Automation, Exploration, and Investment Insights with Doug Smith

The mining industry is undergoing a rapid transformation, driven by advances in artificial intelligence (AI) and automation. From autonomous haul trucks to AI-powered exploration tools, the sector is embracing digital transformation to increase efficiency and sustainability. In the latest episode of the Hevi AI Podcast, Paul Culvenor and Brad Gyngell sit down with mining engineer-turned-investment analyst Doug Smith to explore AI’s role in mining, the challenges of automation, and how investors view tech-driven mining operations.

The Journey from Engineering to Finance

Doug Smith began his career as a mining engineer, working for Rio Tinto in the Pilbara region, home to some of Australia’s largest iron ore mines. Over the years, he gained hands-on experience in drill and blast, scheduling, and contractor management. His career then took a turn towards finance, where he now analyzes mining equities and capital projects.

Doug's insights provide a unique perspective on the intersection of mining operations and investment decisions, particularly how companies adopting AI and automation can gain a competitive edge.

Autonomous Mining: The Rise of Smart Operations

One of the most significant technological shifts in mining has been the adoption of autonomous systems. Doug shares his firsthand experience working with Rio Tinto’s autonomous haul trucks and drills.

"We had one guy sitting in a control room managing three autonomous drills. It was futuristic stuff."

These autonomous systems improve efficiency by eliminating breaks and optimizing haulage cycles. In contrast to human-operated trucks, autonomous fleets operate continuously with minimal downtime, leading to increased productivity and lower operational costs.

Key Benefits of Autonomous Mining

• Increased Utilization – Autonomous trucks and drills operate 24/7, with no shift changes or human-related delays.
• Safety Improvements – Fewer workers in hazardous areas reduce the risk of accidents.
• Optimized Operations – AI-driven fleet management enhances load distribution and route efficiency.

Challenges of Retrofitting Automation

While new mines can be designed with automation in mind, retrofitting existing operations presents challenges. Doug highlights the complexities of implementing automation in established sites:

"AutoHaul for trains was exponentially harder than autonomous trucks. You had to deal with existing infrastructure, level crossings, third-party interactions, and strict safety regulations."

Retrofitting existing rail networks with automation required significant investment, but the long-term benefits—such as improved logistics and reduced labor costs—made it worthwhile. The success of these projects demonstrates that automation is feasible but must be carefully planned and executed.

AI in Mining Exploration: Smarter Targeting

Beyond automation, AI is also transforming mineral exploration. Machine learning algorithms analyze geological data to identify high-potential drill targets with greater accuracy than traditional methods. AI-powered hyperspectral imaging and electromagnetic surveys are now being used to pinpoint mineral deposits with minimal environmental impact.

Doug notes that while some exploration companies have fully embraced AI, others lag behind.

"We're seeing AI-driven geological modeling improve strike rates for junior miners. The ones who aren't adopting these methods are at risk of falling behind."

Advantages of AI in Exploration

• Higher Strike Rates – AI enhances target selection, reducing drilling costs.
• Faster Data Processing – Advanced models quickly analyze satellite and geophysical data.
• Reduced Environmental Impact – AI minimizes unnecessary drilling, preserving natural landscapes.

AI in Mining Investment: A Competitive Advantage?

As a mining equities analyst, Doug evaluates how AI adoption impacts a company's value proposition. He explains that while investors favor technological innovation, they also seek proof of real-world benefits.

"AI is great, but if a company can't demonstrate clear cost savings or operational efficiency, investors remain skeptical."

Mining companies that leverage AI for predictive maintenance, autonomous operations, and enhanced exploration stand to gain a competitive advantage, attracting more investment and improving profitability.

What Investors Look For

• Operational Efficiency – Demonstrated cost reductions from AI-driven optimizations.
• Scalability – Can the technology be applied across multiple sites?
• Regulatory Compliance – Ensuring AI applications align with industry safety and sustainability standards.

Future Outlook: What’s Next for AI in Mining?

Looking ahead, Doug sees AI continuing to play a transformative role in mining, but challenges remain in making these technologies scalable and cost-effective for smaller players. He predicts:

• Greater adoption of real-time AI data analytics to enhance decision-making.
• More AI-driven exploration techniques to locate deeper and more complex ore bodies.
• Expansion of AI-powered predictive maintenance to extend equipment lifespan and reduce downtime.

Conclusion: Embracing AI for a Smarter Mining Industry

AI and automation are reshaping the mining industry, offering opportunities for greater efficiency, sustainability, and profitability. However, as Doug Smith emphasizes, the key to success lies in strategic implementation and demonstrating clear value.

At Hevi, we help mining companies harness the power of AI for smarter contract administration and risk management.

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🔊 Listen to the full episode on:
Spotify: https://open.spotify.com/episode/0awTe5lnRWuT0oXp0x5VJO?si=973yVyCVSR25y4VyMWwQ3w
YouTube: https://youtu.be/l0ZySEC7bjI

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