Mining in the Age of Artificial Intelligence (AI): Harnessing Big Data for Environmental Stewardship - , Ahaneku, C. V.; , Obiamalu, C.C.; , Aseh, P.; , Elomba, U.F.; , Amasiani, E.J.; , Muogbo, D.C.; , Ugwu, F.O.; , Boma, E.K.; , Odoh, B.I.; , Omezi, I. (Archives of Current Research International, 2025)
Mining operations contribute substantially to global environmental degradation. The sector accounts for an estimated 7–9% of global energy consumption and is responsible for widespread groundwater contamination, with acid mine drainage affecting over 12,000 kilometres of streams globally. As global demand for critical minerals surges—driven by the clean energy transition and rapid technological advancement—the mining industry faces mounting pressure to balance productivity with environmental sustainability. This paper explores how artificial intelligence (AI) and big data analytics are revolutionising environmental stewardship in modern mining operations. Through a comprehensive review of literature, real-world case studies, and industry data, the transformative role of AI-enabled technologies such as Internet of Things (IoT) sensors, satellite imaging, and drone-based mapping in reducing environmental impact was examined. These systems provide real-time monitoring, predictive analytics, and automated responses that help mitigate risks such as water contamination, biodiversity loss, and greenhouse gas emissions. Results indicate that AI-driven environmental management systems can reduce water usage by up to 40%, energy consumption by 20%, and pollution-related incidents by over 90%. Despite challenges including data integration complexity and skill gaps, the convergence of AI with quantum computing and advanced sensor networks presents a promising future for sustainable mining. The integration of AI and big data technologies in the mining industry is ushering in a new era of smart, efficient, and sustainable mining practices. By harnessing the power of these transformative tools, mining companies can enhance their competitiveness, mitigate environmental impact, and ensure the long-term viability of the industry. This study proposes a scalable, standardised framework for AI integration to optimise environmental performance, improve economic viability, and enhance stakeholder engagement in the mining sector.