How artificial intelligence is reshaping geotechnical engineering skills

Source Domain: www.geplus.co.uk

As AI adoption grows across site investigations, modelling and construction, the profession faces a critical skills shift, alongside ethical questions about oversight and accountability.

Dependency on underground engineering is soaring. The global tunnel construction market alone is forecast to grow from £88bn to over £160bn in the next decade. At the same time, expanding sectors such as renewable energy and offshore wind are creating a fresh reliance on geotechnical investigations, putting additional pressure on firms to deliver faster designs.

As geotechnical companies scale up their capacity to meet this demand, artificial intelligence (AI) tools are being deployed to assist with routine desk tasks and accelerate some of the most time‑consuming processes, such as manual extraction of data from borehole logs, laboratory reports and field notebooks. Additionally, new specialist roles are emerging which require skills from different disciplines.

This steady rollout of AI is changing how geotechnical contractors and consultancies work – and what skills they now expect from engineers. But as intelligent systems take over human tasks, the shift raises ethical questions about how far businesses can push the technology.

Shaping daily work

AI adoption has more than doubled among geo-professionals over the past five years. According to a 2025 survey of over 1,000 international professionals across geotechnical jobs by geoscience software company Seequent, 51% of respondents use AI in their jobs – a sharp increase from 19% in 2020.

Additionally, 48% said they now use data science scripting (2020: 30%), followed by 36% who use machine learning (2020: 25%) and 35% who use advanced analytics (2020: 25%). Only a quarter (23%) of respondents said they don’t use any of those tools at work (2020: 45%).

Geotechnical engineers routinely use large language models (LLMs), such as ChatGPT, Claude or Microsoft Copilot, to automate workflows, analyse large datasets, build…

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