CDAO Brisbane schedule

Most AI initiatives deliver impressive productivity gains—but fail to move the needle on business performance. This keynote challenges leaders to rethink AI as a strategic resource, showing how to shift focus from efficiency to outcomes, unlock value and deliberately capture financial impact across the value chain. The core message is clear: AI doesn’t transform businesses—leadership decisions do.

As agentic AI moves from pilot to production, the real constraint is no longer model capability. It is trusted access to authoritative external data. In this session, Ajay Kumar, Head of MCP Services at InfoTrack, will show why legacy API integrations are too brittle, fragmented and human-dependent for the next wave of AI-enabled workflows.

You’ll learn how InfoTrack is using Model Context Protocol (MCP) to create a governed, auditable gateway to authoritative data sources, giving agents secure access to the tools and context they need to operate reliably. From insurance and healthcare to financial services and property, this approach unlocks workflows that were previously too fragmented, too labour intensive, or too constrained by legacy systems to automate effectively.

For CDAOs, the opportunity is clear: when agents can safely access trusted data with governance, provenance and control built in, organisations can reduce the “hallucination tax”, remove operational friction, and build a stronger foundation for scalable, production-grade AI.

• Where do most data projects hit roadblocks, and how can leaders identify these early?
• What team structures and collaboration approaches ensure successful execution and delivery?
• How can organisations move beyond pilots and proofs-of-concept to deliver measurable business impact?

Moderator
Tanveer Singh Bal Director, Business Development (Australia & New Zealand) Tiger Analytics
Speakers
Johnny Serrano Chief Information Officer CS Energy
Beverley Paratchek Head of Data Virgin Australia
Tammy Wigg Chief Data Analytics Officer Aurizon
Nick Jewitt Head of Data & Analytics Harcourts  
Tracy Whitelaw Chief Digital Officer LGAQ 

Imagine a world where every system, workflow, and AI agent in your company operates from a single, shared source of truth—where every piece of data is fully understood in its real context. This is the power of Trusted Context, the foundation that transforms raw data into actionable intelligence and drives smarter, faster decisions. In this session, you’ll learn how Informatica, now part of the Salesforce family, is helping leading companies like Takeda and Holiday Inn build this new standard for intelligent enterprises. We’ll walk you through a practical blueprint to create your own trusted context, deeply integrating world-class data management with the platforms where your business runs.

• How should data, AI and analytics leaders decide when to buy versus build — and what criteria matter most when making that call?
• With so many vendors claiming to be “end-to-end,” how can leaders identify which partners truly hit the sweet spot for their business needs?
• How can organisations manage vendor partnerships effectively while ensuring adaptability and avoiding lock-in or over-dependency?
• Where has vendor investment delivered the most value — and where has building in-house proven to be the smarter long-term strategy?

Moderator
Emma Liversidge GM Data, AI & Automation The Lottery Corporation

 Speakers
Ben Pattison CDAO Flight Centre Travel Group
Nick Warwick General Manager Data & Integration Royal Flying Doctor Service
Gemma Lipovski Head of Data and Projects NTI Limited
Dharshun Sridharan Principal – Automation & AI IAG 

Most AI initiatives don’t fail because of weak models — they fail because organisations can’t trust or activate the data those models rely on. As AI moves from experimentation to autonomy, fragmented data, static governance, and disconnected systems quietly become the real blockers to scale.

In this session, David Irecki (CTO, APJ, Boomi) explores the shift required to move beyond pilots and unlock measurable AI value. Drawing on real-world examples and emerging best practices, he will show how data readiness, integration, and governance must evolve to support agentic AI operating safely inside core business processes.

• How to responsibly embed large language models into modern data processes
• Real-world case studies of operationalising analytics with LLMs in production
• Lessons learned from moving beyond proof-of-concept to productinising
• Practical steps for data leaders to drive responsible AI adoption

As organisations move from AI experimentation to intelligent, delegated decision-making, a new question emerges: what data is your AI actually acting on? In an instantaneous economy, customer intent forms and fades in seconds. Yet many enterprises still rely on delayed, decontextualised signals to power automation.

Real-time, consented customer interaction data is fast becoming the true differentiator, enabling context-aware decisions while preserving trust and compliance. This session explores why data velocity, identity integrity, and governed activation are foundational to scalable AI, and how forward-thinking CDAOs are preparing their architecture for what comes next.

Responsible AI isn’t just about meeting standards; it’s about earning trust and creating experiences that truly matter. Technology alone doesn’t guarantee success. The real differentiator is the human factor. 

This session will explore how responsible practices and trust work together to shape customer experience and drive meaningful adoption. When AI is transparent, fair, and aligned with human values, it becomes more than a tool; it becomes a trusted partner. But remember, empathy and accountability are essential for unlocking AI’s full potential and how putting people at the centre ensures AI delivers on its promise.

• How can organisations design governance frameworks that evolve as AI and automation capabilities advance?
• What controls are essential to balance innovation speed with ethical and regulatory compliance?
• How do you ensure AI accountability and transparency across complex automated systems?

• What responsibilities, controls, and standards are required to ensure AI is ethical, explainable, and compliant?
• How can organisations create transparency and trust in AI decision-making—for regulators, customers, and internal leaders?
• What operating model best supports responsible AI across people, process, and technology? 

• How can we streamline governance frameworks so they are practical, lightweight, and embedded into day-to-day work?
• What governance activities create real business value—and which can be removed to eliminate bureaucracy and resistance?
• How do we drive adoption and accountability across the business without overwhelming stakeholders?

• What are the key levers data leaders can pull to convert AI initiatives into measurable business results?
• How should data leaders navigate the tension between experimentation and responsible AI practices?
• What organisational capabilities—data, talent, infrastructure—are critical for scaling AI successfully?

Moderator
Liz Daykin Past President DAMA

Speakers
Tim Johnson Head of Intelligent Solutions Delivery Suncorp
Kris Watt Head of Automation and AI RACQ
Mysun Mathukutty Sr. Manager, Data Management and Governance Queensland Government 
Abbey Beck Data Governance Specialist Super Retail Group 

• How can leaders inspire data-driven behaviours across business units that are resistant or unfamiliar with using data in decision-making?
• What practical strategies and governance structures have helped Australian organisations successfully scale data literacy beyond technical teams?
• Where have organisations failed in their data culture programs, and what lessons can we take from those missteps to avoid repeating them?