How GenAI is reinventing mine maintenance in South Africa

Akash Singh, Platinion principal IT architect at BCG Johannesburg. Image supplied.

Puso Thahane, partner at BCG Johannesburg. Image supplied.

While at the 2026 Investing in African Mining Indaba in Cape Town, Boston Consulting Group’s (BCG) Dr Akash Singh, Platinion Principal IT Architect at BCG Johannesburg, and Puso Thahane, partner at BCG Johannesburg, talked to Bizcommunity about how GenAI is reinventing South African mine maintenance.

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How is GenAI reinventing mine maintenance?

GenAI is reinventing mine maintenance by synthesising structured and unstructured data, such as sensor feeds and technician notes, to predict failures, run diagnostics, order parts in real-time, and coordinate in-field support.

It uses an orchestration layer that connects people, equipment, parts, and real‑time data to enable coordinated and increasingly autonomous maintenance operations.

What are some of the benefits of using AI for mine maintenance?

When applied in maintenance, AI has been shown to increase fleet availability by up to ~15% and reduce maintenance costs by ~10%.

The duration of technician job execution can also be reduced by up to 20% as AI enhances visibility, integrates previously siloed systems, and enables faster, more accurate decisions on mining sites.

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What will its impact be on mine maintenance workers? Will it eventually replace them?

GenAI is designed to augment, not replace, mine maintenance workers.

It is most effective when embedded into existing workflows and used to create early predictions of equipment failure, helping technicians plan work orders, order parts proactively and execute work more efficiently with better diagnostics and coordinated support.

How can mining companies integrate AI into their operations?

Companies can integrate AI by creating an orchestration layer that connects all maintenance data, integrating GenAI platforms with ERP, EAM, and IT/OT systems, and adopting modular solutions that don’t require advanced digital maturity.

Organisational readiness and embedding GenAI into established workflows are essential for successful adoption.

Beyond mine maintenance, how else can AI improve health and safety standards at mines?

By improving visibility and coordination across equipment, people, and data, GenAI reduces the safety risks caused by unplanned maintenance and isolated predictive systems.

Better diagnostics and real‑time support help prevent hazardous breakdowns and enable safer technician interventions.

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What will mine maintenance look like in the next five years?

Mine maintenance will continue to shift toward automated maintenance ecosystems, where GenAI can autonomously predict possible equipment failures, identify required parts and spares and repair equipment and link to existing work order management systems to support human-led scheduling, parts coordination, and work-order execution.

Maintenance operations will become more integrated across sites, with technicians relying on real-time data for diagnostics, planning, and work execution support.

The performance gains seen today, 15% availability, 10% cost savings, and 20% job optimisation, are expected to become standard.