Leaders Roundtable: The AI Execution Gap: How FSI Leaders are Fixing the Data Foundations [Japan]

Japan’s financial services organisations are moving AI towards production, but legacy systems, fragmented data, and governance models built before generative and agentic AI create friction. Data can be difficult to access across existing environments, while data protection, operational resilience, model risk, and third-party technology dependencies add complexity as AI moves into business-critical processes.

The challenge is not simply making data available to AI. It is creating an environment where data can be accessed consistently, governed appropriately, and used across AI applications without introducing new silos or control gaps.

Ecosystm research highlights the gaps in Japan’s Financial Services sector:

• 72% cite governance and compliance as a key barrier
• Only 38% of FSI leaders express confidence in their data strategy
• 53% are actively working on making data reliably accessible for AI use

For Japanese financial institutions, this makes the underlying data environment an important part of the AI strategy. Data needs to work across structured and unstructured sources, legacy and modern platforms, and increasingly diverse AI workloads. Governance also needs to be embedded into how data is accessed and used, rather than added after applications are deployed.

Join us for a candid, off-the-record Ecosystm Leaders Roundtable, where senior peers and regional technology experts will examine the practical constraints shaping AI adoption in Japanese financial services and the decisions that matter next.

The discussion will cover:

• Regional and global perspectives. How financial institutions are evolving data strategy, governance, and AI operating models as AI moves into production.
• Operating model gaps. Where business, technology, data, and risk teams struggle to align, and what is improving decision-making and delivery.
• Regulatory considerations. How institutions are managing data protection, governance, risk, and regulatory expectations as AI use expands.
• Ecosystem decisions. What should be built, bought, or developed with partners as AI architectures and technology providers evolve.
• Value realisation. How institutions are assessing the business case for AI and connecting data investments to measurable business outcomes.

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