AI helping BHP understand operations in new ways and act earlier, van Jaarsveld says
Artificial intelligence (AI) is, BHP says, increasingly shaping how the company operates, as it looks for practical ways to improve safety, reliability and performance while helping meet rising demand for critical minerals.
From supporting teams to identify new mineral deposits, to running large processing plants and transport networks, AI is moving beyond experimentation and becoming part of day-to-day operations across BHP’s global portfolio, it notes.
Johan van Jaarsveld, BHP Chief Technical Officer, says: “AI is no longer a future concept for BHP; it is increasingly part of how we run our operations. Our focus is on applying it in practical, governed ways that support our teams in achieving safer, more productive and more reliable outcomes.”
Across BHP, AI is being applied in practical ways along the mining value chain – from helping find resources, to supporting processing plant operations, to improving reliability across large, interconnected systems. These applications are designed to help teams manage complexity and variability in operations that run continuously and at scale.
In exploration, AI and advanced analytics are being used to help geoscientists analyse large volumes of geological data more efficiently. By reviewing decades of historical information alongside new data, these tools can help teams identify areas of interest earlier and with greater confidence, BHP says. This supports better decision making and can help reduce exploration risk, while decisions on where and how to invest remain with people.
One of the biggest challenges in mining is natural variability, particularly changes in the type and hardness of ore, which can affect how smoothly material moves through a processing plant.
At Escondida in Chile, the world’s largest copper mine, AI-supported digital models are helping operators better understand how changes in ore characteristics or operating settings are likely to affect plant performance, the mining company says. In simple terms, these digital models allow teams to test changes virtually, using live and historical data, before applying them in the real plant.
AI is also being used to support reliability across mining and transport systems, where even short disruptions can have a significant impact.
For example, computer vision systems are used at operations in Chile and Western Australia to help detect issues such as spillage, oversized material or foreign objects on conveyors, crushers and rail loading systems. Using existing camera infrastructure, these tools can alert teams early and, in some cases, trigger pre-programmed automatic responses to help prevent equipment damage and avoid unplanned downtime, BHP says. This helps keep material moving safely and consistently, while reducing the need for teams to work in higher-risk situations.
AI is also supporting safety outcomes for teams on the frontline. For example, a voice-to-text mobile application allows employees to log hazards instantly while in the field. Reports are automatically geotagged and linked to historical incident data, providing rapid digital risk assessments that help teams respond sooner and prioritise controls, the company says.
BHP says it has been applying AI and advanced analytics across its operations for several years, with use increasing as data quality, platforms and internal capability have improved. As this work continues, teams across the business are identifying further opportunities where AI can support day-to-day operations, sharing what works and extending proven approaches where appropriate, supported by strong governance and clear accountability.
van Jaarsveld concluded: “AI is helping us understand our operations in new ways and act earlier, with greater confidence. What excites us is the scale of opportunity ahead as we continue to apply these tools responsibly – learning, improving and expanding what’s possible across our operations.”
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