•    Moving beyond proof-of-concepts to enterprise-wide AI deployment
•    Quantifying ROI: Real metrics from 2+ years of AI implementation
•    Building AI Centers of Excellence within mining organisations
•    Lessons learned from failed AI projects and how to avoid common pitfalls
•    The role of edge computing in real-time AI applications

•    Benchmarking AI adoption across major mining operations
•    Building vs. buying AI solutions - finding the right balance
•    Data governance frameworks that enable AI at scale
•    Integrating AI with existing OT/IT infrastructure
•    Skills gap solutions: Upskilling workforce for AI-powered operations
•    Regulatory compliance and AI transparency requirements

•    From Task to Strategic: Elevating Mining Professionals Through AI 
•    Building Digital Confidence: Closing the Skills Gap Without Leaving Anyone Behind
•    The Internal Innovation Engine: Developing Homegrown AI Talent 
•    Measuring What Matters: AI-Enhanced Performance and Wellbeing 
•    Using predictive analytics to identify training needs, optimise shift patterns, and prevent burnout in remote operations 
 

•    Data Interoperability: Breaking down silos between OEM systems and proprietary formats
•    Industry Standards: Developing mining-specific data frameworks and common protocols
•    Integration Challenges: Managing vendor resistance and IP protection concerns
•    Single Source of Truth: Practical approaches to unified data across supply chain partners
 

•    The Insider Threat Reality: Preparing for both internal threats and external attacks - balancing employee trust with security requirements 
•    Remote Site Vulnerabilities: Unique challenges of distributed workforces with limited on-site personnel and delayed incident response - technology solutions for isolated operations 
•    Legal Complexity of Monitoring: Navigating privacy laws across jurisdictions while maintaining security oversight - creating transparent policies that protect both company and employees 
•    Security as Innovation Enabler: Rebranding security teams from saying "no" to facilitating secure operations - cultural change management strategies that work 
 

Each round table covers a different topic, allowing attendees to select which one to join. Round table leaders will begin with a 5-minute introduction of themselves and a brief overview of the topic, which can include a case study, lessons learned log, or industry update. They will then facilitate a 40-minute discussion with the group, encouraging feedback and questions. The last 10 minutes will focus on agreeing on five industry recommendations. These recommendations will be shared with the entire audience and summarized in the post-event report.

1. GenAI in Production - Beyond ChatGPT    
2. Strategic Partnerships vs. Traditional Procurement: The Future of Mining Supply Chains    
3. Autonomous Mining: Promise vs. Reality - When Will We See True ROI?    
4. ESG in Mining: Competitive Advantage or Compliance Burden?    
5. Natural language interfaces for equipment diagnostics

•    Internal data governance and quality
•    Phased approach to data standardization across operations
•    Change management strategies for technical and operational teams
•    Quick wins: Where to start for immediate AI benefits

•    Phased approach to data standardisation across operations
•    Change management strategies for technical and operational teams
•    Investment requirements and expected ROI timelines
•    Quick wins: Where to start for immediate AI benefits
•    Building internal data governance frameworks that enforce standards

•    Rail and Port Synchronization: The Last Mile Challenge 
•    Mixed Fleet Reality: Breaking the 25% Barrier - Overcoming OEM Vendor Lock-in to Enable Full Fleet Remote Operations
•    From Incidental to Intentional: Mining Transport's Hidden Data Gold 
•    Digital Handoffs: Solving the Modal Transition Problem

•    AI vs. Human Authority in Crisis: When should AI emergency systems make autonomous decisions versus requiring human override during critical mining incidents? 
•    New Emergency Categories from Automation Failures: How do mining operations manage unprecedented crisis scenarios when autonomous equipment, AI safety systems, or communication networks fail simultaneously? 
•    Crisis Communication in Hybrid Operations: How can emergency communication strategies adapt for mixed human-AI workforces while maintaining continuity when technology-dependent systems fail?
 

•    Cloud-native architectures for mining data lakes
•    Real-time data streaming from IoT sensors
•    API-first approaches to system integration
•    Data mesh architectures for decentralized ownership
•    Cost optimization strategies for massive data volumes

•    Why traditional operator-dependent process control creates bottlenecks, inconsistencies, and limits optimization potential in modern mining operations
•    How sensors, real-time data analytics, and intelligent control systems are replacing manual decision-making with automated process optimization
•    Demonstrating improved recovery rates, reduced operating costs, and enhanced safety through fully automated process plant management

•    Legacy System Integration Strategies
•    Risk Management and Operational Resilience
•    Architecture, Connectivity and Governance Frameworks

•    The Procurement Puzzle: Do AI solutions fit standard ROI models or department categories - new frameworks for evaluating cross-functional technologies?
•    White Collar Disruption Coming: Predictions of AI eliminating administrative positions while operational roles remain - preparing workforce for fundamental shifts 
•    Big vs. Agile Players: Are some companies "too big" to incentivize innovation - lessons from different organizational scales 
•    Beyond Operational Focus: Industry fixation on tonnage metrics misses serious business process automation opportunities - expanding AI vision beyond production metrics 

•    Renewable energy integration and smart grid management
•    Battery-electric vs. hydrogen equipment - operational insights
•    AI-optimized energy consumption across operations
•    Carbon capture and utilization technologies in mining
•    Real-time emissions monitoring and automated reporting

•    Evolution of training roles in digital mining operations
•    Skills required for modern training professionals
•    Building training organisations that support digital transformation
•    Career pathways in technology-enabled training