CDAO Brisbane schedule

Reserved for InfoTrack

• 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?

Speakers
Johnny Serrano Chief Information Officer CS Energy
Beverley Paratchek Head of Data Virgin Australia (to be confirmed)
Tammy Wigg Chief Data Analytics Officer Aurizon
Nick Jewitt Head of Data & Analytics Harcourts  

• 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 

• How can AI enable predictive detection of data issues before they cascade into downstream errors?
• What design principles help teams build self-correcting and resilient data pipelines?
• How can organisations maintain the right level of human oversight without slowing agility? 

• 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

• Why do so many AI pilots “work” but still fail to scale, and how do fragmentation and disconnected systems create silent failures?
• Which architectural and governance approaches actually enable enterprise-wide AI instead of isolated experimentation?
• What are the most impactful actions organisations can take in the next 12 months to break down AI islands and build a connected, trusted AI ecosystem?

• How must data operating models evolve to make AI scalable and embedded in daily decision-making?
• What operating structures — from central hubs to embedded product teams — best support AI adoption across the business?
• How can governance adapt to balance autonomy, accountability, and innovation in AI-driven environments? 

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.

• What governance capabilities are essential as organisations move from experimentation to scaled AI
• How can leaders ensure transparency, lineage and risk controls across both structured and unstructured data
• What role can vendors play in helping organisations operationalise responsible AI practices

• 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?