Financial institutions need AI agents that function reliably in real-time environments, while meeting stringent regulatory and governance requirements. This requires more than powerful models—it demands understanding the organization’s business logic, reporting structures, compliance constraints etc.
Join TDWI Research Fellow Donald Farmer and experts from Databricks and Impetus to learn how context-aware agentic AI helps financial institutions strengthen compliance, manage risk, and scale trusted AI on a unified, governed data foundation.
Attendees will discover how to address the context gap between what AI models know and what their enterprise knows, so agentic AI deployments deliver the intended business outcomes. Drawing on real-world customer success stories, the discussion explores how financial institutions can move beyond rule-based controls toward explainable, auditable agentic decisioning at scale.
Key Takeaways:
- Why explainability and auditability are becoming as critical as speed and accuracy for agentic AI in financial services
- The four components of the context gap and how financial enterprises can address them
- Understanding governance barriers that separate AI experimentation from measurable value
- How to bring real-time risk management, regulatory compliance, and AI-driven decisioning onto a unified, governed platform
- Real-world applications across risk & fraud mitigation and regulatory compliance orchestration
- The role of Databricks Lakehouse, Genie, Agent Bricks, and Impetus Leap™ AI in your governance architecture
- A practical roadmap for CXOs to build a robust semantic foundation and activate trusted AI agents
