles and professional identity (60.7% optimistic). Most respondents (70.8%) reported no formal AI education or training, with AI education emerging as the top priority for improving preparedness in clinical practice. Concerns centered around the potential deskilling of radiographers and AI inefficiencies. However, 81.2% agreed AI would not replace radiographers in the long term. Conclusion: Radiographers are broadly optimistic about AI's impact but express concerns about deskilling due to reliance on AI. While their optimism is encouraging for recruitment and retention, there is a clear need for AI-specific education to enhance preparedness to work with AI.
KW - AI education
KW - artificial intelligence (AI)
KW - clinical roles
KW - professional identity
KW - radiographer
KW - radiography
KW - workforce preparedness
UR - https://www.scopus.com/pages/publications/105025658662
U2 - 10.3389/fdgth.2025.1603511
DO - 10.3389/fdgth.2025.1603511
M3 - Article
AN - SCOPUS:105025658662
SN - 2673-253X
VL - 7
JO - Frontiers in Digital Health
JF - Frontiers in Digital Health
M1 - 1603511
ER -