2 It is in this context that the World Mining Congress convenes in Lima, Peru, for its 27th edition in June 2026. Peru is the world's second-largest producer of copper and zinc, and a leading producer of silver, gold, lead, and molybdenum. Latin America as a whole holds more than half of the world's known lithium reserves and a dominant share of its copper resources. To host this Congress in the Andean heartland of global mineral supply is to situate the conversation precisely where it must occur: at the nexus of resource endowment, industrial ambition, indigenous rights, environmental stewardship, and geopolitical significance. The theme of WMC 2026 — mining's evolving role in a resource-constrained, decarbonizing world — runs as a thread through every session and every track of this program. The questions the industry faces are not merely technical. They are questions of governance, social legitimacy, environmental responsibility, and the fair distribution of the wealth that minerals generate. The presentations gathered here, drawn from more than 70 countries and spanning the full spectrum from deep-sea polymetallic nodule collection to geothermal decarbonization in the Andes, reflect an industry that is simultaneously under the most intense scrutiny it has ever faced and rising to that scrutiny with genuine innovation. The Technical Program for WMC 2026 comprises 266 oral presentations organized across nine thematic tracks and more than 40 sessions, structured over three days of intensive exchange. The program has been designed to ensure that no discipline operates in isolation: a geotechnical engineer will find their work connected to questions of environmental closure; a process metallurgist will encounter the AI systems that are transforming their field; a policy specialist will confront the ground-level social realities that determine whether any policy succeeds. This integration is intentional. The challenges ahead demand it. Synopsis of Technical Tracks and Sessions The following provides an overview of the nine thematic tracks that constitute the 2026 Technical Program, together with a summary of the principal sessions and the scope of presentations within each track. Track 1: AI and Data-Driven Decision Making The largest track in the program reflects a fundamental transformation underway across the industry. Artificial intelligence, machine learning, digital twins, and data-driven analytics are no longer emerging technologies in mining — they are operational realities, and their scope is expanding rapidly. This track, organized across ten sessions, examines AI applications ranging from mineral exploration and resource estimation to real-time operational optimization, safety management, and processing plant control. AI in Mineral Exploration and Geoscience: Sessions examine the use of convolutional neural networks and variational autoencoders for predicting deposit occurrence, hyperspectral data integration for lithological classification, and machine learning workflows for predictive exploration targeting. The promise of AI to compress exploration timelines and reduce discovery costs is examined critically, with presentations separating demonstrable achievement from speculative claims. Automation, Data and AI in Operations: Presentations address fleet management systems, autonomous mechatronic systems for mine servicing, and reinforcement learning applications for resource extraction scheduling. A notable contribution explores the connection between classical economic theory and AI-driven extraction optimization. Digital Twins and Connected Operations: The application of digital twin architectures to processing plants, SAG mills, and tailings facilities is examined across several sessions, with emphasis on real-time forecasting, uncertainty quantification, and transparent risk-communication frameworks. AI-Enabled Safety and Risk Management: Machine learning approaches to slope movement detection, collision avoidance, neural network-based landslide susceptibility mapping, and multi-source monitoring of tailings dam deformation dynamics are presented, reflecting a growing convergence between AI capability and the industry's most critical safety imperatives. Processing and Operational Intelligence: Sessions cover AI-assisted grinding circuit control, SAG mill feed characterization through deep clustering, heap leach pad planning using predictive models,
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