Agentic AI is emerging as a transformative force in financial services, promising to enhance decision-making processes across various domains such as fraud detection, compliance, customer experience, and trading by operating semi-independently to observe, reason, plan, and execute tasks without constant human input. Elastic plays a pivotal role in this evolution by providing the essential data foundation and tools necessary for agentic AI to function effectively, including real-time data access, governance, and observability. By integrating with tools like LangChain and employing retrieval augmented generation (RAG), Elastic enhances data retrieval and workflow automation, thereby reducing errors and increasing precision in AI outputs. An example of its application is Elastic's Attack Discovery in cybersecurity, which uses agentic AI to rapidly identify and respond to threats. However, the autonomous nature of agentic AI introduces risks such as hallucinated outputs and privacy breaches, which Elastic mitigates through secure architectures and human-in-the-loop options. As agentic AI continues to evolve, Elastic aims to provide a secure and effective platform for financial institutions to leverage its capabilities while maintaining control and trust.