Rex Washburn
Arif Rajwani
As organizations accelerate their AI initiatives, many are discovering that success depends less on the models themselves and more on the quality, governance, and security of the data that powers them.
The rise of Agentic AI introduces a new set of challenges that extend beyond the data lakehouse.
Modern data platforms have helped organizations centralize and govern large volumes of analytical data. However, AI agents increasingly require access to information that remains distributed across operational systems, enterprise applications, cloud platforms, and business processes.
How can organizations provide trusted, governed access to both analytical and operational data? How should security, compliance, and accountability evolve as AI agents become active participants in enterprise workflows? What architectural principles will enable organizations to balance innovation with control?
Join Rex Washburn, Chief Data Architect at CDW, and Arif Rajwani, Senior Solution Architect at Denodo, for a strategic fireside chat exploring the evolving relationship between data governance, security, and AI.
Through real-world observations and industry perspectives, this discussion will examine how organizations are preparing their data foundations for Agentic AI while balancing innovation, risk, and enterprise trust.
What You'll Learn
- How leading organizations are evolving governance and security strategies as AI moves from analytics to operational decision-making.
- Why Agentic AI requires access to both analytical and operational data, even in organizations with mature lakehouse and cloud data platform investments.
- Architectural principles for enabling trusted, governed data access across applications, operational systems, and modern data platforms in an increasingly agent-driven future.
