By Maple & North
The debate around artificial intelligence often focuses on capability, regulation, and data sovereignty. Those are important conversations. But there is another question that receives far less attention:
What happens when access to a critical AI capability disappears?
For many organizations, AI has already moved beyond experimentation. Models are being integrated into security operations, software development, customer service, risk analysis, fraud detection, and business decision-making. In some environments, AI is beginning to influence actions rather than simply provide recommendations.
That shift introduces a new category of dependency.
The risk is not that Canadian organizations use AI. The risk is that critical workflows become dependent on tools, models, platforms, or autonomous agents whose availability and authority sit outside the organization.
Canada does not need to build every AI capability itself. But organizations should understand what happens when a critical AI service becomes unavailable due to provider decisions, regulatory restrictions, geopolitical events, commercial disputes, outages, or policy changes.
That question matters now because AI is steadily moving from advice into action.
The Continuity Question
Most organizations already understand the importance of business continuity planning.
Executives ask what happens if a cloud region fails, an identity provider experiences an outage, or a telecommunications provider becomes unavailable. Disaster recovery exercises, backup systems, and alternate suppliers exist because leaders recognize that dependencies create risk.
AI deserves the same treatment.
Many organizations are rapidly integrating AI into operational processes without fully understanding the consequences of losing access to those capabilities.
Recent events involving restrictions on advanced AI systems demonstrated that access to a capability can be affected by decisions made outside an organization, outside a province, and in some cases outside Canada entirely. Regardless of the specific vendor involved, the lesson is broader than any individual platform.
If a critical capability can be altered, restricted, or withdrawn by an external party, then continuity planning becomes essential.
AI Is Becoming Operational Infrastructure
The conversation changes when AI moves beyond productivity assistance.
Consider a security operations centre that uses AI to:
- Triage alerts.
- Prioritize vulnerabilities.
- Analyze malicious activity.
- Generate detection logic.
- Recommend response actions.
Now consider the same environment one year from now, where AI agents may be authorized to:
- Open and close tickets.
- Modify security controls.
- Approve access requests.
- Execute remediation actions.
- Interact directly with cloud infrastructure.
At that point, AI is no longer simply a tool. It becomes operational infrastructure.
The question is no longer whether the model is accurate.
The question becomes whether the organization can continue operating if that capability suddenly becomes unavailable.
Why This Matters in Canada
Canada's economy depends heavily on sectors where trust, continuity, and resilience are fundamental requirements.
Financial institutions, healthcare organizations, critical infrastructure operators, telecommunications providers, and government agencies increasingly rely on advanced digital services supplied by global technology providers.
This is not inherently a problem. Global platforms provide enormous value, innovation, and scale.
However, dependency becomes a concern when organizations fail to understand where critical capabilities originate and who ultimately controls them.
The discussion often focuses on where data resides. Data residency remains important, particularly in regulated industries, but data location alone does not guarantee operational independence.
An organization may store data entirely within Canada while still depending on AI models, platforms, services, or decision-making systems that are governed elsewhere.
The result is a gap between perceived control and actual control.
The Cybersecurity Dimension
Cybersecurity leaders should pay particular attention to AI dependency because many of the earliest enterprise deployments are occurring within security programs.
Threat detection, vulnerability management, security analytics, incident response, and identity operations are all becoming candidates for AI augmentation.
The Canadian Security Intelligence Service (CSIS) has repeatedly highlighted the importance of protecting critical infrastructure from evolving cyber threats. Likewise, the Canadian Centre for Cyber Security continues to emphasize resilience, preparedness, and operational continuity as foundational principles of modern cybersecurity.
Those principles apply equally to AI-enabled environments.
The question is not whether a particular model is foreign or domestic.
The question is whether security teams understand their dependencies well enough to maintain operations when conditions change.
Sovereign Compute Helps—but Does Not Solve the Problem
Canada has already begun investing in domestic AI capabilities.
The Government of Canada's AI Sovereign Compute Infrastructure Program seeks to expand access to advanced computing resources while strengthening Canada's long-term AI ecosystem. Initiatives such as the Pan-Canadian Artificial Intelligence Strategy have also helped establish Canada as a significant contributor to global AI research.
These efforts are important.
However, sovereign compute should not be viewed as a complete solution to the dependency problem.
Even organizations with access to domestic infrastructure may continue relying on external models, proprietary services, cloud providers, datasets, APIs, or autonomous agents.
Resilience comes not from ownership alone, but from understanding dependencies and planning for disruption.
Five Questions Every Executive Should Ask
As AI becomes embedded in business operations, leadership teams should be asking five straightforward questions:
- Which critical business processes depend on AI today?
- Which providers, models, or platforms support those processes?
- What happens if access disappears tomorrow?
- Do we have a tested alternative?
- Who owns the risk?
Organizations routinely ask these questions for cloud services, payment systems, telecommunications providers, and identity platforms.
AI should be no different.
What Leaders Should Do Now
Security and technology leaders should begin treating AI systems and autonomous agents as governed operational assets rather than informal productivity tools.
Practical steps include:
- Inventory critical AI dependencies.
- Assign accountable owners for AI-enabled workflows.
- Document access controls, approval boundaries, and logging requirements.
- Assess jurisdictional and continuity risks during procurement.
- Develop fallback procedures and alternate operating models.
- Test continuity plans through tabletop exercises and simulations.
The objective is not to eliminate dependency.
The objective is to understand it.
Conclusion
The debate is often framed as sovereignty versus globalization.
That is the wrong question.
The real question is continuity.
Every organization depends on capabilities it does not fully control. Artificial intelligence simply introduces a new category of dependency—one that is increasingly involved in decisions, actions, and authority.
Canada does not need to build every model, platform, or service itself. But organizations do need to understand where critical AI dependencies exist, who ultimately controls them, and what happens when access changes without warning.
Resilience is not measured when everything is available.
It is measured on the day it is not.
References
- Government of Canada. AI Sovereign Compute Infrastructure Program.
- Government of Canada. Directive on Automated Decision-Making.
- Pan-Canadian Artificial Intelligence Strategy (CIFAR).
- Canadian Security Intelligence Service (CSIS). National Security and Critical Infrastructure Publications.
- Canadian Centre for Cyber Security. Guidance on Operational Resilience and Critical Infrastructure Protection.
- National Research Council Canada. Research and publications related to AI, cybersecurity, and critical infrastructure resilience.