Exhibition floor open and Brella Networking

• How data, automation, and artificial intelligence are reshaping mining operations to improve safety, productivity, and operational visibility across complex sites.
• The role of digital technologies in advancing more sustainable mining, from optimizing energy and water usage to supporting decarbonization goals.
• Creating a strong digital foundation through cloud platforms, integrated data environments, and robust cybersecurity to enable scalable innovation.
• Empowering people to work alongside advanced technologies by building digital capabilities, fostering collaboration, and driving cultural transformation across the organization.

• Understanding the main barriers slowing digital adoption in mining, including legacy systems, integration challenges, workforce readiness, and change management.
• Exploring the balance between standardizing digital platforms across operations and allowing site-level customization to address unique geological and operational realities.
• Lessons learned from early digital initiatives, including what mining companies would approach differently if starting their transformation today.
• Identifying practical steps to move from pilot projects to scalable digital and AI solutions that deliver measurable value across North American mining operations.

• Applying AI and digital technologies across mining operations to unlock measurable improvements in productivity, safety, and operational performance. 

• Scaling AI from pilots to enterprise-wide deployment through strong data foundations, governance, and cross-functional collaboration. 

• Managing the risks of AI adoption, including data quality, model transparency, cybersecurity, and operational reliability. 

• Embedding responsible AI principles, governance frameworks, and workforce engagement to ensure safe and trusted deployment across mining operations. 

• Understanding the operational challenge that triggered the digital initiative, whether related to productivity, safety, maintenance, energy efficiency, or operational visibility across mining sites.
• Examining the technology approach used to address the challenge, including how AI, advanced analytics, digital platforms, or automation solutions were integrated into existing mining operations.
• Lessons learned from implementation, including managing change, integrating with legacy systems, engaging site teams, and moving beyond pilot projects.
• Exploring the measurable impact of digital solutions on operational performance, from improved equipment uptime and decision-making to cost reduction and safety improvements.
• Identifying how successful digital initiatives can be scaled across multiple sites to drive long-term operational and strategic value.

1. Autonomous Mining: From Pilot to Digital Mine

• How Teck Resources scaled autonomous haulage from a pilot to a fleet of 87 trucks at Highland Valley Copper Mine.
• The digital infrastructure required for large-scale autonomy, including connectivity, IoT sensors, and fleet platforms such as FrontRunner Autonomous Haulage System.
• How real-time data and analytics improve dispatching, haul routes, equipment utilization, and overall mine productivity.
• Workforce transformation as operations shift from truck drivers to digital fleet monitoring and control.
• Key lessons from moving beyond pilots to scalable digital and AI-enabled mining operations.

2. Scaling Digital Transformation Across Multi-Site Gold Mining Operations 

• Building a connected digital ecosystem across exploration, mining, and processing operations 

• Leveraging data platforms, automation, and advanced analytics to improve operational visibility and decision-making 

• Integrating safety, production, and asset performance data to drive real-time operational improvements 

• Lessons learned from deploying digital technologies across large, geographically distributed mining assets 

2. Understanding the Digital Shift Handover & Production Reporting Improvement 

• Understanding the evolving cybersecurity threat landscape in mining as operations become more connected through automation, IoT, cloud platforms, and remote operations centers.
• Protecting critical operational technology (OT) and industrial control systems while ensuring continuity and safety across mine sites, processing plants, and logistics networks.
• Bridging the gap between IT and OT security teams to build unified cybersecurity strategies that protect both corporate and operational environments.
• Managing third-party and supply chain cyber risks as mining companies increasingly rely on digital vendors, connected equipment, and integrated platforms.
• Building a resilient cybersecurity culture through workforce awareness, incident response planning, and governance frameworks that support safe digital transformation.

