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Canada
GuidanceVoluntary / non-binding· Canadian Forum for Digital Infrastructure Resilience (CFDIR), AI/ML Working Group

Operationalizing the Gen-AI Voluntary Code of Conduct for Canadian Critical Infrastructure Entities

Prepared by Shubhank Suman · Last reviewed

CURRENT / VOLUNTARY / NON-BINDING

Legal character
AI risk-management implementation guidance
Region
North America
Published
25 September 2024

What it covers

This document operationalises Canada's voluntary approach to generative-AI governance for critical infrastructure. It recognises that AI may enter infrastructure intentionally or through existing IT and operational-technology products, where failure may affect public safety, essential services, communications, transportation, energy, financial systems, digital infrastructure and national resilience. It uses the NIST-style GOVERN, MAP, MEASURE and MANAGE structure and is broad and non-prescriptive rather than a mandatory checklist.

Why it matters

It connects AI governance with the heightened safety, security and resilience consequences of critical-infrastructure environments.

Refer to it when

Use it for critical-infrastructure AI governance, organisational accountability, use-case and dependency mapping, risk measurement, continuous mitigation, incident response, operational technology, supply-chain controls and resilience.

AI, privacy and cybersecurity relevance

  • AI: Very High
  • Privacy: High
  • Cyber: Very High

AI

VERY HIGH RELEVANCE

The document expressly operationalises AI governance through GOVERN, MAP, MEASURE and MANAGE for critical-infrastructure organisations.

Privacy

MODERATE / HIGH INDIRECT RELEVANCE

The document is not a privacy statute. Applicable Canadian federal and provincial privacy laws still govern. Its data-governance analysis is relevant to employee, customer, operational, communications, security, location, access-control and sensitive infrastructure information.

Cybersecurity

VERY HIGH RELEVANCE

It covers IT, operational technology, cloud services, AI supply chains, third-party vendors, availability, integrity, monitoring and resilience, bridging the NIST AI RMF with critical-infrastructure AI safety.

Applicability

Canadian critical-infrastructure owners, operators and related stakeholders, including suppliers of AI-enabled products or services into critical-infrastructure environments.

Current validity

CURRENT VOLUNTARY GUIDANCE.

Read first

Introduction & Purpose → AI Risk Governance Framework → GOVERN → MAP → MEASURE → MANAGE → AI Incident/Risk Controls → Critical-Infrastructure Application.

Provisions / sections covered

GOVERN

Establish policies, procedures, roles, responsibilities, risk ownership, organisational values and culture, aligned with law and sector-specific regulation.

MAP

Understand the use case, stakeholders, legal and sector obligations, operational dependencies, potential harms, data flows and third-party dependencies.

MEASURE

Use quantitative, qualitative or mixed methods to analyse risks, benchmark performance, monitor impacts and evaluate effects on operations and organisational data.

MANAGE

Continuously monitor change, mitigate risk, respond to incidents, review controls, escalate material issues and modify or suspend unsafe uses.

Subject-matter tags

  • Employment data
  • Surveillance
  • AI governance
  • AI safety
  • Generative AI
  • Transparency
  • Risk management
  • AI cybersecurity
  • Accountability

Subject-matter tags describe what the indexed text discusses. They are not legal conclusions.

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