November 10, 2025
At IMARC 2025, Razor Labs Director of Marketing Liel Anisenko sat down with Jake Thornton, Director, Mining Operations Advisory at KPMG Australia, for a candid conversation on one of mining’s biggest challenges: how to turn the promise of digital transformation into operational reality.
Drawing on lessons from sites across Australia, South Africa, and beyond, they explored what it truly takes to get mining teams to trust and adopt advanced technologies like AI-based predictive maintenance.
Technology Isn’t the Problem – Adoption Is
Jake opened with a sharp observation: mining companies are no longer focused on throwing more tools at the problem. The industry is shifting from a “cost-cutting” mindset to doing more with what they already have – which means better productivity, more reliable maintenance, and fewer failures.
But implementing technology alone isn’t enough.
“The tool delivers ROI,” Jake said, “but change management makes it stick.”
He shared how KPMG works with miners to embed new systems in real workflows – aligning digital tools to real business problems, training frontline teams, and ensuring leadership buy-in. Without that, even the best tools won’t yield results.
The Trust Barrier: Why Change Management Fails
Liel echoed the challenge: “We often hear people on site say, ‘You’re trying to replace us.’”
The truth, she emphasized, is that Razor Labs’ AI solutions are designed to make work easier, safer, and more efficient — not eliminate jobs.
In fact, Liel highlighted a case at a vanadium site where trust in Razor Labs’ system helped prevent a major failure. Despite a recent shutdown and no manual indicators of a problem, the AI detected an issue with a ball mill. Because the local team had built trust with Razor Labs, they listened, investigated — and discovered damage that would have otherwise gone unnoticed until a costly failure occurred.
Mining Needs People + AI – Not One or the Other
A central theme of the session was collaboration between people and technology. Jake stressed that AI doesn’t replace engineers – it supports them. But adoption depends on transparency, co-design, and clear communication of ROI.
Liel added a powerful quote:
“AI will never replace mining professionals. But mining professionals using AI will replace those not using it.”
With looming workforce shortages in the sector (50% retirement forecasted in the U.S. by 2030), the ability to capture expertise, automate insights, and preserve institutional knowledge will become a key success factor.
From Pilots to Real Impact: Lessons from the Field
Both speakers emphasized the importance of starting small, proving value, and scaling fast.
Jake shared a case of a coal operation that successfully adopted a site-wide data strategy because leadership drove it from the top, engaged operations early, and tied it directly to business KPIs. Liel referenced Glencore’s “entrepreneurial” approach – defining the problem first, then testing and scaling only what works.
Looking Ahead: The Road to Optimized Maintenance
As demand for critical minerals surges, the pressure to modernize mine operations is only growing. The session concluded with a shared vision:
Mining companies that combine AI, change management, and a people-first approach can dramatically reduce unplanned downtime, optimize maintenance, and unlock billions in potential savings.