• Understanding how data silos between OT and IT systems—such as fleet management, plant control systems, maintenance platforms, and enterprise software—limit operational visibility and decision-making across mining operations.
• Exploring practical approaches to OT/IT integration, enabling operational technology (equipment, sensors, control systems) to connect with enterprise IT systems to create a unified and reliable data environment.
• Establishing clear data ownership and governance, including who is responsible for data quality, how standards are defined, and how mining organizations ensure data remains trusted and consistent across sites.
• Identifying how to move beyond dashboards that no one uses by developing KPIs that operators, engineers, and supervisors actually rely on for daily operational decisions.
• Sharing lessons on how a unified mine data platform helps transform fragmented operational data into high-quality, trusted datasets that support analytics, AI, and autonomous mining operations.

• Using digital twin models to simulate mine plans, processing scenarios, and operational changes to support more informed decision-making 

• Connecting operational, geological, and processing data to create real-time digital representations of mining and processing systems 

• Optimizing plant performance, recovery rates, and production stability through simulation-driven insights and predictive analytics 

• Improving environmental and ESG performance by modeling energy use, water consumption, and emissions across mining operations 

• Exploring where artificial intelligence is delivering the most measurable value in mineral processing, particularly in areas such as grinding circuit optimization and throughput improvements.
• Examining the use of AI and advanced process control in flotation circuits to stabilize performance, improve recovery rates, and reduce variability in plant operations.
• Understanding the role of digital twins in processing plants, enabling simulation, predictive insights, and improved decision-making across complex processing systems.
• Assessing the importance of instrumentation and data quality, including sensor coverage, calibration, and data infrastructure required to support effective AI deployment.
• Identifying the practical limitations and lessons learned from AI initiatives in processing environments, including where expectations have exceeded operational reality.

• Creating a unified digital infrastructure that connects power systems, automation platforms, and operational data across mining sites 

• Improving operational visibility and reliability through integrated monitoring of electrical networks, equipment, and production systems 

• Enabling real-time decision-making with connected platforms that bridge operational technology (OT) and enterprise IT environments 

• Supporting safer, more energy-efficient mining operations through advanced automation, electrification, and digital control systems 

• The strategic importance of digital innovation in strengthening the competitiveness of the mining sector

• Supporting responsible and sustainable mining through technology and data-driven operations
• Government priorities for innovation, digital infrastructure, and workforce development in the mining industry

Under Invitation: The Minister for Mining & Energy, The Government of Ontario  

• Managing organizational change as AI initiatives expand across multiple mining sites
• Developing a standardized operating model for deploying digital and AI solutions
• Balancing internal capability development with the use of external technology partners
• Lessons learned from scaling digital initiatives beyond early pilot projects

• Examining why reliable connectivity has become a critical foundation for digital mining initiatives, enabling automation, real-time data, and remote operations in underground and remote environments.
• Comparing connectivity technologies such as private LTE and Wi-Fi 6/7, and how mining companies are evaluating performance, scalability, and deployment considerations in challenging environments.
• Understanding the importance of latency, network reliability, and coverage for supporting autonomous equipment, monitoring systems, and real-time operational decision-making.
• Lessons learned from connectivity deployments at remote Canadian mining sites, including infrastructure challenges, harsh environmental conditions, and long-distance data transmission.
• Exploring how mining companies can build future-ready connectivity networks that support digital transformation, AI applications, and increasingly connected operations. 

• Aligning IT and OT teams to support connected mining operations, from mine sites and processing plants to corporate systems and cloud platforms.
• Integrating operational technology systems with enterprise IT environments while maintaining reliability, safety, and operational continuity.
• Managing cybersecurity risks across both IT and OT environments as mines become increasingly connected and data-driven.
• Overcoming cultural and organizational barriers between IT and operations teams to enable successful digital transformation.
• Establishing governance models, data ownership frameworks, and collaboration structures that allow IT and OT to jointly support innovation and operational performance.

• Overcoming fragmented data environments across legacy historians, control systems, and operational platforms. 

• Building a strong data foundation to enable reliable analytics, operational visibility, and AI adoption. 

• Integrating OT and IT systems to unlock real-time insights across mining and processing operations. 

• Applying advanced analytics and automation to move from pilot projects to scalable AI-driven optimization. 

