The next evolution of mining is knowledge, not data

Mining has never been short on complexity. A disruption in one part of the operation can quickly ripple across the business, affecting maintenance, plan throughput, and production. What has changed is the speed of those ripple effects and the growing interdependence of modern mining operations.

Demand for critical minerals continues to rise while operators face growing pressure to improve recovery, lower all-in sustaining costs (AISC), and maintain the highest safety standards. At the same time, experienced workers are becoming harder to replace, supply chains remain unpredictable in and beyond the site, and every operational decision carries greater consequences.

After more than 30 years working across manufacturing, supply chain, and industrial operations, I’ve learned the answer is rarely more technology or more data. The real challenge is turning information into knowledge that helps people make better decisions. With the advent of physical AI, more decisions and actions will increasingly become autonomous.

Today’s mines generate enormous amounts of information. Equipment, maintenance systems, processing plants, and supply chain operations all produce valuable data, but they rarely work together. One system may identify a problem, but it can’t always show how that problem will affect the rest of the operation. That’s the knowledge gap.

Consider a haul truck that’s beginning to show signs of failure. Most operations can identify the issue early. The harder question is what happens next. Should maintenance happen now or after the next production run? Are the required parts available already on site? If not, is it worth waiting for the next shipment? And what will that decision mean for production?

Those aren’t maintenance questions. They’re operational questions.

For years, we’ve tried to solve these challenges by giving people more dashboards and more reports. Better visibility helps, but it doesn’t connect maintenance planning with production or inventory. People still have to piece information together before they can act.

That’s where I believe Physical AI can make the biggest difference.

Physical AI is purpose-built for industrial operations. Its value isn’t simply generating another prediction. It’s helping people see the consequences of a decision before they make it, bringing together information that has traditionally lived in separate systems.

I’ve seen this firsthand working with some of the world’s largest mining operations. The organisations making the greatest progress aren’t focused on optimising one function at a time. They’re connecting the operation so maintenance, production, and supply chain work from the same understanding of what’s happening. The benefits extend well beyond equipment reliability.

Predictive maintenance becomes far more valuable when it’s aligned with prescriptive actions, coordinated with production schedules and spare parts availability. Planning improves because decisions reflect equipment condition and operational priorities, not just historical data. The same principle applies to safety. Real-time operational intelligence and computer vision can help identify unsafe conditions earlier, giving operators better information before a risk becomes an incident.

Technology doesn’t replace experience. Mining will always depend on the judgment of the people who know the operation best. Physical AI should strengthen that expertise, not replace it.

Mining has always rewarded better decisions. The companies that lead the next era won’t necessarily have more data than everyone else. They’ll be the ones that turn information into knowledge. and knowledge into action.

Read the article online at: https://www.globalminingreview.com/mining/11092026/the-next-evolution-of-mining-is-knowledge-not-data/