Data Subject Rights at Scale: Can AI Fix What Governance Broke?

Companies and institutions are struggling to meet data subject right obligations at scale. DSARs, deletion requests and retention requirements are increasingly complex, fragmented and operationally burdensome, particularly across large, data-rich environments. At the same time, AI is being positioned as the solution, automating discovery, classification, redaction and response. But does AI solve the problem, or simply expose deeper issues in data governance, ownership and control? This session brings together real-world practitioner experience from financial services, telecoms and global data environments to explore how companies are implementing data subject rights and retention obligations. It examines where AI is genuinely helping versus where it introduces new risks. The focus is practical: what works, what does not and how to design governance models that can operate at scale.

What you will learn: 

• How companies are using AI to automate discovery, redaction and response workflows.
• Where AI introduces new risks: accuracy, explainability, over-deletion and under-disclosure.
• Practical steps for retention policies, data ownership and operational delivery.