Arrival and Opening Energy

Sydney’s weather was miserable that morning, with heavy rain and grey skies, but inside the Boronia Ballroom the energy was electric. By 8:30 AM, more than 160+ delegates had gathered, coffee in hand and conversations sparking.

Tim Moon, MC and Co-Founder of DGX, opened the summit by setting two challenges for the room. First, to make connections and use the day to meet people and build relationships. Second, to look for “golden nuggets” — practical insights they could take back and apply in their own organisations. “If you leave with a couple of nuggets and one new connection, we’ve done our job,” he said.

Conference chair Chad Barendse, Co-Founder of DGX, followed, reflecting on how the summit had grown from an idea scribbled over coffee just a year earlier into a sold-out event with 160+ delegates, 30+ speakers, and five sponsors. He underlined why it mattered: “Data and AI governance has never been more important. With AI moving as fast as it is, data governance underpins everything. If we want to scale safely and sustainably, we need the right foundations.”

None of this would have been possible without the support of our sponsors. Thank you to Actian as headline sponsor, Experian and Alation as gold sponsors, and Rubix and Ataccama as silver sponsors.

Keynote: The Hidden Reason AI Projects Fail – Cuan DeVries, Senior Sales Engineer at Actian

The first keynote came from Cuan DeVries of Actian, who opened bluntly: “Look to your left, look to your right. Only one in three of you will successfully deploy AI in the next two years. That’s bloody scary.”

His message was clear. AI projects do not fail because of algorithms, they fail because of weak data foundations. He highlighted the data governance maturity gap, where executives often rate capability higher than frontline teams, a mismatch that drew knowing laughter.

Cuan summed it up with a metaphor: “Data without data governance is just raw ingredients on a kitchen table. Without a recipe, you are not making anything anyone wants to eat.”

Key insights:

• Only 1 in 3 AI projects succeed, and failure usually comes from poor data foundations.
• Executives consistently overrate their organisation’s data maturity compared to staff.
• Data quality, accessibility, and bias are the hidden blockers.
• Data governance maturity models help expose blind spots and align leadership.

Panel: The Convergence of Data Governance and Data Enablement

The morning’s first panel brought together a mix of perspectives: Reshma Devi, Data and AI Risk Leader at Transurban, as moderator, with Payal Pandya, Data Governance Lead at Sportsbet, Bikram Choudhury, Responsible AI Senior Manager at Accenture, and Stuart Brown, Head of Data and Analytics at BT Financial Group.

Reshma opened by asking each panellist to share something outside work, from Payal’s admission that she prefers not to talk about data governance after hours, to Bikram’s new passion for running, to Stuart trading snowboarding for raising his one-year-old daughter. It was the perfect way to humanise the stage before diving into tough questions.

When asked if traditional data governance is broken, Payal was clear: “Yes. Data governance cannot just be about controls. It has to start with the value it creates, not the restrictions it imposes.”

Stuart built on this: “You cannot separate records management from data governance anymore. With AI pulling in PDFs and SharePoint files, you need the whole supply chain governed, not just structured datasets.”

Bikram brought a global lens: “If boards only hear compliance language, they disengage. We need to show data governance as an enabler of value, not bureaucracy.”

The panel closed with a focus on culture and risk. Payal tied data governance to literacy, Stuart warned that “without foundations, speed just multiplies risk,” and Bikram was blunt: “With AI, data governance is not optional. Done badly, the risks accelerate.”

Key insights:

• Data governance must shift from “prevention” to value creation.
• Teams are evolving into connectors across privacy, risk, and AI
• Boards switch off if data governance is framed only as compliance.
• With AI, data governance is non-optional and risks compound at machine speed.
  

Keynote: Dynamic AI Governance – Daniela Elia

Our next keynote is from Daniela Elia, an AI leader and PhD candidate at UTS’s Data Science Institute. She contrasted global headlines: the EU banning social scoring systems under its AI Act, while in the US, an executive order stripped back federal AI governance. Two approaches, just ten days apart, highlighted what she called the pacing problem.

“Traditional data governance policies can take 18 to 24 months to design and approve,” she explained, “while AI systems can retrain in 30 to 90 days. We are trying to govern a technology that no longer exists.”

Her answer: dynamic AI governance, frameworks that adapt as quickly as the technology itself, with built-in review cycles and feedback.

Key insights:

• The pacing problem means static governance cannot keep up with AI.
• Blind spots, bias, and failures emerge after compliance checks if frameworks are too slow.
• Dynamic data governance needs real-time monitoring, adaptive triggers, and multi-stakeholder feedback.
• Leaders, technologists, regulators, and communities each play a role.
  

Keynote: Making Data Governance Stick – Trinity McNicol, KPMG

Trinity McNicol, Associate Director of Data and AI at KPMG, focused on how to make data governance real in daily work. “Start with people and process, because one size does not fit all. But do not wait too long on technology — it is what makes data governance scale.”

Her core message was simple: data governance platforms only matter if they reduce effort and add value. “People do not want more work. They want data governance that makes their lives easier.”

Key insights:

• Start with people and process, then scale with technology.
• Data Governance platforms only matter if they reduce effort in daily work.
• Adoption depends on framing value in terms executives care about, not just “data language.”

Fireside Chat: Migrating with Confidence – Experian & Regional Australia Bank

With Martin Soley, Director of Strategic Solutions at Experian, and Aleena DeLore, Head of Data Management at Regional Australia Bank.

This was a practical talk on how to keep quality high during a live bank migration. It showed why data quality must be owned by the business and technology together, with clear lines of responsibility and real visibility of issues as they move through systems.

Key points

• Give business owners clear sight of data quality at every step so they can act.
• Define who owns which checks, then support that ownership with simple tools and process.
• Tie quality rules to real goals, for example service to regional communities, so fixes lead to outcomes. Data governance provides the guardrails

Keynote: Building a Data Culture that Lasts – Neil Coulson, Transurban

Senior Manager for Data and Data Literacy at Transurban, shifted the focus from tools to people. “Technology will not save you. Data culture is what makes governance stick.”

He described how Transurban built culture into routines by linking governance to strategy, embedding it into delivery squads, and making it part of leadership conversations. Measurement was critical — literacy scores, adoption metrics, and feedback loops showed whether the culture was real.

“People learn from what their managers do, not from what their managers say,” he reminded the room.

Key insights:

• Data governance only succeeds when underpinned by strong data culture.
• Culture grows when governance is tied directly to strategy and delivery.
• Metrics such as literacy scores and adoption rates show if culture is taking hold.
• Leaders must model behaviours — culture spreads by action, not slogans.

That’s Part 1. In Part 2 we’ll cover the afternoon sessions — from Lisa Garbutt on data maturity, UniSuper’s fireside with Alation, and Natalie Hogan’s practical lessons, through to the Modern Data Governance Leaders panel, Canva’s privacy keynote, and the presentation of the inaugural Data & AI Governance Leader of the Year award.