AI System Audits and Assurance

As AI systems become deeply embedded in business operations, assurance mechanisms are essential to maintain trust, compliance and accountability. This session explores how companies and institutions can design and implement effective audit programs for AI—covering model validation, data governance, risk assessment and documentation standards. Drawing on lessons from both privacy and regulatory audit disciplines, we will discuss emerging global frameworks and practical approaches for ensuring transparency and reliability in generative and predictive AI systems. Attendees will gain insight into how to integrate AI audits into existing governance structures, demonstrate compliance with the EU AI Act, and build cross-functional collaboration between legal, technical and ethics teams.

What you will learn:

• How to design and implement an AI audit framework that ensures transparency, accountability and compliance. 
• Practical methods for assessing and documenting AI system risks, controls and performance. 
• How to align AI assurance practices with global regulatory expectations, including the EU AI Act.

Additional registration fee required.