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AI Readiness Audit — Mining and Metals
Score how ready Mining and Metals is to deploy practical AI — and see the highest-ROI use cases for your sector.
Where AI pays off in Mining and Metals
- Predictive maintenance on haul trucks, shovels, mills, and crushers — using OEM telemetry and condition-monitoring data to schedule before failure.
- Autonomous haulage and drilling at scale — and the operating model redesign that makes those deployments actually deliver.
- Ore body modeling and grade control AI — improving recovery and reducing dilution by closing the loop between drilling, blasting, and processing.
- Process control optimization at the mill — AI on flotation, grinding, and leaching circuits to lift recovery and reduce reagent use.
Strategy & Use Cases
Whether AI is pointed at a real, measurable business problem.
More tools for Mining and Metals
AI Readiness Audit
Score process clarity, data readiness, team adoption, and guardrails before investing in AI.
Sample output
67/100 → pilot with control, not full rollout
Digital Transformation Audit
Assess KPI clarity, reporting, tool alignment, ownership, and automation maturity.
Sample output
52/100 → foundation gaps in metrics and handoffs
Supplier Cost Audit
Assess supplier diversification, cost visibility, pricing competitiveness, and negotiation strength.
Sample output
65/100 → 3-5% cost reduction opportunity
Cost of Manual Work — Mining and Metals
Quantify the annual cost and people-weeks lost to repetitive manual work — and the automation payback.
Build vs Buy — Mining and Metals
Compare the multi-year total cost of SaaS subscriptions against a custom build — with a clear build, buy, or hybrid recommendation.
Operations Maturity Audit — Mining and Metals
Score how mature your operations are across metrics, handoffs, tooling, ownership, and automation — and pinpoint the weakest link to fix first.