As global competition for critical minerals grows, technological advancements are rapidly changing Africa’s resource exploration and development. At the Investing in African Mining Indaba 2026, industry leaders highlighted the role of technology in boosting discovery, reducing uncertainty, and increasing investor confidence through data-driven processes and innovative methodologies.
Exploration is becoming a precise, data-centric discipline, requiring new skills and workforce development. Automation, AI-powered targeting, low-impact drilling, and real-time analytics are accelerating project discovery and improving operational efficiency. For instance, inversion modelling helps geologists pinpoint resource locations with greater accuracy, while Measure While Drilling (MWD) provides real-time metrics to guide decisions and validate geological models, minimizing risks.
Drilling now relies heavily on AI integration and real-time feedback for optimized performance. Experts at Mining Indaba emphasized confirmation-focused drilling, which enhances efficiency and strengthens validation of geological models. This shift demands substantial upskilling within the mining workforce to support a data-driven future centered on precision and reduced uncertainty.
According to Dave Goddard (Hexagon), contemporary drilling focuses on validation rather than discovery, with advanced analytics confirming geological models and supporting major investment decisions. Automation and remote operations, inspired by oil and gas practices, further improve safety and precision.
Professor Glen Nwaila compared AI’s impact to aviation, where professionals move from manual tasks to supervisory roles. He stressed the need for immediate feedback loops and real-time MWD data to reduce uncertainty and increase confidence. Fleet Space Technologies’ AI-powered rigs in Zambia demonstrate how technology shortens exploration timelines and boosts discovery success rates.
Kendall Cole-Rae noted that top mining companies now integrate data architects and analysts with traditional teams to accelerate discovery and improve results. Glen McGavigan (Rosond) predicted drillers will transition into maintainers focused on data integrity, with future rigs leveraging machine learning for optimized operations.
Professor Nwaila advocated for education and training reforms, calling for industry-academic collaboration and the rise of geo-data scientists to bridge technical data with practical mining needs. Ongoing cooperation between operators, geologists, managers, and data specialists will be crucial for greater precision and sustainability in mining.