Financial services institutions are rapidly adopting generative AI technologies to enhance capabilities such as instant credit decisions, fraud prevention, and personalized customer engagement, but achieving these advancements requires a robust data infrastructure that many firms have yet to fully develop. While previous modernization efforts focused on cost efficiency and agility through cloud migrations and microservices, they did not address the real-time data needs of AI applications. To truly harness AI's potential, financial services must implement an AI-ready operational data layer that ensures low-latency data access, compliance with regulatory frameworks, and the ability to handle new AI demands like vector searches and real-time contextual insights. This shift involves not just upgrading existing systems but fundamentally reimagining how data serves AI-driven intelligence, allowing institutions to quickly deploy intelligent services that redefine customer expectations and operational efficiency. Early adopters of AI-ready infrastructures are already gaining competitive advantages, as they can provide advanced services such as real-time fraud detection and instant loan decisions, suggesting that the time to transition is now.