• The key digital trends reshaping Australia's mining industry
• How leading operators are leveraging AI, automation and advanced analytics
• Balancing innovation with operational realities and workforce adoption
• Emerging technologies expected to define the next decade of mining
• Strategic priorities for building a connected and intelligent mine

• Aligning AI investments with long-term business strategy
• Creating an organisational culture that embraces innovation
• Balancing operational performance with digital transformation
• Developing the leadership capabilities required for an AI-driven future
• Lessons from enterprise-wide transformation programmes

• Moving beyond isolated proofs of concept
• Building trusted data and digital foundations
• Overcoming organisational barriers to scale
• Demonstrating measurable operational value
• Lessons learned from enterprise AI deployment

• Breaking down data silos across mining operations
• Improving data quality to enable trusted AI
• Transforming operational data into real-time insights
• Building scalable data platforms for future growth
• Transforming data into measurable business outcomes

• Explore real-world applications of machine learning and AI to enhance grade control, mineral estimation, and operational decision-making across mining operations.

• Discover practical approaches to integrating AI into QA/QC workflows, including the use of predictive models for material properties such as moisture content to improve accuracy, consistency, and confidence in operational outcomes.

• Learn how interpretable AI models can support business-critical decisions, drive stakeholder trust, and demonstrate measurable value in production environments.

• Gain insights from firsthand experience deploying AI solutions in mining operations, including lessons learned around data quality, model validation, change management, and the transition from proof of concept to operational adoption.

• Understand the challenges, successes, and key considerations when scaling machine learning initiatives from experimentation to practical, day-to-day use within mining organisations.

Understanding what differentiates AI agents from today's chatbots and copilots, including planning, tool use, reasoning and the ability to execute multi-step workflows  

• Identifying where AI agents can deliver the greatest near-term value across maintenance, procurement, reporting and operational decision support  

• Designing governance, human oversight and accountability into AI agents from the outset to enable safe and responsible adoption  

• Building a practical roadmap from individual productivity tools to enterprise-wide AI-enabled workflows  

• Looking beyond AI agents towards digital colleagues and the next generation of autonomous enterprise systems 

• What differentiates agentic AI from today's copilots and predictive AI

• Early use cases in mine planning, maintenance, geology and procurement

• Governance, oversight and operational risk

• Where mining companies should experiment over the next 2–5 years

• Explore why resilient connectivity has become the critical foundation for digitalisation, AI and autonomous mining operations across increasingly connected mine sites.

• Examine the challenges of designing network infrastructure across geographically dispersed operations, balancing enterprise-wide standards with the unique requirements of individual mine sites.

• Understand how reliable communications infrastructure enables real-time data exchange, remote operations and the adoption of emerging digital technologies.

• Discover the key considerations for building scalable, future-ready connectivity strategies that support the next generation of intelligent mining operations.

• Using digital twins to optimise mine planning
• Integrating real-time operational data
• Supporting predictive and scenario-based decision-making
• Improving collaboration across functions
• Scaling digital twins across mining operations

From Process Monitoring to Operational Intelligence 

• Moving beyond monitoring to operational intelligence that enables real-time decision-making 

• Turning process and asset data into actionable insights that improve productivity, stability and asset performance 

• Leveraging AI, advanced analytics and digital twins to optimise mineral processing operations 

• Embedding digital capabilities alongside metallurgical expertise to accelerate operational excellence 

• Building the organisational capabilities needed to scale operational intelligence across the processing value chain 

• Defining the next generation of mining operations through connected data, intelligent systems and continuous optimisation 

• Building the foundations for effective remote mining operations beyond traditional SCADA.
• Overcoming the "keyhole effect" through real-time data platforms, interoperability, and operational context.
• Enabling Decision Intelligence with Industrial AI, digital twins, and progressive automation.
• Integrating maintenance, operations, and business data for faster, smarter decision-making.
• Extending optimisation from individual plants to the entire pit-to-port value chain.
• Redefining the operator's role from monitoring and control to orchestration and continuous improvement.

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. 

