By Glenn Kerkhoff

Data has become the backbone of modern industrial performance because it enables continuous optimisation, advanced automation and resilient decision-making. In mining, the growth of times-series, transactional, geospatial location and business systems data has made integrated, high-fidelity information environments essential for achieving competitive advantage.

Current industry practice is shifting toward unified data infrastructures that consolidate different types of data into a common unified data repository. This foundation supports emerging capabilities such as digital twins and AI-driven simulation models, which allow operators to test possible scenarios, derisk decisions and optimise production in real time.

Mining companies are increasingly moving toward cloud-based platforms with operational technology (OT) and/or IT integration and information sharing, allowing them to break down siloes within their organisation and improve overall efficiency using an integrated data and insights approach.

AVEVA’s technology is centred on advanced OT solutions designed to enhance performance across mining, mineral processing, transportation, logistics, metallurgy and broader supply-chain operations. With decades of industry expertise, AVEVA’s technologies are engineered to enhance asset reliability and availability, improve use and efficiency, boost productivity and optimise overall equipment effectiveness and end-to-end value-chain performance.

Solutions, such as AVEVA CONNECT, provide industrial intelligence support, enabling scalable data ingestion, harmonisation and analytics across diverse technology ecosystems, directly underpinning sustainability objectives.

This includes optimising energy and power consumption, monitoring workplace conditions to strengthen health and safety outcomes, lowering greenhouse-gas emissions and limiting environmental impacts across industrial operations.

A cloud-native industrial intelligence platform, CONNECT allows users to access unified and trusted industrial and operational information in an open platform across their enterprise. It provides a single source of truth in real-time and uses advanced analytics to drive operational data insights to improve performance and enhance sustainability.

A large South African mining company with deep underground operations recently deployed AVEVA’s CONNECT to monitor the performance of its dewatering operations. It identified several areas where maintenance and operations could be improved, driving a sizable positive impact on performance, power reduction and cost. Using AVEVA CONNECT, the mining company identified 600 000 kWh of energy savings a month, equating to monthly savings of about $50 000.

Navigating Complex, Data-Heavy Environment

Combining AI and machine-learning technologies offers the most effective path to overcoming mining’s unique operational, environmental and integration challenges.

As mining operations become more complex, companies must adopt advanced technologies to enhance productivity, maintain product quality and reduce waste and environmental impact. AI can address many operational challenges, but its effectiveness depends on a high level of instrumentation, automation and digitalisation.

Without reliable and robust data infrastructure, AI models cannot operate effectively in industrial environments. This makes the convergence of IT, OT and engineering technology essential.

Highly integrated systems must be extremely robust, as human involvement may be reduced in certain workflows. A degree of human oversight will remain necessary to ensure technology behaves as expected, while still enabling personnel to focus on higher-value problem solving rather than routine operational tasks.

Mining sites are also often exposed to extreme temperatures, high vibration, corrosion, dust and debris, all of which can impair sensors, reduce measurement accuracy, or introduce data biases. Automation combined with real-time data capture helps mitigate these issues by predicting maintenance needs and compensating for data gaps using historical information or digital-twin simulations.

For Safety Sake

AI and predictive analytics are enabling operators to anticipate risks before they escalate, identifying subtle changes in equipment performance and operating conditions that could lead to dangerous failures. Simultaneously, integrated platforms are bringing together data and analytics from across the mine into unified insights. This real-time visibility helps teams detect abnormal situations faster and coordinate safer responses. Digital workflows for servicing heavy equipment, combined with mobile tools that keep workers connected to procedures and expert guidance, further reduce exposure to high-risk tasks.

The result is a shift from compliance-driven safety to a culture of incident-prevention, powered by connectivity and intelligence. For mining companies, their digital transformation is not just about technology – it is about protecting lives, sustaining productivity and reinforcing trust in an industry where safety is a top priority.

Where to Next?

Over the next five years, mining will be increasingly shaped by advancements in AI, automation and integrated edge-to-cloud data architectures. Operations will continue to modernise through the maturation of technologies that unite real-time descriptive, predictive and prescriptive asset-management insights, enabling more streamlined processes and more efficient operational control. AI-driven analytics will further accelerate the transition from reactive to proactive asset management, resulting in improved performance and equipment reliability across the value chain.

Automation of heavy mobile equipment will continue to advance, with autonomy becoming a key driver of productivity and operational consistency. Additionally, the adoption of robotics will expand as miners look to enhance safety and improve the efficiency of high-risk or repetitive tasks.

Mining executives need a clear, future-focused OT roadmap for AI and digital transformation to ensure systems are secure, interoperable and scalable across many remote locations. AI should be integrated – not dealt with as a stand-alone isolated project – so it delivers measurable efficiency, productivity, safety and environmental gains.

While flexibility – made possible through modular solutions – is critical, so is workforce readiness: embedding digital skills and remote collaboration into everyday operations ensures long-term, successful digital and AI adoption.

The right strategic partner adds value by bridging vision and execution, with digital transformation in mining requiring significant collaboration. To make advanced solutions truly effective, technology providers must work together with mine operators, original-equipment manufacturers and contractors from the earliest stages of design to commissioning, handover, ramp-up and optimisation. This collaboration turns technology into a practical advantage, creating mines that are safer, smarter and future-ready.

* Glenn Kerkhoff is the global industry principal for Mining, Metals and Minerals at AVEVA