Canada AI Governance

Artificial Intelligence and Data Act (AIDA)

The Artificial Intelligence and Data Act forms part of Bill C-27, the Digital Charter Implementation Act, introduced in the Canadian Parliament to establish a comprehensive framework for regulating artificial intelligence systems. AIDA represents Canada's approach to balancing innovation with protection of individual rights and societal interests in the deployment of AI technologies.

The Act establishes obligations for persons engaged in international or interprovincial trade and commerce who design, develop, or make available for use AI systems. AIDA applies extraterritorially to organizations outside Canada whose AI systems are used in Canada or produce outputs used in Canada. This broad jurisdictional reach ensures that AI systems affecting Canadian residents remain subject to regulatory oversight regardless of where system operators are located.

AIDA distinguishes between general AI systems and high-impact AI systems, imposing enhanced obligations on systems capable of causing serious harm to individuals or their interests. The risk-based approach recognizes that not all AI systems present equivalent risks and that regulatory requirements should be proportionate to potential harms. Organizations must assess whether their AI systems meet criteria for high-impact designation and implement appropriate compliance measures.

High-Impact AI Systems

High-impact AI systems are those that may reasonably be expected to cause or contribute to serious harm to individuals or their interests. The Act defines harm broadly to include physical harm, psychological harm, damage to property, economic loss, and damage to reputation. Determining whether a system constitutes high-impact AI requires analysis of the system's capabilities, intended use, context of deployment, and potential consequences of errors or misuse.

Regulations to be developed under AIDA will specify criteria and thresholds for high-impact designation. Organizations should anticipate that AI systems used in sensitive domains such as healthcare, employment, financial services, law enforcement, and critical infrastructure are likely to be designated high-impact. Systems that make or materially influence decisions affecting individual rights, entitlements, or opportunities will warrant careful assessment for high-impact status.

Persons responsible for high-impact AI systems must establish measures to identify, assess, and mitigate risks of harm or biased output throughout the AI system lifecycle. Risk management measures must be documented and updated as understanding of risks evolves or as system characteristics change. Organizations should implement governance frameworks that enable systematic risk identification, evaluation of mitigation options, and monitoring of control effectiveness.

High-impact systems must be designed and developed in accordance with requirements prescribed by regulation. These requirements are expected to address data quality, model validation, testing procedures, documentation standards, and ongoing monitoring. Organizations should monitor regulatory developments closely and prepare to implement technical and procedural controls necessary for compliance.

Impact Assessments

AIDA requires persons responsible for high-impact AI systems to conduct impact assessments before making systems available for use. Impact assessments evaluate the nature and severity of potential harms, assess measures to mitigate identified risks, and document the rationale for proceeding with system deployment. Assessments provide structured frameworks for considering potential consequences and ensuring that risk mitigation measures are appropriate.

Impact assessments must consider potential biased output that could adversely affect individuals or communities. This requires analysis of training data for representativeness and balance, evaluation of model performance across relevant demographic groups, and assessment of whether system design incorporates appropriate bias mitigation techniques. Organizations should document data sources, data quality controls, validation methodologies, and performance metrics disaggregated by relevant characteristics.

Assessment documentation must be maintained and made available to the Minister upon request. Organizations should establish document retention policies that preserve impact assessment records throughout system lifecycles. Documentation should be sufficiently detailed to enable independent review and should clearly demonstrate that required assessments were conducted rigorously and in good faith.

Impact assessments should be updated when material changes occur to AI systems or operating contexts. Material changes include modifications to system design, expansion to new use cases, deployment in different populations, or identification of previously unrecognized risks. Organizations should establish change management procedures that trigger reassessment when appropriate.

Algorithmic Transparency

AIDA establishes transparency obligations requiring persons making AI systems available for use to publish plain language descriptions of the systems. Descriptions must explain how systems are intended to be used, the types of decisions or recommendations they generate, and the data they process. Transparency enables affected individuals to understand when and how AI systems may influence decisions affecting them.

For high-impact AI systems, enhanced transparency requirements mandate publication of anonymized results of impact assessments. This provision enables public scrutiny of risk assessments and mitigation measures for systems capable of serious harm. Organizations must balance transparency obligations with protection of confidential business information and trade secrets. Regulations will provide guidance on appropriate levels of detail and mechanisms for protecting sensitive information while meeting transparency requirements.

Organizations should develop plain language materials that communicate AI system characteristics and risks to diverse audiences. Technical jargon should be minimized, and explanations should be accessible to individuals without specialized expertise. Organizations may need to prepare multiple versions of transparency materials tailored to different stakeholder groups, including affected individuals, regulators, and technical evaluators.

