Traditional approaches to validating data controls are often manual, time-consuming and difficult to scale, creating gaps in assurance and increasing operational risk. As data environments grow more complex, organisations are rethinking how controls are tested and monitored across the enterprise.

This session will explore how AI and automation are being applied to transform control validation. 

• How to move from periodic, evidence-based testing to continuous, code-level assurance
• What are the benefits for reliability, risk reduction and efficiency
• How to implement this approach across complex data environments while maintaining strong governance and oversight