• Scaling AI Beyond the Pilot Phase: Turning Innovation into Enterprise Value
• Building Trusted Data Foundations for the Intelligent Mine
• Securing the Connected Mine: Cybersecurity & Operational Technology
• Preparing the Workforce for the AI Era: Driving Adoption and Change
• Demonstrating ROI: Measuring the Business Value of AI & Digital Investments
• AI Governance & Responsible Innovation: Building Trust in Operational AI
• The Roadmap to the Autonomous Mine: What's Still Missing?
• Partnering for Innovation: Collaborating with Startups, OEMs & Technology Providers

• Accelerating innovation through industry collaboration

• Supporting AI adoption across the sector

• Developing the future digital workforce

• Strengthening Australia's mining technology leadership

• Creating an ecosystem that accelerates innovation

Under Invitation: Minister for Mines, Petroleum and Exploration, Honourable Daniel Pastorelli MLA 

• Prioritising AI initiatives that deliver measurable operational outcomes
• Lessons from successfully scaling AI across multiple sites
• Balancing quick wins with long-term transformation strategies
• Embedding AI into day-to-day operational decision-making
• Where mining companies should focus investment over the next five years

• Examine how mining organisations can accelerate AI adoption while managing the unique cybersecurity and digital risks associated with increasingly connected mining operations.

• Identify the key security considerations when deploying AI across operational technology (OT) and IT environments, including protecting critical infrastructure, managing third-party risks and maintaining workforce trust.

• Understand how practical governance and security frameworks can enable AI adoption while balancing innovation, operational resilience and regulatory obligations.

• Consider the strategies organisations are adopting to strengthen cyber resilience, secure AI-enabled operations and prepare for the next generation of intelligent mining.

• Five emerging technology companies presenting breakthrough mining solutions
• Practical applications of AI, robotics, machine vision and digital twins
• Early deployment results and customer success stories
• How startups are solving long-standing operational challenges
• Connecting miners with the next generation of technology innovators

1. AI + Optimisation: Turning Tacit Maintenance Knowledge into Better Shutdown Schedules

• Combining robotics, AI and computer vision to automate physical tasks
• Improving safety through intelligent inspection and monitoring
• Human-robot collaboration across mining operations
• Real-world deployment experiences from early adopters
• The future role of intelligent robotics across the mine site

• Combining AI with advanced process control to improve plant performance
• Using real-time operational data to maximise throughput and recovery
• Building operator trust in AI-driven recommendations
• Measuring operational and financial improvements
• The future of autonomous mineral processing

• Why do so many AI proof-of-concepts fail to become production-ready solutions? 

• What organisational capabilities—in data, governance, leadership and operating models—are essential for scaling AI? 

• How can mining companies right-size governance without slowing innovation? 

• Who should own AI once it moves from experimentation into day-to-day operations? 

• What changes between the PoC, pilot and production stages, and how should organisations adapt? 

• How do mining companies continuously evaluate, govern and improve AI once it's deployed? 

A Representative from the Geological survey of Queensland 

• Building resilient communications infrastructure
• Leveraging edge computing for real-time decision-making
• Supporting autonomous fleets through connected operations
• Managing bandwidth, latency and cybersecurity
• Lessons learned from deploying connectivity at scale

• Building compelling business cases for AI investments
• Selecting KPIs that matter to executive leadership
• Scaling successful initiatives while avoiding common pitfalls
• Aligning digital investments with strategic objectives
• Lessons from organisations delivering measurable business value

• Which roles will evolve over the next decade

• Upskilling engineers, operators and frontline supervisors

• Leading organisational change at scale

• Creating trust and adoption across the workforce

• Attracting digital talent into mining

• Coaching mid-level leaders to develop judgment, expertise, and a shared sense of purpose in increasingly AI-enabled and complex operating environments

• The convergence of AI, autonomy, robotics and advanced analytics
• How intelligent mines will reshape productivity, sustainability and safety
• The future skills required for AI-enabled operations
• Strategic priorities for remaining competitive in a rapidly changing industry
• A roadmap towards the fully autonomous mine