It’s AI Jim, but not as we know it. The first generation of the AI revolution has delivered some well-worn paths in advancing the science of condition monitoring, improving our ability to diagnose, predict and track asset health. But the delivery of real outcomes from this has been patchy. For every Rolls Royce there are half a dozen tales of woe. A thousand seeds never germinating. Promises stuck in pilot purgatory. Ivory tower technology teams that never made it into the field, working on problems that nobody cares about, while site teams continue to trudge through a wasteland of broken SAP forms and unmanaged master data.

The opportunity: the next generation of AI technologies will continue to transform what is possible. Agents and GPT-type AI models offer the potential to extend the art of the possible from narrow analytical and predictive tasks into the flexible automation of the broader asset management workflow. Our challenge: driving the asset management transformation required to deliver on this promise will grow increasingly complex, as the range of skills, technologies and teams required to deliver measurable outcomes grows increasingly diverse.

In this session we will take you through the promise of AI 2.0, the potential for the frontier of asset management and explore some examples and lessons learned in delivering these outcomes in the field from two and a half years within Fortescue.

What happens when you’re asked to make high-stakes decisions in an area where you’re not the expert? For this speaker, it was being tasked with cutting eight positions in a department that was already stretched thin. The imposter voice was immediate: “You don’t know enough to get this right.”

Drawing on real past experience as a superintendent and knowing that stretching leaders across multiple sites would erode culture. Instead, making the call to restructure—creating distinct pathways for both technical mastery and leadership.

The solution brought its own challenges: leaders without deep technical expertise struggled to earn credibility. It became clear that leadership is never about knowing everything. Whether you’re an insider or outsider, it’s about making the best possible decision with the information you have, and building structures that sustain your people.

Hear how the “outsider lens” became an asset. By reframing control systems as a form of asset management, not only reshaping our strategy but also earning the respect of the very toughest critics. The experience revealed that imposter syndrome tends to shout the loudest when the stakes are highest—but that tension is also evidence of growth.

This session will explore how to navigate the imposter–innovator paradox, showing that leadership is less about having all the answers and more about owning your choices, learning from their consequences, and building trust along the way.

Australian industrial organisations are facing critical workforce, knowledge, and capability gaps. With 62% reporting acute shortages in maintenance and reliability roles, and nearly 40% of technical know-how leaving annually due to retirement and turnover, retaining skills isn’t just an HR issue, it’s an operational imperative. This session explores practical methods for translating core competencies into everyday capability, bridging generational knowledge divides, and building resilient teams ready for evolving digital, decarbonisation, and business demands. Attendees will walk away with actionable ideas for keeping knowledge in-house, reducing costly misalignment, and unlocking real business impact.

Managing rail shutdowns comes with several key challenges, many of which are common across industries. The challenges faced required significant change management, stakeholder engagement and problem solving. There was a disconnect in the team around buy-in for what is best for business, lacking a customer focused approach, and a change resistant attitude. Additionally, there was a perception that closure performance was consistently poor/overrunning against plan and a lack of data to verify or analyse if this perception was reality.

Coming from a mining background into rail, I identified that these challenges required a data approach, shift in team mindset and stakeholder engagement.

Over the last 12 months, we have:

• Developed a performance reporting framework identifying trends, gaps and opportunities
• Shifted team culture toward continuous improvement and customer impact
• Enhanced transparency with timely updates to external stakeholders
• Refined recovery planning for real-time decisions balancing reliability and throughput
• Implemented proactive measures in a reactive environment
• Established a team mindset that maximizes decision-making under time pressure
• Used data and communications to support both planned and unplanned situations

A 2025 MIT report highlights that 95% of AI pilots have failed. The data landscape in industrial asset management is growing not only in volume, but also in complexity. At the same time, expectations for data to be Findable, Accessible, Interoperable, and Reusable (FAIR) are rising rapidly.

The lesson here is clear. For future Enterprise AI to be successful, we need to find practical ways to manage an increasingly inconsistent and fragmented data landscape.

