Foundations for AI in Mining

The Foundations for AI in Mining project produced a white paper that provides a unified understanding of the basics of AI in mining that cuts through the hype, clarifies what methods are useful and identifies how they can be applied.


Articulate a clear and unified understanding and framework of what artificial intelligence (AI) is and how it can benefit the mining industry.


This white paper offers a framework to assist mining companies with successfully implementing AI techniques within their business. This includes:

    • Discussion of the terminology surrounding AI
    • A maturity model to enable companies to plan their AI strategy
    • The high-level steps needed to introduce AI into an organization

Business Case

AI has quickly become recognized as an opportunity to harness new technology for operational efficiency, but there is still general confusion about what it is, and there are many questions about its applications in mining.

Media announcements about new uses of AI often create hype around spectacular features but rarely describe the basics. Resources covering these basics are therefore needed to cut through the hype and clarify what methods are useful, and for what circumstances they can be applied.

Participating Companies

Agile GeoScience, Alex Atkins & Associates, Ambuja Cements, Andrés Bello National University, Antofagasta Minerals, Augmented Analytics, Barrick Gold, Bechtel, BHP, Boliden, C&O Servicios profesionales, Canary Systems, Canvass Analytics, Caterpillar, CITIC Pacific Mining, COREM, CSIRO, Curtin University, Datinfact, Deloitte, Department of Mines, Industry Regulation and Safety (DMIRS), Digital Mine from GE Transportation, a Wabtec Company, Ecole Polytechnique, Emergency Response Consulting, Enaex, ERAMET-SLN, ESG Solutions, Exergia, Flanders Electric, Flinders University, Fourdplan, Fundación Chile, Geological Survey of South Australia, Geomodelr, Global Insertion, Global Research, Hatch, Haultrax, Hitachi, Hudbay Minerals, IBM, Infosys, ISCTE – Lisbon University Institute, JVA, Larrain & Asociados, Les Entreprises Bektex, Liebherr, LKAB, Luleå University of Technology, Ma’aden, McGill University, Minetec, National Research Council Canada, Natural Resources Canada / Government of Canada, Newcrest, Newmont Goldcorp, Newtrax, Nutrien, Odgers Berndtson, Open World, Optika Solutions, Option, Organum Technology, OZ Minerals, Paradyn Systems, PETRA Data Science, Phoenix Contact, Resolution Systems, Rio Tinto, Rithmik Solutions, Rock Tech Centre, Rockwell Automation, Roy Hill, SafeAI, Santoencanto, Schneider Electric, Seed AI, Seequent, Seyo, Siemens, Sinese, Spectris Advance Mining, SRK Consulting, Stantec, Stratalis Group Consulting, Stratum AI, Symbiotic Innovations, Symboticware, Teck, TransformAction, TriStar Gold, Unearthed Solutions, University of Adelaide, University of South Africa, University of South Australia, Vale, Vedanta Resources, Wood, Yamana Gold, Zettascale Data Consulting

Project Updates

White paper published!

Foundations of AI: A Framework for AI in mining


Thank you to all who participated in developing this useful document.Read it here...

Paper in editing


The project group finished developing the content in June and the paper is now in editing. Stay tuned for more details about publication. In the meantime, here is a preview of one of the visuals included in it. Read more...

Use Case Survey

Have your say on what AI use cases are most important


A key component of this project is to collect use cases and examples to illustrate key concepts, demonstrate what is possible and inspire the industry. We have developed a brief survey to help determine what would be most relevant and useful to include in the project. Read more...