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Lookup NU author(s): Professor Stefano UtiliORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2025. 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.
Author(s): Sheil B, Anagnostopoulos C, Buckley R, Ciantia MO, Febrianto E, Fu J, Gao Z, Geng X, Gong B, Hanley K, He P, Kolomvatsos K, de CFL Lopes B, Ninic J, Previtali M, Rezania M, Ruiz-Lopez A, Sun J, Suryasentana S, Taborda D, Utili S, Whyte S, Zhang P
Publication type: Review
Publication status: Published
Journal: Computers and Geotechnics
Year: 2026
Volume: 189
Print publication date: 01/01/2026
Online publication date: 08/09/2025
Acceptance date: 26/08/2025
ISSN (print): 0266-352X
ISSN (electronic): 1873-7633
Publisher: Elsevier Ltd
URL: https://doi.org/10.1016/j.compgeo.2025.107604
DOI: 10.1016/j.compgeo.2025.107604
Data Access Statement: No data was used for the research described in the article.