In this talk we discuss the role of Linked Data in the future of industrial asset management. We explore how the existing Semantic Web framework, including the Resource Description framework (RDF), underpins successful enterprise AI and give practical guidance to Linked Data implementation in industry.

• The 2025 Data Landscape in Industrial Assert Management
• An introduction to Linked Data and the Semantic Web framework
• The role of Linked Data in future enterprise AI with industry examples
• Practical guidance and first steps for organisations implementing a Linked Data strategy

Most asset management processes and deliverables can be traced back to five fundamental corporate datasets. Consequently, the scope and quality of these datasets act as a limiting factor – they predetermine how far up the asset management maturity curve an organisation is capable of progressing.

Unlike other limiting factors in asset management (strategy misalignment, lack of resourcing, etc.) dataset limitations are often intractable and require large investments in time, capital and organisational change management to alleviate.

While 72% of Australian asset-intensive organisations are racing to implement AI in maintenance and reliability, only 23% are seeing meaningful returns. This isn't a technology problem. It's an organisational one, and it's not limited to this industry. The companies winning with AI aren't just deploying smarter algorithms; they're fundamentally restructuring how humans and machines collaborate, make decisions, and create value.

With practical examples, you'll discover why organisations are struggling with AI projects and how those that are thinking beyond the pilot are more rapidly able to unlock the potential that AI promises. Drawing from real-world case studies across a variety of industries, we'll explore:

Regardless of your role, this session will help you influence your organisational roadmap for turning AI potential into operational reality. Be the person who uses AI to your advantage, not the person who has the fear of being obsolete.

• The gap between the promise and reality with AI
• What foundational elements are critical for success
• The key enablers for the human-AI workforce of the future
• Practical strategies to build AI readiness

Introducing change in any organisation is challenging. Doing so in a large recently merged electricity distribution utility with different people, processes, and systems might seem even more challenging. Doing all of this in addition to your day job seems downright crazy.

Take a trip down the rabbit hole as we explore an example of doing just this, introducing new systems and thinking to systematise asset management and risk management benefits for an organisation, and surfacing asset management insights for actionable decision making.

• Leading strategic change in engineering-focused organizations
• Understanding personality types and change tolerance in technical environments
• Thinking like your customer and asking the right questions
• Finding the optimal pace of change for your organization
• Defining and measuring success throughout the transformation
• Embedding change while pushing boundaries for continuous improvement
• Keeping implementation simple and avoiding perfectionism
• Surrounding yourself with the right people to drive change

Using data and technology to completely alter the way we do maintenance has never been so topical as it is today, and yet, we haven’t really seen any big transformations in this space to date. On one side, we have an overload of available data, to enable us to make these radical changes, and on the other, we have foundational work practices, that can significantly impact the usefulness and accuracy of this data, and in turn, the positive impact in the maintenance domain.

1. The importance of strong work practices, in the realms of quality data
2. Why do work management processes fail
3. Some key actions you can take to address these gaps
4. How better data from a strong foundational base can improve pace of change in maintenance
5. Worked example of this in practice

Maintenance builds often emphasise data loading over long-term reliability. In Pluto Train 2, we reversed that approach by embedding reliability principles from the start—aligning maintenance strategies, spares, and procedures with operational needs. Structured against ISO 14224 standards, the build achieved consistency, compliance, and a strong foundation for analytics. This reliability-first strategy delivered seamless Day 1 operations, minimised rework, and created enduring asset performance.

• Applied key reliability techniques across large equipment base
• Built fit-for-purpose maintenance build tool to support planning
• Conducted on-site equipment surveys to fill critical data gaps
• Structured data in alignment with ISO 14224
• Integrated assurance processes to reduce handover risks

This session explores how reliability at DP World has evolved from a tactical task into a global movement powered by people.

Across more than sixty countries, we’ve built a culture that’s human-centered and technology-enabled, united by a shared language that starts on the terminal floor and reaches the executive office.

