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Why Decisions - Not Data - Will Define the Future of Mining
Mining organisations have undergone significant digital transformation over the past decade, resulting in widespread availability of data, advanced analytics and insights across operations, assets, and enterprise systems. However, despite this progress, operational decision-making remains inconsistent, delayed, and highly dependent on individual expertise.
This paper argues that the industry has reached an inflection point where data and insights have become a commodity, contributing to increased cognitive overload and accelerating skills loss within the workforce.
The paper introduces Decision Automation as a fast-adopting current phase of AI evolution in mining — shifting the focus from data acquisition and analysis toward the systematic augmentation and standardisation of decision-making. It explores how decision intelligence can be embedded across operational, maintenance, and planning workflows to improve consistency, responsiveness, and
overall performance.
Drawing on practical industry architectures, including Yokogawa’s Asset Operations Management (AOM) and emerging agentic AI approaches, the paper outlines how organisations can transition from data-centric systems to decision-centric operations. It further examines the role of Decision Automation in scaling expertise, reducing variability, and enabling more resilient and adaptive mining
operations.
