•    Understanding current AI capabilities and their real impact on exploration, automation, and operational efficiency.
•    Debunking the myths—separating exaggerated AI promises from real-world applications and practical limitations in mining.
•    Learning from case studies of companies that have effectively implemented AI-driven solutions to improve safety, productivity, and cost savings.
•    Exploring the road ahead—emerging AI trends, workforce impacts, and what’s needed for large-scale adoption in the mining industry.
 

•    Exploring advancements in AI, automation, and IoT that are reshaping mining operations.
•    Enhancing efficiency and productivity through digital tools, predictive analytics, and smart systems that optimize extraction, processing, and logistics.
•    Discovering how technology-driven solutions minimize waste, reduce emissions, and improve resource management.
•    Overcoming adoption challenges by addressing key barriers such as integration, cost, and workforce readiness to ensure the successful implementation of new technologies.
 

•    Leverage AI and digitalization to understand the connectedness of you operational business processes.
•    Define who does what when, how and why.
•    Explore the possibilities for LLM’s (large language models) against AI augmented work flow database
 

•    Transforming mining operations—how AI enhances exploration, extraction, and mineral processing through automation and real-time data analysis.
•    Boosting safety and profitability—autonomous machinery and predictive analytics leading to safer work environments and improved financial performance.
•    Driving sustainability—AI minimizes environmental impact by optimizing resource use and reducing waste.
•    Implementation roadmap—starting with system assessments, collecting quality data, launching pilot projects, and scaling up while continuously monitoring AI performance.
 

The lightning rounds will showcase case studies from speakers who each have 10-15 minutes to present their update on the Problem, challenge + solution.

•    Empowering the Mine of the Future with Trifork’s Mobile and AI capabilities: Smarter Operations, Safer Workforces, and Stronger Returns
•    AI-Powered Predictive Maintenance: Reducing Downtime & Costs
•    Real-Time Ore Grade Prediction Using AI & IoT Sensors
•    Digital Twins & AI for Mine Planning & Simulation
•    AI-Powered ESG & Sustainability Analytics for Mining

•    Building a Unified Data Strategy: The role of data centralization in driving efficiency.
•    Vendor Selection & Assessment: Key criteria for choosing AI and digital solutions.
•    From Data to Decisions: Leveraging AI for real-time, automated decision-making
•    Vendor Deployment: Discussing challenges with adoption, data quality, and integration with broader corporate strategy

•    Understanding how predictive maintenance with AI works in practice - How machine learning and digital twins help prevent equipment failures before they occur.
•    Enhancing maintenance strategies with GenAI recommendations and diagnostics for decision support.
•    Looking at reducing downtime, increasing safety, and optimizing resource use through intelligent maintenance.
 

•    Successfully leverage digital technologies throughout the lifecycle of a mine to address challenges facing the industry and ensure profitable operations.
•    Optimize design, unify operations, and take intelligent decisions with Unified Power and Process solutions.
•    Adopt Dynamic Digital Twins to shorten Project Engineering time and enable data-driven decisions
•    Employ Real-Time Operational Digital Twins for site and enterprise-wide optimization of critical assets.

•    Autonomous haulage, AI-powered drilling, and smart processing plants.
•    Improving efficiency, reducing costs, and enhancing safety.
•    Real-time data analytics for predictive maintenance.
•    AI-driven decision-making to optimize resource extraction.
•    Environmental benefits of automation in mining.
•    Overcoming challenges in AI adoption and workforce transformation.
 

•    Unlocking operational efficiency—how automation and AI solutions streamline mining processes, reduce downtime, and optimize resource utilization.
•    Leveraging smart technologies to enhance worker safety, meet regulatory standards, and ensure operational compliance in challenging environments.
•    Demonstrating the economic benefits of automation and AI—reducing operational costs and improving long-term profitability through smarter decision-making.

•    Exploring how machine learning, AI-powered hazard detection, LiDAR, and radar technology work together to detect and prevent collisions in real-time.
•    Discussing the role of collision avoidance systems in meeting global mining safety regulations and reducing workplace incidents.
•    Discovering how CAS solutions improve safety for both automated and operator-driven vehicles in open-pit and underground mines.
•    Exploring the future of collision avoidance in mining—emerging trends such as predictive analytics, digital twins, and V2X (vehicle-to-everything) communication for next-gen mine safety.
 

•    Tackling implementation costs & ROI concerns—balancing upfront investments with long-term gains and securing executive buy-in for digital projects.
•    Bridging the talent gap—addressing workforce shortages by upskilling current employees, attracting digital talent, and fostering partnerships with universities.
•    Discussing industry collaborations—how mining companies can accelerate innovation by partnering with tech startups, leveraging incubators, and co-developing AI-driven solutions.
 

•    Aligning security and business goals by redefining cybersecurity success to support mining innovation rather than hinder it, ensuring security objectives align with business growth.
•    Shifting from “No” to “How”: Transforming cybersecurity teams into enablers of innovation by integrating security early in project planning and risk management.
•    Measuring security success beyond budget by evaluating cybersecurity effectiveness based on risk reduction, operational resilience, and business continuity, rather than just cost avoidance.
•    Building a culture of security-first Innovation and encouraging cross-functional collaboration to embed security into digital transformation projects without stalling progress.
 

•    Dataset Standardization & Managed AI Services
•    Real-Time Decision Making Through Edge AI
•    Predictive Analytics for Operational Excellence
•    Human-AI Collaboration in Mine Planning

•    Government initiatives supporting digitalization and AI adoption
•    Regulatory challenges and opportunities in AI-driven mining
•    Ethical AI and responsible mining practices
 

•    Translating the subject-matter-expert knowledge to build KPI analytics and Power BI reports around ASARCO's mining operations, focusing on operational productivity, maintenance, and fleet management
•    Enable data-driven decisions to optimize operations based on reports showcasing critical insights into mining operations
•    Targeted analytics to facilitate rapid response for performance metrics, issue identification, and continuous improvement
•    Customizable, dynamic reporting allowing users to filter data by equipment, manufacturer, operator, crew, and date for tailored insights
 

The lightning rounds will showcase case studies from speakers who each have 10-15 minutes to present their update on the Problem, challenge + solution.

•    Revolutionizing Tooth Wear Monitoring and Changeout Timing Through AI & Machine Vision. 
•    Sustainability and Energy Management in Remote Operations. 
•    Connectivity solutions for remote mining sites and the role of satellite communications, private LTE, and 5G networks.

•    Discussing how machine learning and data analytics optimize drill patterns for better fragmentation and minimal waste.
•    Understanding the role of remote-controlled and AI-assisted blasting in improving efficiency and ensuring compliance with safety regulations.
•    Looking at how automation and robotics are minimizing human exposure to hazardous drilling, and blasting environments and reducing operational risks.
•    Using IoT sensors, AI, and cloud computing to monitor drilling and blasting performance and dynamically adjust strategies.

•    AI and automation: Transforming efficiency and safety.
•    Robotics and remote operations: Overcoming challenges in implementation.
•    ESG and sustainability: Balancing innovation with environmental responsibility.
•    The Road Ahead: Collaboration, cybersecurity, and workforce transformation.