Our journey began in 2013 with the arrival of our first reliability engineer. Since then, reliability has grown—not just in numbers, but in mindset. Today, thousands across our ports and terminals speak the language of reliability with purpose, pride, and conviction.

The movement continues to expand, creating champions who look beyond their own sites, support others, and learn from each other’s strengths. Together, they’re building a culture where reliability is more than a function—it’s a unifying force across regions and roles.

In this session, you’ll hear the voices of our people, sharing real stories that answer the questions many reliability professionals ask themselves—helping them connect the dots, find clarity, and shape the next step in their own reliability journey.

• Developed a performance reporting framework identifying trends, gaps and opportunities
• Shifted team culture toward continuous improvement and customer impact
• Enhanced transparency with timely updates to external stakeholders
• Refined recovery planning for real-time decisions balancing reliability and throughput
• Implemented proactive measures in a reactive environment
• Established a team mindset that maximizes decision-making under time pressure
• Used data and communications to support both planned and unplanned situations

When veteran technicians face unfamiliar digital interfaces, or planners must adopt workflows designed by IT professionals who've never executed a work order, adoption failures become inevitable.

Enterprise systems and major digital transformation projects that are designed to optimise reliability, often create complexities that undermine the very performance they promise to deliver. This session explores why digital transformation in maintenance and asset management frequently falls short, and what it takes to bridge the gap between technological capability and frontline adoption.

• Organisations operate disparate systems, with some managing 100’s of applications.
• System transitions often trigger "data degradation" with new platforms paradoxically producing lower-quality maintenance records than the legacy systems they replace.
• Technicians spend more time navigating systems than maintaining assets, eroding reliability performance.
• The core issue isn't tech: it's the collision between sophisticated enterprise platforms and diverse workforces spanning generations and skill sets.
• Parallel systems can build confidence rather than force abrupt transitions.
• Peer-based training using respected tradespeople as champions, not IT staff explaining workflows they've never performed.
• Field-first design for mobile devices, gloved hands, and industrial environments, where maintenance happens.
• Small-scale validation that proves value to sceptical crews before enterprise-wide rollout.

This keynote frames reliability in financial terms - highlighting how a well-executed reliability management strategy influences profit, return on net assets (RONA) and share price. You will see the difference between the industry leaders and laggards and learn how to close the gaps to turn the potential benefits into real profit. This is not a maintenance seminar. Rather, we take a cross functional look at reliability management and link it to key financial performance indicators.

• Relate plant reliability to profit, return on net assets (RONA), share price and other key financial performance indicators.
• See the cross-functional nature of process reliability management – it is not all about maintenance.
• Move beyond thinking in terms Overall Equipment Effectiveness (OEE) to Overall Business Effectiveness (OBE) to manage reliability across the entire value stream.
• Delve into the human factors of failure, including psychological and social psychological drivers.
• Design for reliability, maintainability, operability, and flexibility the genetic code of the manufacturing process.
• Operate for reliability, including supply chain management and customer/SKU rationalisation.
• Maintain for reliability.
• Deploy a comprehensive and lasting reliability management strategy that drives value for your shareholders.

Climeworks is pioneering direct air capture (DAC) technology to permanently remove CO₂ from the atmosphere. As both OEM and owner-operator, they face the dual challenge of designing frontier technology for high reliability while defining maintenance practices for equipment operating in Iceland's harsh conditions. High uptime is critical to reducing carbon removal costs and achieving profitability.

Doug's career spans maintaining critical rotating equipment on ExxonMobil's offshore platforms, commissioning gas turbines and centrifugal compressors for Solar Turbines Australia, and scaling manufacturing as Director of Manufacturing at Tesla, directly reporting to Elon Musk. He now applies these lessons to making carbon removal economically viable at Climeworks.

• What is direct air capture and how it works
• How to overcome the challenges of designing and deploying first-of-a-kind technology
• Influencing R&D and equipment design to deliver a safe and reliable product
• How to build a maintenance & reliability team to service nascent technology in remote locations
• Convincing the executive team to see high availability as a value, not a cost