Integrating artificial intelligence and data science in environmental geotechnics: a review

Environmental geotechnics plays a critical role in the development of sustainable and resilient infrastructure systems, while addressing global challenges, such as climate change and resource depletion. This review paper explores the integration of artificial intelligence (AI) and data science (DS) within environmental geotechnics, and their potential to advance the field while supporting the United Nations Sustainable Development Goals (SDGs). By leveraging diverse data sources, including sensors, satellites, laboratory testing and case-history projects, AI-driven and data-centric approaches can support evidence-based decision making for the design, construction and maintenance of climate-resilient infrastructure. The integration of AI and DS enables engineers to efficiently interpret complex datasets, anticipate risks, optimise resource use and respond proactively to evolving ground conditions throughout infrastructure lifecycles. These capabilities contribute to enhanced risk mitigation, environmental protection and sustainable infrastructure development. The synergy between AI–DS and environmental geotechnics directly supports key SDGs, including clean water (SDG 6), industry, innovation and infrastructure (SDG 9), sustainable cities and communities (SDG 11) and climate action (SDG 13), thereby fostering more sustainable and adaptive approaches to infrastructure and environmental management.