A key challenge in hard-rock mining remains the time lag in obtaining Measure While Drilling (MWD) data.
While operator assistance remains key in current setups, there’s a growing push to automate manual processes and enable remote operations, drawing significant lessons from the oil and gas sector. Prof. Glen Nwaila, Director of the African Research Centre for Ore Systems Science (CORES) at the University of The Witwatersrand drew parallels between current AI deployment in exploration and the aviation industry, where pilots became supervisors rather than just operators. “A key challenge in hard-rock mining remains the time lag in obtaining Measure While Drilling (MWD) data,” he said. “That’s why we need more immediate feedback loops for effective decision- making. We drill to reduce uncertainty, to gain confidence.” Accelerating the timeline to discovery remains the main goal for exploration, particularly when it comes to meeting the critical-mineral requirements of the global energy transition. Kendall Cole-Rae, expert in residence at Fleet Space Technologies, pointed out that Tier 1 mining companies were now actively integrating non-traditional experts like data architects and analysts into their teams, merging deep traditional drilling expertise with cutting-edge technologists. “Reducing the timeline to discovery is key with energy transition requirements,” he said. “We must increase the probability of success.” Rosond CEO Glen McGavigan predicted that the future driller would evolve into a maintainer and QC officer over the data, moving away from purely manual operation to a more holistic, data-informed role. He drew parallels with Google Maps, saying that future drilling rigs would use machine learning to detect geological changes and recommend optimal parameters to operators, while ensuring safety and productivity at the same time. Prof. Nwaila said the future would require significant reforms in education and training, advocating for formalised programmes with industry leaders and continuous learning modules for professionals. He said a critical new discipline will be the “geo-data scientist”. “We need a bridge between operator, the mine, geologists
We need a bridge between operator, the mine, geologists and the mine manager who must use the data.”
and the mine manager who must use the data.” The discussions underscored a consensus that the future of mining hinges on cross-disciplinary cooperation. From the integration of data scientists and AI specialists into geological teams, to the sharing of data for collective benefit, the way forward is unmistakably one of partnerships – with every stakeholder contributing to a more precise and sustainable mining landscape. n
April 2026 | www.modernminingmagazine.co.za MODERN MINING 23
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