Personal Information Protection

AI systems processing personal information must comply with applicable privacy laws, including the Personal Information Protection and Electronic Documents Act and provincial privacy legislation. Organizations must establish lawful bases for collecting, using, and disclosing personal information in AI contexts. Consent requirements apply where personal information is collected, used, or disclosed in ways that individuals would not reasonably expect.

Bill C-27 includes the Consumer Privacy Protection Act, which will replace PIPEDA and establish enhanced requirements for automated decision-making. The CPPA grants individuals rights to be informed of automated decision-making, to obtain explanations of decisions, and to challenge decisions made solely by automated means. Organizations deploying AI systems must design processes that enable exercise of these rights.

Privacy impact assessments for AI systems should evaluate how personal information flows through AI lifecycles, from initial collection through model training, validation, deployment, and monitoring. Assessments should identify privacy risks arising from AI-specific factors such as inferences drawn from data, potential for re-identification of anonymized data, and secondary uses of personal information. Organizations should implement privacy by design principles that embed privacy protections into AI system architectures.

Minister's Powers

AIDA grants the Minister responsible for the Act broad powers to administer and enforce its requirements. The Minister may require persons to provide information or records relevant to verifying compliance. Organizations must respond to ministerial requests within specified timeframes and provide complete and accurate information. Failure to cooperate with investigations or provision of false or misleading information constitutes separate offenses under the Act.

The Minister may order audits or assessments of AI systems to verify compliance with the Act or regulations. Audits may be conducted by ministerial personnel or by qualified third parties appointed by the Minister. Organizations subject to audits must provide access to systems, documentation, and personnel necessary for audit completion. Audit findings may result in orders requiring corrective action, modification of AI systems, or cessation of system operation.

Where the Minister believes on reasonable grounds that an AI system presents serious risk of harm or that a person has contravened the Act, the Minister may issue compliance orders. Compliance orders specify required actions and timeframes for compliance. Organizations subject to compliance orders should promptly assess feasibility of compliance, engage with the Minister regarding any concerns, and implement corrective measures expeditiously.

Penalties and Enforcement

AIDA establishes significant penalties for violations. The most serious offenses, involving reckless or intentional contraventions causing serious harm, may result in fines up to five percent of gross global revenue or twenty-five million dollars, whichever is greater. Imprisonment up to two years may be imposed for particularly egregious violations. These penalty levels reflect the seriousness with which Parliament views AI-related risks and underscore the importance of compliance.

Administrative monetary penalties may be imposed for contraventions that do not rise to the level of criminal offenses. Penalty amounts will be prescribed by regulation and will vary based on severity of violations and circumstances of contraventions. Factors considered in determining penalties include degree of intent or negligence, extent of harm caused or risked, history of compliance, and efforts to mitigate harm.

Organizations should establish robust compliance programs to prevent violations and demonstrate good faith efforts to comply with AIDA. Documented compliance programs, regular assessments, training initiatives, and prompt remediation of identified issues may influence enforcement discretion and penalty determinations. Organizations that discover potential violations should consider voluntary disclosure and cooperation with authorities.

Compliance Requirements

Organizations subject to AIDA should implement comprehensive compliance programs addressing the following elements:

• •AI system inventories identifying all systems within AIDA scope and classifying them according to impact level. Inventories enable targeted application of compliance requirements based on system risk profiles.
• •Governance frameworks establishing accountability for AIDA compliance, including designated responsible persons, oversight committees, and escalation procedures. Governance should integrate with existing risk management and compliance functions.
• •Risk management processes for identifying, assessing, and mitigating risks of harm and biased output. Processes should be documented, validated, and updated as understanding of risks evolves.
• •Impact assessment procedures ensuring that high-impact AI systems undergo required assessments before deployment. Procedures should specify assessment methodologies, approval authorities, and documentation requirements.
• •Transparency mechanisms for publishing required information about AI systems and making impact assessment results available. Organizations should establish processes for preparing, reviewing, and disseminating transparency materials.
• •Documentation systems maintaining records required by AIDA, including system descriptions, risk assessments, impact assessments, validation results, and monitoring data. Document retention policies should ensure availability throughout system lifecycles and regulatory retention periods.
• •Training programs ensuring personnel understand AIDA requirements and their responsibilities. Training should address technical staff, business users, compliance personnel, and senior management.
• •Incident response procedures for addressing potential harms, biased outputs, or compliance issues. Procedures should include investigation, remediation, notification, and reporting obligations.
• •Monitoring and audit functions verifying ongoing compliance with AIDA requirements. Internal audits should be conducted regularly and findings should inform continuous improvement of compliance programs.

Organizations should begin compliance preparation even as regulations are developed. Early implementation of governance structures, risk management processes, and documentation systems positions organizations to respond efficiently when detailed regulatory requirements are finalized. Proactive compliance demonstrates organizational commitment to responsible AI and may influence regulatory engagement opportunities.