Building the Data Foundation for Agentic AI with Snowflake and Precisely
11 attendees from 11 groups hosting
Details
AI is entering a new phase. Instead of simply generating content, agentic AI systems can reason, plan, and take action in real time. But these systems are only as effective as the data behind them. When data is incomplete, inconsistent, duplicated, or outdated, AI decisions become unreliable and difficult to trust.
Join experts from Precisely and Snowflake for a practical discussion on what it takes to build a trusted data foundation for agentic AI. This session will explore how organizations are improving data integrity, accessibility, and governance to support AI systems that can operate with greater confidence and autonomy at scale.
You’ll learn where many organizations struggle today, including fragmented data environments, stale information, and governance gaps that limit AI readiness. The conversation will also examine how cloud-native architectures and modern data platforms are helping teams unify, enrich, and operationalize data for real-time AI use cases.
The session will conclude with a short panel discussion featuring industry perspectives, implementation lessons, and practical guidance for organizations beginning their agentic AI journey.
What You'll Learn:
1️⃣ Why Data Integrity Matters for AI: Understand why trusted, complete, and current data is becoming foundational for agentic AI systems and autonomous decision-making.
2️⃣ Common AI Readiness Gaps: Explore the operational and architectural challenges that prevent organizations from delivering reliable, real-time data to AI applications.
3️⃣ Building AI-Ready Data Pipelines: Learn how teams are improving data quality through integration, enrichment, governance, and modernization strategies in the cloud.
4️⃣ Operationalizing Real-Time AI at Scale: Discover how Snowflake and Precisely help organizations deliver accessible, governed, and continuously updated data for AI-driven workflows and decision systems.