MINING
GenAI cuts mining maintenance costs by 10 %
Unplanned maintenance eats up mining budgets. Deploying advanced GenAI tools can slash these costs, boost efficiency and transform operations by integrating predictive systems, optimising inventory and supporting field teams – all while reducing downtime.
By Puso Thahane, Partner, and Akash Singh, Principal IT Architect at Boston Consulting Group( BCG)
Unplanned maintenance now accounts for 60 % of total mine maintenance spending. However, innovative solutions – specifically, deploying the right Generative AI( GenAI) tools – can bring down those costs.
When mines deploy predictive maintenance systems, they tend to do so in isolation and rely on static thresholds. This lack of integration limits visibility and prevents coordinated responses, which erodes productivity and efficiency. According to recent research by Boston Consulting Group( BCG), the right GenAI tools can transform predictive capabilities and cut costs by 10 %. That’ s because unlike traditional fixed-schedule methods based on legacy telemetry data, GenAI solutions can synthesise structured and unstructured data to perform smart diagnostics, support real-time parts ordering, or augment in-field support.
The differentiator is GenAI’ s ability to interpret patterns and contextualise valuable outputs from vast datasets. An orchestration layer powered by the right technology can process information from every sensor feed and every set of technician notes seamlessly – and across sites. Using this approach, we have seen mining companies increase fleet availability by 15 % within six months, improve technician job effectiveness, and optimise technician job durations by up to 20 %.
GenAI in mining is not a distant aspiration. Modular, mine-ready solutions are already available …
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