Description

Organizations are increasingly dependent on artificial intelligence to deliver services, manage infrastructure, and support critical decisions. Yet many of these systems are built, hosted, or governed outside Canada, raising an important leadership question: how much real control do we have over the technologies we rely on?

This course introduces a structured approach to evaluating AI systems so that assumptions about control can be replaced with a clear, practical assessment. It reframes “sovereignty” not as an abstract concept, but as a system property that can be examined across concrete dimensions such as data, infrastructure, governance, jurisdiction, and ownership.

Designed for leaders in government, Crown corporations, and regulated industries, the course focuses on decisions organizations are actively making—such as selecting vendors, designing system architectures, managing operational risk, and ensuring accountability in the use of AI.

Through guided discussion, real-world case studies, and a hands-on sovereignty mapping exercise, participants apply a seven-part framework to assess AI systems step by step. The framework provides a practical method for evaluating sovereighty across AI systems, technology platforms, vendor relationships, and digital infrastructure initiatives, enabling a clearer understanding of where control is concentrated, where dependencies exist, and how those dependencies influence decision-making and oversight.

By the end of the course, participants will be equipped with a structured method for evaluating AI systems in their own context, along with practical criteria for assessing technology choices, vendor relationships, and governance implications in environments increasingly shaped by artificial intelligence.

Learning Outcomes

At the end of this course, participants will be able to:
  • Define Sovereign AI and explain its strategic relevance in a Canadian context
  • Identify where AI dependency on external platforms, models, or jurisdictions exists within organizational systems
  • Assess AI systems using a structured seven-part sovereignty framework across data, computing, governance, and jurisdiction
  • Interpret emerging AI governance frameworks within Canadian regulatory and operational environments
  • Evaluate procurement, architecture, and partnership decisions for sovereignty alignment and long-term control
  • Formulate leadership-level actions to strengthen organizational autonomy, accountability, and resilience

Duration

6 hours

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Instructor

Roy Chartier is CTO and co-founder of Qvelo, an engineering firm specializing in sovereign HPC and AI infrastructure, and interim Executive Director of Computing for Humanity, a Canadian charity operating research cloud infrastructure. He previously served as Director of Architecture at the Digital Research Alliance of Canada and as Vice Chair with the U.S. National Science Foundation's ACCESS program. Roy is a volunteer standards committee member with the Digital Governance Standards Institute, contributing to a digital sovereignty data governance framework and the PAS 142 healthcare data governance panel, and is an active voice in Canadian digital sovereignty and AI policy.