• Training and supporting frontline teams to work effectively with new digital technologies
• Creating incentives that encourage adoption and long-term engagement with digital tools
• Understanding workforce realities, including collaboration with unions and evolving job roles
• Identifying the digital skills and specialist roles that mining organizations increasingly require

• Mining haul trucks consume approximately 32% of total energy and account for up to 22% of operating costs in open-pit mines. 

• Fuel consumption can be affected by equipment condition and characteristics, road design and conditions, weather conditions and driving behaviour, among others. 

• Using data collected from sensors installed on haul trucks, the effect of important factors such as travel speed, road inclination, payload and weather conditions on fuel consumption is studied. 

• Supervised machine learning modelling, followed by scenario analyses are used to support decision-making related to mine operation, maintenance and design. 

• Our findings suggest strategies such as payload and maximum speed limit adjustments can yield significant fuel savings. 

• Understanding the strategic decision between building internal digital capabilities and relying on external technology vendors, consultants, and platform providers.
• Identifying which capabilities mining companies should develop internally, including data engineering, analytics, and digital product ownership.
• Exploring where external partners add the most value, particularly in areas such as AI development, specialized software platforms, and advanced analytics.
• Managing vendor relationships and avoiding long-term technology lock-in while maintaining flexibility and scalability.
• Lessons learned from mining companies that have successfully built internal digital teams while leveraging external expertise to accelerate innovation.

Each presentation is 10 minutes.  

1. AI for Dispatch, Scheduling & Short Interval Control
2. Predictive Maintenance, Reliability & Asset Health at Scale
3. AI for Mine-to-Mill Optimization: Connecting Extraction and Processing Data
4. Computer Vision in Mining: From Conveyor Monitoring to Safety Detection  
5. Edge AI Underground: Processing Data Where Connectivity Is Limited  

• Exploring the emerging technologies expected to transform mining operations over the next decade, including AI, robotics, autonomous systems, and advanced sensing technologies.
• Understanding how technologies such as digital twins, edge computing, and real-time analytics are improving operational visibility and decision-making across mining operations.
• The growing role of robotics and autonomous systems in improving safety and productivity in both surface and underground environments.
• Evaluating which emerging technologies are delivering real operational value and which remain in early development stages.
• Preparing mining organizations to adopt and scale new technologies while managing risk, investment, and workforce transformation.

Participants can join the round table of their choice. Each roundtable leader will spend the first 10 minutes on a case study, lessons learned, or industry update. This will be followed by a 30-minute open discussion with all participants, moderated by the leader. The final 5 minutes will be used to identify 3-5 industry recommendations resulting from the group discussion. Key recommendations will be shared with the entire audience, and all roundtable recommendations will be included in the post-event report. 

1. Building a Roadmap for AI Adoption in Mining Operations

2. Real-Time Data Integration: From Fragmented Systems to a Unified Operational View

3. Autonomous & Semi‑Autonomous Mining: What’s Next?

4. Improving Safety Outcomes with AI-Driven Predictive Analytics

5. Digital Twins for Mines of the Future

6. AI for Energy Efficiency & Emissions Reduction

7. Workforce Transformation: Skills, Training, and Human‑Machine Collaboration

8. Cybersecurity in the Era of Hyper-Digital Mines

9. AI in Mineral Processing: Smart Optimization for Throughput & Recovery

10. Vendor–Operator Collaboration Models for High-Impact Innovation

• Exploring how AI copilots are being deployed to support supervisors and frontline teams with real-time decision support, operational insights, and improved shift management.
• Examining the growing use of computer vision technologies to improve safety monitoring, detect hazards, and enhance situational awareness across mining operations.
• Understanding the next phase of autonomous technologies, including autonomous drilling and blasting systems designed to improve precision, productivity, and operational safety.
• Leveraging advanced analytics and digital platforms to optimize energy consumption, reduce emissions, and support decarbonization goals across mining operations.
• Identifying the digital initiatives mining leaders are prioritizing over the next two years and the practical steps required to move from experimentation to operational scale.