Taylor McGrath

Enterprise data infrastructure has never been under more pressure — and AI agents are about to demand even more from it. In this session, we explore what it takes to move from insight to action: activating trusted business data as the foundation for agentic workflows that deliver measurable ROI. We'll cover why insights alone don't drive value, how agentic workflows differ from pure agent architectures, and why governance by design — not as an afterthought — is the key to scaling AI safely and predictably. Learn how entity resolution and data quality form the foundation agents need to reason reliably, and how context engineering and explainability ensure those agents remain governed, auditable, and trusted.

In the age of agentic AI, competitive advantage lies not only in AI models, but in the quality of the data agents reason on and the agility of the tools that feed them. To fully realize the ROI of agentic AI, organizations need a platform that enables high-quality data pipelines and provides scalable, enterprise-grade tools. In this session, discover how a unified platform for integration, data management, MCP server management, API management, and agent orchestration can help you to bring cohesion and control to how data and agents are used across your organization.