Artificial Intelligence Pushes Mining Toward Autonomous, Self-Optimizing Operations

Highlights

• Researchers from Saveetha Institute reviewed 2020–2026 literature on AI applications across exploration, maintenance, processing, safety, and environmental monitoring in mining.
• Autonomous haulage is nearing commercial maturity, while mine-wide digital twins and fully self-optimizing mines remain at the Peak of Inflated Expectations.
• Many so-called digital twins are actually digital shadows—they monitor operations but cannot autonomously control them.
• For rare earths and critical minerals, AI-driven efficiency could improve orebody characterization and reduce waste without creating new mineral supply.
• Key barriers to deployment include proprietary data silos, site-specific geology, cybersecurity risks, capital costs, and workforce skill gaps.