As organizations race to harness AI, traditional data governance and emerging AI governance are converging. Policies that once focused solely on data quality, access, and lineage now directly shape model performance, fairness, and regulatory compliance. In this live panel, leaders from Anomalo, Atlan, Lovelytics, and Databricks will explore how to build a unified governance framework that spans from raw data to production AI systems.

Join us live to discover how:

• Anomalo shares how automatically detecting anomalies and drift in both structured and unstructured data helps AI models learn and infer from trustworthy information.
• Atlan shares how a modern active metadata platform enables cross-functional visibility, governance, and collaboration — helping data and AI teams connect lineage, context, and ownership across the entire data ecosystem.
• Lovelytics shares real-world strategies for designing governance programs that enable organizations to achieve their AI goals, balance agility with compliance, embedding stewardship and operational excellence into day-to-day operations.
• Databricks shares the scalable Lakehouse platform and Unity Catalog lineage tools that make integrated governance technically and operationally feasible. 

Together, Anomalo, Atlan, Lovelytics, and Databricks will demonstrate how unified policies, continuous quality monitoring across all types of data, and end-to-end lineage can transform governance from a regulatory checkbox into a strategic enabler of AI innovation. You will leave with actionable advice to reduce risk, meet compliance requirements head on, and accelerate trustworthy AI adoption.

Speakers