BibTex format
@article{Sheil:2026:10.1016/j.compgeo.2025.107604,
author = {Sheil, B and Anagnostopoulos, C and Buckley, R and Ciantia, M and Febrianto, E and Fu, J and Gao, Z and Geng, X and Gong, B and Hanley, K and He, P and Kolomvatsos, K and Lopes, B and Ninic, J and Previtali, M and Rezania, M and Ruiz, Lopez A and Sun, J and Suryasentana, S and Taborda, D and Utili, S and Whyte, S and Zhang, P},
doi = {10.1016/j.compgeo.2025.107604},
journal = {Computers and Geotechnics},
title = {Artificial intelligence transformations in geotechnics: progress, challenges and future enablers},
url = {http://dx.doi.org/10.1016/j.compgeo.2025.107604},
volume = {189},
year = {2026}
}
RIS format (EndNote, RefMan)
TY - JOUR
AB - Our reliance on the underground space to deliver critical civil engineering infrastructure is growing: to accommodate utility and transport infrastructure in urban environments, to provide innovative housing and commercial solutions, and to support proliferating renewable energy infrastructure, particularly offshore. Artificial intelligence (AI) is arguably the most promising enabler to transform geotechnical engineering by extracting knowledge from data to achieve step-change increases in efficiency, sustainability, reliability and safety. This paper seeks to develop a shared understanding of the state of the art of AI in geotechnics and to explore future developments. By way of example, specific popular use cases in geotechnics are considered to highlight current progress in AI applications including intelligent site investigation, predictive modelling for soil behaviour, and optimisation of design and construction processes. The paper then addresses key research challenges, such as data scarcity and interpretability, and discusses the opportunities that lie ahead in the integration of AI with geotechnical engineering. Finally, priority technological enablers are identified for future transformations.
AU - Sheil,B
AU - Anagnostopoulos,C
AU - Buckley,R
AU - Ciantia,M
AU - Febrianto,E
AU - Fu,J
AU - Gao,Z
AU - Geng,X
AU - Gong,B
AU - Hanley,K
AU - He,P
AU - Kolomvatsos,K
AU - Lopes,B
AU - Ninic,J
AU - Previtali,M
AU - Rezania,M
AU - Ruiz,Lopez A
AU - Sun,J
AU - Suryasentana,S
AU - Taborda,D
AU - Utili,S
AU - Whyte,S
AU - Zhang,P
DO - 10.1016/j.compgeo.2025.107604
PY - 2026///
SN - 0266-352X
TI - Artificial intelligence transformations in geotechnics: progress, challenges and future enablers
T2 - Computers and Geotechnics
UR - http://dx.doi.org/10.1016/j.compgeo.2025.107604
VL - 189
ER -
