Artificial Intelligence (AI) is poised to transform the mining industry, and according to Stanford professor and World Mining Congress (WMC) 2026 programme committee member Jef Caers, the impact could be dramatic. Caers believes AI has the potential to reduce drilling requirements by a factor of five, saving time, capital, and enabling more informed “go-or-no-go” decisions in exploration and mineral processing.
From Static Models to Intelligent Agents
Caers, a leading expert in applied geosciences and decision-making under uncertainty, argues that mining companies must adopt intelligent agents to fundamentally change how decisions are made in exploration and processing.
Traditionally, exploration relies on drilling fixed grids to estimate grades. This approach is costly, time-consuming, and often inefficient. AI, however, introduces a new logic: instead of filling grids, intelligent agents plan drilling campaigns to falsify geological hypotheses and strategically reduce uncertainty. The goal is not to drill more, but to drill smarter—until companies can confidently decide whether to proceed or walk away.
Intelligent Prospector: AI as a Decision-Maker
Caers likens this new AI approach to autonomous vehicles operating in San Francisco: sophisticated systems that make sequential decisions under uncertainty.
An intelligent agent in mining is not just a predictive tool—it is an AI system designed for sequential planning, capable of making decisions while simultaneously optimising data collection. In exploration, this means dynamically adjusting drilling locations based on emerging information, rather than sticking to rigid plans.
Drilling to Falsify Hypotheses
In conventional practice, companies often build a single deterministic subsurface model and drill accordingly. But if the hypothesis is wrong, drilling becomes highly inefficient.
Caers explains: “An intelligent agent will plan drilling to falsify human-generated hypotheses, then only drill to define grades and tons.” By strategically reducing geological uncertainty, AI can cut down drilling requirements significantly, saving millions in exploration budgets while accelerating timelines.
Implications for Critical Minerals
Caers frames the challenge of critical mineral supply chains as a sequential planning under uncertainty problem. From exploration to processing, every stage involves decisions made with incomplete information. AI can help companies navigate this uncertainty more effectively, ensuring resources are allocated where they matter most.
This is particularly relevant as demand for critical minerals—such as lithium, cobalt, and rare earths—continues to rise, driven by clean energy technologies and global industrial transformation.
AI as a Theme at WMC 2026
The technological transformation of decision-making under uncertainty is expected to be one of the central themes at the World Mining Congress 2026. Industry leaders will explore how AI can reshape exploration strategies, reduce costs, and improve sustainability in mining operations.
By integrating intelligent agents into exploration workflows, companies can move beyond traditional models and embrace a future where data-driven decision-making is the norm.
AI is no longer just a buzzword in mining—it is becoming a practical tool for efficiency, sustainability, and smarter exploration. By reducing drilling requirements, optimising data collection, and enabling more informed decisions, intelligent agents could redefine how mining companies approach uncertainty.
As Caers emphasises, the future of mining lies not in drilling more holes, but in drilling the right ones—guided by AI systems that learn, adapt, and plan strategically. With WMC 2026 set to spotlight these innovations, the industry is on the cusp of a new era where exploration is faster, cheaper, and more intelligent.
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