The Shift from Data Governance to AI Accountability

Traditional data governance was built for documentation, reporting, and compliance. But AI systems change the stakes.

As data pipelines increasingly influence automated decisions, recommendations, and outcomes, policies stored in documents and dashboards designed for visibility are no longer enough. Accountability must move from static oversight to structural design.

This session explores the evolution from governance to accountability in modern AI systems. What changes when systems begin to act, not just inform? How do lineage, embedded assumptions, dependencies, and feedback loops shape real-world impact? And what does it mean to design systems that are defensible, not just observable?

Attendees will gain a systems-level framework for rethinking governance in the age of AI and practical guidance on embedding accountability into the foundation of the systems they build.