AI Readiness:
How should financial service organizations
rethink their data strategy to stay
ahead in an AI-first world?

Every financial institution nowadays wants to harness AI — but without the right foundation, even the most advanced initiatives can fall short. Many firms struggle to move beyond experimentation and turn AI into a true competitive advantage. The difference between success and stagnation often comes down to one factor: data readiness..

Real-time portfolio analytics, intelligent risk management, and AI-driven fraud detection all depend on having a high-performance data strategy. Without a scalable, low-latency baseline, institutions risk increasing costs, limiting impact and missing opportunities in a rapidly evolving financial landscape.

So, how can firms ensure their AI initiatives deliver measurable business value rather than becoming costly, complex experiments?

Participants joined us for an exclusive roundtable discussion where we explored:

• How AI-ready data strategies enhance portfolio management, client retention, and profitability
• Overcoming data bottlenecks to power real-time risk analytics and fraud detection
• The role of real-time data processing in improving investment decision-making
• Lessons from industry leaders who have successfully scaled AI-driven financial applications

AI is no longer just an innovation play — it’s a critical business driver. In this discussion, participants discovered how to build a data foundation that enables AI success and boosts agility, ensuring their organizations remain competitive in an increasingly AI-driven financial landscape.