TY - JOUR
T1 - The ACPGBI AI taskforce report
T2 - A mixed-methods roadmap for AI in colorectal surgery
AU - Kinross, James M.
AU - Lam, Kyle
AU - Yiu, Andrew
AU - Adams, Katie
AU - Altaf, Kiran
AU - Burns, Elaine
AU - Duffourc, Mindy
AU - Eardley, Nicola
AU - Evans, Charles
AU - Giannarou, Stamatia
AU - Hancock, Laura
AU - Hu, Victoria
AU - Javed, Ahsan
AU - Khare, Shivank
AU - Mazomenos, Evangelos
AU - McGeever, Linnet
AU - Moug, Susan
AU - Nastro, Piero
AU - Ourselin, Sebastien
AU - Ramamoorthy, Subramanian
AU - Roxburgh, Campbell
AU - Simister, Catherine
AU - Stoyanov, Danail
AU - Thomas, Gregory
AU - Valdastri, Pietro
AU - Vass, Marcus
AU - Vimalachandran, Dale
AU - Vercauteren, Tom
AU - Davies, Justin
N1 - Publisher Copyright:
© 2025 The Author(s). Colorectal Disease published by John Wiley & Sons Ltd on behalf of Association of Coloproctology of Great Britain and Ireland.
PY - 2025/9/1
Y1 - 2025/9/1
N2 - Aim: The ACPGBI has commissioned a taskforce to devise a strategy for integrating artificial intelligence (AI) into colorectal surgery. This report aims to (i) map current AI adoption amongst UK colorectal surgeons; (ii) evaluate knowledge, attitudes, perceptions and experience of AI technologies; and (iii) establish priority recommendations to drive innovation across the specialty. Methods: A prospective 45-item questionnaire was circulated to the ACPGBI membership. Questionnaire findings were explored at a multidisciplinary round table of surgeons, allied professionals, computer scientists and lawyers. Strategic recommendations were then generated. Results: 122 members responded (75.4% consultants; 72.1% male; modal age 41–50 years). Although 43.5% used AI daily, only one third said they could explain key concepts within AI. 86.9% anticipated routine future-AI use, with documentation and imaging ranked highest. 88.5% endorsed formal AI training. Major obstacles were unclear regulation, cost, medicolegal liability and professional or patient distrust. The round table generated 17 recommendations across clinical, educational and research domains and a ten-point action plan, including the establishment of a Colorectal AI Committee and the creation of an open-source colorectal foundational data initiative. Conclusion: This taskforce report combines questionnaire insights from the ACPGBI membership and expert debate into 17 key recommendations and a ten-point action plan that will set the direction of future colorectal AI practice. The objective is to establish a framework through which colorectal surgical practice can be augmented by safe, trustworthy AI.
AB - Aim: The ACPGBI has commissioned a taskforce to devise a strategy for integrating artificial intelligence (AI) into colorectal surgery. This report aims to (i) map current AI adoption amongst UK colorectal surgeons; (ii) evaluate knowledge, attitudes, perceptions and experience of AI technologies; and (iii) establish priority recommendations to drive innovation across the specialty. Methods: A prospective 45-item questionnaire was circulated to the ACPGBI membership. Questionnaire findings were explored at a multidisciplinary round table of surgeons, allied professionals, computer scientists and lawyers. Strategic recommendations were then generated. Results: 122 members responded (75.4% consultants; 72.1% male; modal age 41–50 years). Although 43.5% used AI daily, only one third said they could explain key concepts within AI. 86.9% anticipated routine future-AI use, with documentation and imaging ranked highest. 88.5% endorsed formal AI training. Major obstacles were unclear regulation, cost, medicolegal liability and professional or patient distrust. The round table generated 17 recommendations across clinical, educational and research domains and a ten-point action plan, including the establishment of a Colorectal AI Committee and the creation of an open-source colorectal foundational data initiative. Conclusion: This taskforce report combines questionnaire insights from the ACPGBI membership and expert debate into 17 key recommendations and a ten-point action plan that will set the direction of future colorectal AI practice. The objective is to establish a framework through which colorectal surgical practice can be augmented by safe, trustworthy AI.
KW - artificial intelligence
KW - foundational datasets
KW - generative AI
KW - implementation strategy
KW - machine learning
KW - surgical education
KW - surgical innovation
U2 - 10.1111/codi.70232
DO - 10.1111/codi.70232
M3 - Article
SN - 1462-8910
VL - 27
SP - 1
EP - 15
JO - Colorectal Disease
JF - Colorectal Disease
IS - 9
M1 - e70232
ER -