Leaders Roundtable: The AI Execution Gap: Turning Data Foundations into Business Value

Financial services organisations in Australia are investing in AI; but turning that investment into measurable business outcomes remains difficult. Legacy data environments are costly to modernise, architectures remain siloed, governance models were not designed for AI workloads, and regulatory expectations from bodies such as APRA and evolving privacy reforms add complexity. At the same time, leaders are under pressure to determine where AI investment should be prioritised, what should be built or bought, and where it can deliver meaningful revenue, productivity, or cost outcomes.

Ecosystm research highlights the structural gap:   

• Only 22% of FSI leaders express confidence in their data strategy
• 67% cite governance and compliance as a key barrier
• 57% are still working through how to make data reliably accessible for AI use

These challenges are not limited to Technology or Data teams. They affect how organisations prioritise AI investment, manage risk, allocate resources, and assess whether individual initiatives can scale beyond experimentation.

Addressing this requires a shift in how data is organised and governed, enabling it to be accessed consistently, used safely across structured and unstructured sources, and connected into AI workflows without creating additional fragmentation. It requires a foundation where data is AI-ready by design, not retrofitted through layers of integration and exception handling.

Join us for a candid, off-the-record Ecosystm Leaders Roundtable, where senior peers and global technology and business experts will examine what needs to change in the technology and data foundations, and how leadership teams can make better decisions about where AI investment will create measurable value.

The discussion will cover:

• Investment priorities. Where organisations should direct AI investment, and how leaders are assessing competing opportunities across productivity, cost, revenue, and customer outcomes
• Data and technology foundations. What needs to change in data architecture, accessibility, governance, and legacy environments to support AI at scale
• Operating model gaps. Where alignment between business, Technology, Data, Finance, and Risk breaks down, and what improves execution at leadership level
• Risk and regulatory trade-offs. How institutions are balancing regulatory scrutiny, risk exposure, and delivery speed when scaling AI
• Build, buy, or partner decisions. How leaders are assessing the cost, control, capability, and strategic implications of different approaches to AI
• Value realisation. How organisations are moving beyond AI activity and pilots to assess measurable impact on revenue, margins, productivity, and the cost base

Plus: Attendees receive a standing invitation to a complimentary, tailored data strategy session with the Snowflake x Accenture FSI leadership team.