Data governance & infrastructure readiness agentic AI

The move to Agentic AI changes everything—from linear pipelines to continuous, high-speed data networks. Learn how to transform your data infrastructure to eliminate "ghost-data liability" and ensure your AI agents act on accurate, real-time information.

What you will learn

• The cost of bad data: Understand how poor data quality leads to erroneous model outputs and user frustration, learning from critical failures.
• Agentic vs. traditional AI: Differentiate the data relationship, moving from static, bounded datasets to the continuous, networked reasoning cycle of Agentic AI.
• Bridging the infrastructure gap: Learn to transition from legacy batch processing (the "stale-data wall") to the real-time data streaming required for autonomous action.
• Maturity levels: Assess where your organization stands on the four levels of AI agentic environments and map your path to adaptive, future-ready infrastructure.
• Three pillars of readiness: Master the foundations of data quality (Fairness, Completeness, Accuracy), accessibility (Real-time availability, APIs), and security (CIA Triad: Confidentiality, Integrity, Availability).
• Navigating regulations: Prepare for the evolving regulatory landscape (HIPAA, GDPR, EU AI Act) by implementing governance designed for machine-speed autonomous access.