The use of Artificial Intelligence (AI) and Machine Learning (ML) have significantly increased over the last couple of years. ML is driven by the availability of data. Although geotechnical engineering is generally not among the first in picking up new technologies, there is a lot of data in our profession, and therefore, lots of opportunities to apply ML. In this article some examples are given of how ML can be used to facilitate and automate the geotechnical engineering workflow. Examples of soil identification, CPT interpretation, 3D soil stratification, parameter determination and surrogate modelling are given, and some other applications are mentioned.@en

The use of soil data is essential in geotechnical design, but in a preliminary project phase such data are usually limited to that inferred from field tests, like CPT, SPT or DMT. In previous publications by the authors and co-workers, it was shown how such data can be automatically processed into soil profiles and parameter sets for geotechnical finite element analysis. Another publication demonstrated the automated processing and creation of geological models as an intermediate step to more advanced 3D geotechnical modelling in a BIM / Digital Twin environment, which facilitates the link with other disciplines and stakeholders in a project. The major challenge of connecting layers across multiple 1D boreholes to form 3D soil layers is overcome by using a Machine Learning clustering algorithm. As a next step, the previously introduced Automated Parameter Determination (APD) method (connecting correlations using Graph theory) is applied based on averaged CPT parameters from all contributing layer sections. The result is an automated system that creates a complete 2D or 3D finite element model, including constitutive model parameters, for geotechnical analysis purposes. An automated system may be very efficient when exploring different design alternatives in an early stage of a project. However, it is important to emphasize the role and responsibilities of the geotechnical engineer in the design process, which requires the system to be transparent, verifiable, and adaptable. This paper describes the state-of-the-art of this ongoing research project. @en