An Opportunity for Regeneration

Beth Williamson, Head of Sustainable Equity Research at Calamos Investments, explains how investors can help the mining industry harness AI to improve its sustainability.

There is an under-appreciated risk to the energy transition: The supply of clean energy depends on mined natural resources that are steeped in ecologic, geopolitical, and governance challenges. A recent World Bank report estimates that over three billion tons of minerals are required to match the energy production and storage demands of a ‘2-degree future’ by 2050.

Despite the increasing global appetite for minerals – fueled largely by AI demand – long-term investors should not be dismissive of risks associated with the mining sector and specific companies within it.

Many sustainable investors approach direct mining investments with caution because of the industry’s ecological footprint, labour practices, and operational risks. Sustainable investors also often recognise that the shift to renewable energy and low-carbon technologies must not compromise the environment we aim to conserve, and mining companies need to address their ‘dirty’ profiles to ensure long-term financial success.

There are opportunities for investors to participate in the growth of more ‘sustainable’ mining while mitigating ecological and societal risks – for example, through companies that are providing products and services to the mining industry to help automate and reduce the environmental cost of production with low-carbon solutions.

Moreover, AI may well be one of the most powerful secular growth themes the world has seen, with cascading effects across all sectors of the economy, including mining. AI has the potential to improve the environmental impact, health, and safety of the mining industry.

Regarding the critical minerals sector, two issues are at the forefront:

• The exponential growth in AI applications is driving unprecedented demand for minerals like lithium, cobalt, and rare earth elements needed in advanced computing and energy storage systems.
• AI is revolutionising mining operations themselves.  According to the World Economic Forum, the global market for autonomous mining equipment, for example, is projected to grow from US$3.1 billion in 2020 to US$6.2 billion by 2026.

Efficiency, safety, and environmental and social impacts

The adoption of AI in mining represents a fundamental shift toward safer, more efficient, productive, and sustainable operations. Thus, mining extraction companies using AI can be well-aligned with sustainable investment criteria. We are encouraged to see mining companies using AI to improve the efficiency and safety of the mining industry while reducing the industry’s environmental and social impacts. In fact, we have identified ten ways in which mining companies can harness AI to manage environmental and social risk while improving a company’s growth potential.

1. Advanced mineral exploration – Machine learning models now integrate geospatial data, satellite imagery, and historical exploration records to pinpoint untapped mineral deposits.
2. Autonomous mining equipment – Autonomous vehicles and equipment are becoming more sophisticated, with AI enabling real-time decision-making and adaptability.
3. Predictive maintenance and asset management – AI-driven systems predict equipment failures with remarkable accuracy by analysing sensor data and performance records. This minimises downtime, reduces maintenance costs, and extends the lifespan of critical machinery.
4. Enhanced ore processing – AI systems increase efficiency by optimising the separation and refining of minerals. AI algorithms analyse ore grades in real time and adjust processing parameters to maximise recovery rates and minimise waste.
5. Real-time monitoring for environmental compliance – By analysing data from Internet of Things (IoT) sensors, drones, and satellite imagery, AI systems identify potential water contamination, detect dam instability, and other environmental risks.
6. Carbon footprint reduction – AI helps mining companies meet sustainability goals, with solutions that include optimising energy usage and reducing greenhouse gas emissions.
7. Workforce augmentation and training – VR and AR systems are integrated with AI for training workers. This ensures workers are prepared for the latest technologies and trained in safety protocols.
8. Digital twin technology – Digital twins are virtual replicas of physical assets. Powered by AI, they provide real-time simulations of mining operations, allowing mining companies to test scenarios and optimise processes without disrupting actual operations.
9. Community engagement – AI may be able to predict potential community issues before they escalate, allowing companies to take preventive measures. This includes forecasting environmental impacts and planning mitigation strategies.
10. Enhanced supply chain management – AI is transforming supply chain operations by optimising logistics and inventory management. Predictive analytics tools enable companies to anticipate demand and streamline the supply chain, reducing costs and improving reliability.

Investing in innovation

Investors can aid in the regeneration of the mining industry by focusing on companies utilising AI to help make mining operations more sustainable through automation, improved extraction methods, and reduced environmental impact, rather than on mining extraction companies themselves. Below, we offer several examples of such businesses.

Epiroc (EPOKY) leverages AI to enhance mining operations through predictive maintenance, geospatial data analysis, and autonomous equipment. It uses AI for real-time environmental monitoring and digital twin technology to optimise processes and improve decision-making. This integration of AI promotes efficiency, cost reduction, and sustainability in the mining industry.

Atlas Copco (ATCO-A) advances AI in mining through its SMART LINK system for air compressor management and the Service Master project for monitoring production processes. Its 6thSense initiative integrates smart connected products to enhance automation and digitalisation in mining operations.

Bentley Systems (BSY) enhances mining efficiency with AI-driven solutions like digital twins and advanced data analytics, providing real-time simulations for better decision-making and process optimization. Its AI tools also analyse geospatial and geological data to improve mineral discovery, production, safety, and sustainability.

Siemens (SIEGY) is a major provider of industrial automation and digitalisation solutions for mining operations. They offer comprehensive systems for mine electrification, automation, and digital twin technology that helps optimise mining processes and improve safety.

Rockwell Automation (ROK) specialises in mining automation and process control systems. Its solutions include safety systems, conveyor automation, hoisting systems, and intelligent motor control centres specifically designed for mining operations.

NVIDIA (NVDA) supplies the computing platforms and AI technologies that power many modern mining solutions, from autonomous equipment to predictive maintenance systems.

Drive the regeneration

The mining sector is crucial to the future net zero economy, providing essential materials for renewable energy technologies and infrastructure. While many sustainable investors may choose not to invest directly in mining companies, investors can gain exposure to this industry while driving the regeneration of the mining industry by prioritising companies that leverage AI for improved operations.

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