Financial institutions’ effectiveness with agentic AI systems depends critically on the quality and governance of underlying data infrastructure. The article examines how data preparation, integration, and management practices directly impact the performance and reliability of AI agents deployed in financial services. Proper data architecture and oversight are essential for institutions seeking to maximize returns on agentic AI investments.