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Literature review

Artificial intelligence transformations in geotechnics: progress, challenges and future enablers

Sheyl B.

Department of Engineering, University of Cambridge, Cambridge, UK bbs24@cam.ac.uk

Anagnostopulos K.

School of Computing Science, University of Glasgow, Glasgow, UK

Bakli R.

James Watt School of Engineering, University of Glasgow, Glasgow, UK

Chiantia M. O.

School of Science and Engineering, University of Dundee, Dundee, Scotland, UK; Department of Earth and Environmental Sciences, University of Milano-Bicocca, Milan, Italy

Febrianto E.

James Watt School of Engineering, University of Glasgow, Glasgow, UK

Fu Ts.

School of Engineering and Materials Science, Queen Mary University of London, London, UK

Gao Ch.

James Watt School of Engineering, University of Glasgow, Glasgow, UK

Gen S.

School of Engineering, University of Warwick, Coventry, UK

Gun B.

College of Engineering, Design and Physical Sciences, Brunel University of London, London, UK

Khenli K.

Chemical Engineering (BEng Hons) programme, University of Edinburgh, Edinburgh, UK

Khe P.

School of Science and Engineering, University of Dundee, Dundee, UK

Kolomvatsos K.

Engineering and Computer Science, University of Thessaly, Volos, Greece

Lopes B.K.F.L.

Department of Civil and Environmental Engineering, University of Strathclyde, Glasgow, UK

Ninich Y.

School of Engineering, University of Birmingham, Birmingham, UK

Previtali M.

School of Science and Engineering, University of Dundee, Dundee, UK

Rezaniya M.

School of Engineering, University of Warwick, Coventry, UK

Ruis-Lopes A.

Sequent (The Bentley Subsurface Company), Christchurch, New Zealand; Faculty of Engineering, Imperial College London, London, UK

Sun Ts.

James Watt School of Engineering, University of Glasgow, Glasgow, UK

Suryasentana S.

Department of Civil and Environmental Engineering, University of Strathclyde, Glasgow, UK

Taborda D.

Faculty of Engineering, Imperial College London, London, UK

Utili S.

School of Engineering, Newcastle University, Newcastle upon Tyne, UK

Vayt S.

Geowynd company, London, UK

Chzhan P.

Department of Civil and Environmental Engineering, National University of Singapore, Singapore

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DOI: 10.58339/2949-0677-2025-7-4-52-80

UDC: 004; 624.131

Funding: No information

For citation: Sheil B., Anagnostopoulos C., Buckley R., Ciantia M.O., Febrianto E., Fu J., Gao Z., Geng X., Gong B., Hanley K., He P., Kolomvatsos K., Lopes B.C.F.L., Ninic J., Previtali M., Rezania M., Ruiz-Lopez A., Sun J., Suryasentana S., Taborda D., Utili S., Whyte S., Zhang P. Transformatsii v geotehnike s pomoshch'yu iskusstvennogo intellekta: dostizheniya, problemy i perspektivy (adapt. per. s angl.) [Artificial intelligence transformations in geotechnics: progress, challenges and future enablers (adapted translation from English into Russian)] // Geoinfo. 2025. T. 7. № 4. S. 52–80. DOI:10.58339/2949-0677-2025-7-4-52-80 (in Rus.)

Article in RSCI: No information

Keywords: geotechnics; geotechnical investigations; artificial intelligence; intelligent site investigations; soil behavior modeling; geotechnical design optimization; machine learning; human-machine interaction; interdisciplinary approach; ethical aspects; legal aspects.

30 December 2025