In mining, every hour of downtime carries a very high price.
Real cases — including operations in Chile — of how leading mining companies use AI to reduce equipment failures, optimize extraction, improve safety, and save millions in operating costs.
Chilean mining is already in this conversation. The gap between those who move and those who wait is growing.
The AI market applied to mining is worth US$5.4 billion in 2024 and grows at 20.6% annually. Major global operations — including those operating in Chile — have been integrating AI for years in predictive maintenance, autonomous fleets, and process optimization. Codelco, the world's largest copper producer, already operates AI-based classification systems at Chuquicamata. BHP uses AI at Escondida to reduce water and energy consumption.
greater extraction efficiency in BHP's autonomous truck fleets in Australia, with 20% reduction in operating costs
of additional copper per year that Codelco obtains at Chuquicamata through machine learning extraction optimization
reduction in unplanned downtime with AI-based predictive maintenance, according to multiple global operators
What other mining operations have already achieved
Not endless pilot projects. Production implementations, in real-scale operations.
Codelco: AI-based copper classification at Chuquicamata
MINERAL PROCESSINGCodelco — Sistemas EPCM y COBRA, Chuquicamata, Chile
Codelco implemented AI-based mineral classification systems with 95% effectiveness — far exceeding manual classification methods. The system distinguishes in real time which material is worth processing and which is not, optimizing plant usage and reducing processing of low-grade material. The direct result is additional production equivalent to 8,000 metric tons of copper per year, at Chuquicamata alone.
mineral classification effectiveness
additional copper annually at Chuquicamata alone
BHP Escondida: AI to recover water and energy in Chile
OPERATIONAL SUSTAINABILITYBHP — Escondida Mine, Atacama, Chile — in partnership with Microsoft Azure, since 2022
BHP integrated AI into Escondida's concentration processes, the world's largest copper mine. The models adjust concentrator operational parameters in real time to maximize copper recovery and reduce resource consumption. Since 2022, the operation has saved more than three gigaliters of water and 118 gigawatt-hours of energy — in a region where both are critical resources.
of water saved since 2022
of energy saved in the same period
Rio Tinto: autonomous fleet operating at 99% availability
OPERATIONS AND LOGISTICSRio Tinto — Pilbara, Australia — fleet of more than 200 autonomous trucks
Rio Tinto operates in Pilbara the world's largest autonomous truck fleet, managed by AI. The vehicles optimize routes, manage loads, anticipate maintenance, and respond to safety alerts autonomously. The result is not just efficiency: it's consistency. The fleet operates at 99% availability, without fatigue, without human driving error.
autonomous fleet availability
productivity vs. manual operation
time in geological exploration
Predictive maintenance: anticipating failures before they occur
EQUIPMENT MAINTENANCEMultiple operators — including Codelco and Freeport McMoRan — 2024
Unplanned maintenance is one of the largest hidden costs of any mining operation. AI systems analyze sensor data from critical equipment — trucks, mills, pumps, conveyors — to detect patterns that precede failures, hours or days before they occur. Codelco uses Uptake to monitor equipment health at Ministro Hales. At Freeport McMoRan, AI-based gas detection systems respond 60% faster to risk events.
unplanned downtime in operations with AI
faster response to risk events (Freeport)
Three concrete starting points
Not what could happen. What operations with a similar profile are already executing.
Predictive maintenance on critical equipment
Trucks, mills, compressors, conveyors. Each one already has sensors generating data. AI can learn normal operating patterns and detect anomalies before they become failures. In an operation where one hour of unplanned downtime can cost hundreds of thousands of dollars, anticipating even 20% of failures delivers direct and measurable returns.
Highest ROI potential — start with a data diagnosticProcess optimization in the concentrator plant
Grinding, flotation, and concentration processes have variables that operators adjust from experience. AI models can analyze in real time how each variable affects recovery and recommend adjustments no human can process at that speed. The result is more mineral recovered from the same material already entering the plant — without additional infrastructure investment.
Direct impact on recovery and processing costsTechnical knowledge assistant for shift teams
Equipment manuals, operating procedures, failure history, safety protocols. All that information exists but is scattered. An AI assistant lets any operator or supervisor access the right information in seconds — without depending on the shift expert being available. Reduces errors, accelerates decisions, and preserves institutional knowledge.
Fast to implement — high impact on safety and continuityWe don't sell AI,
we sell adoption.
We understand how your company works today and build the bridge so AI does the heavy lifting, giving your team back time for strategic tasks.
We audit processes, interview teams and map the highest-impact opportunities. You leave with a prioritized roadmap.
We build the first agent or workflow in production. We measure ROI from day one. No PowerPoints, only results.
We train teams to own the technology. The agent becomes their tool, not ours.
We expand what works. New processes, new teams. AI stops being a project and becomes an operational advantage.
We don't sell AI. We sell tons that don't get lost.
This conversation is about listening to you. We want to understand how the operation runs today, where production is lost, and which processes could work with more intelligence.