Artificial intelligence is being rolled out across mines for tasks such as mill optimisation, predictive maintenance and fleet dispatch, but its success still hinges on experienced operators, metallurgists and geotechs defining constraints and validating outputs. Vendors are pairing machine-learning models with domain-specific tools – for example, digital twins of crushers and grinding circuits, or AI-assisted short-interval control in fleet management systems – to capture tacit knowledge from senior crews. The message for sites is to treat AI as an augmentation layer on existing control, planning and reconciliation workflows, not a plug‑and‑play replacement for human judgement.

Vulcan Energy’s Lionheart lithium project in Germany’s Upper Rhine Valley is advancing as a geothermal brine operation backed by more than $3 billion in international funding to support Europe’s energy and critical raw material resilience. The project targets lithium extraction from deep geothermal reservoirs, pairing baseload renewable power generation with direct lithium recovery to supply European battery and automotive supply chains. For geotechnical and process engineers, the scheme centres on managing high-temperature brine production wells, reinjection strategies, and closed-loop fluid handling to minimise surface footprint and chemical consumption.

AI-driven data centres are emerging as both customers and competitors for miners, with Meta’s 1‑GW, US$9.5‑billion Sturgeon County facility and a 932‑MW dedicated gas plant in Alberta illustrating how hyperscale loads can strain grids and local support near projects like E3 Lithium’s Clearwater brine operation. Alberta has imposed a 1,200‑MW cap on large new connections to 2028, while BC Hydro is rationing up to 400 MW for tech projects but exempting mining, forestry and LNG. S&P Global warns copper demand could reach 42 Mt by 2040, yet rising power prices, grid queues and competition for electricians and engineers risk delaying mine and smelter investments.