Organizations across sectors face mounting pressure to integrate artificial intelligence capabilities while maintaining security posture and regulatory compliance. Government entities must balance rapid innovation demands with strict data governance requirements, particularly when handling sensitive citizen information and public sector operations. Traditional cybersecurity frameworks require adaptation to address unique AI-specific risks including model transparency, data sovereignty, training data provenance and algorithmic bias.

This session, led by Michael Schwab, director of application and product security for the Government of Alberta, will cover:

• Information controller accountability and data governance throughout AI implementation phases;
• Human-in-the-loop requirements to prevent autonomous decision-making vulnerabilities;
• The importance of executive support and dedicated cybersecurity resources for enterprise AI programs.