BHP–Microsoft AI copper leaching: design and testwork shifts for mine planners
Reviewed by Joe Ashwell
First reported on International Mining – News
30 Second Briefing
BHP is working with Microsoft to deploy AI agents to accelerate discovery of advanced copper leaching chemistries, replacing slow, manual trial‑and‑error testing of millions of potential molecules. The system uses large‑scale computational screening to predict leach reagent performance on different ore types, aiming to improve copper recovery from low‑grade and complex ores where conventional sulphide flotation or heap leach kinetics are marginal. For mine planners and metallurgists, this could shift testwork programmes towards AI‑guided candidate selection, reducing lab cycles and de‑risking leach circuit design.
Technical Brief
- Similar AI-agent frameworks could be extended to other hydrometallurgical flowsheets, e.g. nickel, cobalt or rare earths.
Our Take
In our database, BHP’s copper items increasingly pair operational themes with decarbonisation, as seen in the Escondida and Spence renewable power agreements, so AI‑enhanced leaching is likely being evaluated not just for recovery uplift but also for its emissions and energy profile versus conventional processing.
The related AI screening work with Microsoft and Prescience Insilico on more than 500,000 candidate molecules suggests BHP is building an in‑house data asset around copper leach chemistry that could be portable across multiple brownfield operations rather than tied to a single project.
Prepared by collating external sources, AI-assisted tools, and Geomechanics.io’s proprietary mining database, then reviewed for technical accuracy & edited by our geotechnical team.
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