AI Regulatory Compliance & Risk Management

The Regulatory Environment Is Not Waiting

Canadian AI regulation is accelerating. AIDA is moving through Parliament. The Office of the Privacy Commissioner has signalled that AI uses of personal information are a priority for enforcement action. OSFI's expectations for AI in federally regulated financial institutions are becoming more explicit. The Treasury Board Secretariat continues to extend the reach of its Directive on Automated Decision-Making.

Organisations that assess and address their compliance position now will be better positioned than those that wait for enforcement action or mandatory compliance deadlines to initiate the work.

The Canadian Regulatory Landscape for AI

Artificial Intelligence and Data Act (AIDA). Canada's proposed federal AI legislation introduces a risk-based framework: high-impact AI systems will be subject to mandatory risk assessment, risk mitigation measures, monitoring, and incident reporting obligations. Penalties for non-compliance are substantial. We track AIDA's development and help clients understand their likely obligations.

PIPEDA and Provincial Privacy Legislation. The Personal Information Protection and Electronic Documents Act governs how federally regulated organisations collect, use, and disclose personal information — including information used in AI training datasets and AI inference. Quebec's Law 25 and British Columbia's PIPA impose equivalent and in some respects stricter requirements. We assess AI systems for compliance with applicable privacy legislation and identify where consent, purpose limitation, or data minimisation requirements are not met.

Directive on Automated Decision-Making. Federal institutions using AI in administrative decisions are subject to this Treasury Board directive, which requires impact assessment at four risk levels, human oversight mechanisms proportionate to risk, and notice to affected individuals. We conduct impact assessments under the directive's framework and design the oversight mechanisms the directive requires.

OSFI Expectations for Financial Institutions. The Office of the Superintendent of Financial Institutions has incorporated AI risk into its supervisory expectations for model risk management (E-23) and technology and cyber risk (B-13). We assess AI deployments in financial institutions against these expectations and produce the documentation that OSFI expects to see in supervisory reviews.

Provincial Health Privacy Legislation. PHIPA (Ontario), HIPA (Saskatchewan), HIA (Alberta), and equivalent legislation in other provinces impose specific obligations on health information custodians using AI to process personal health information. We assess AI deployments in healthcare organisations against applicable provincial legislation and identify compliance gaps.

What the Compliance Audit Covers

Regulatory Mapping. Identifying every applicable regulation, directive, and guideline — federal, provincial, and sector-specific — that applies to your AI systems. This mapping forms the foundation of the compliance assessment.

Gap Analysis. Assessing each AI system against applicable requirements and identifying gaps: missing documentation, absent controls, inadequate consent mechanisms, insufficient human oversight, or undisclosed use of personal information.

Risk Prioritisation. Not all compliance gaps carry equal risk. We assess each gap by the likelihood of regulatory attention, the potential consequences of a finding, and the effort required for remediation — and produce a prioritised remediation plan accordingly.

Remediation Design. Designing the specific changes — technical controls, documentation, process changes, governance structures, contractual amendments — required to close identified gaps. Remediation plans are specific, not generic: we specify what needs to change, who needs to change it, and by when.

Ongoing Compliance Monitoring. Regulatory requirements change. AI systems change. We establish ongoing monitoring arrangements — typically under an Evolve phase engagement — that ensure compliance is maintained as both the regulatory environment and your AI deployments evolve.

Working with Regulators

When organisations need to engage proactively with regulators — the Office of the Privacy Commissioner, OSFI, a provincial regulator, or a law society — we support that engagement with documentation, compliance assessments, and remediation evidence that demonstrates the organisation's good faith and progress. We have experience preparing the kind of materials that regulators find credible.

Delivery Process

Step 1: Regulatory Mapping and AI System Inventory (Weeks 1–2). We identify every applicable regulation, directive, and guideline relevant to your organisation's AI deployments — federal, provincial, and sector-specific. Concurrently, we inventory your deployed AI systems, the personal information they process, the decisions they influence, and the third-party vendors involved. This mapping establishes the full scope of the compliance assessment before detailed review begins.

Step 2: Gap Analysis by System (Weeks 2–4). We assess each AI system against applicable requirements and document every gap: missing documentation, absent controls, inadequate consent mechanisms, insufficient human oversight mechanisms, undisclosed processing of personal information, or non-compliant vendor contracts. Gaps are classified by severity — those that require immediate remediation, those that require planned remediation within 90 days, and those that represent acceptable risk with enhanced monitoring.

Step 3: Risk Prioritisation and Remediation Design (Weeks 4–5). We assess each gap by the likelihood of regulatory attention, the potential consequences of a finding, and the effort required for remediation. We produce a prioritised remediation plan with specific actions, owners, timelines, and success criteria. For organisations facing imminent regulatory scrutiny, we identify the actions with the highest risk-reduction value per unit of effort.

Step 4: Remediation Support and Evidence Documentation (Weeks 5–12, depending on remediation scope). We support execution of the remediation plan — designing specific technical controls, drafting governance documentation, developing contractual amendments for vendor agreements, and building the evidence package that demonstrates compliance. We produce the documentation that regulators expect to see: not just policy statements, but evidence of controls in operation.

Typical Engagement

Duration: 4–6 weeks for a focused compliance audit of a specific AI system or regulatory requirement. Comprehensive assessments covering multiple AI systems and regulatory frameworks typically run 8–12 weeks plus remediation support.

What the client needs to provide: Inventory of deployed AI systems and vendors; access to IT, legal, compliance, and privacy officer stakeholders; AI vendor contracts and data processing agreements for review; access to the AI systems and their associated data flows for technical assessment.

What Remolda provides: Full regulatory mapping, AI system inventory facilitation, gap analysis, risk assessment, remediation plan, remediation support, and evidence documentation. For organisations engaging with regulators, we provide preparation support including review of regulator correspondence and preparation of response materials.

Technology & Integrations

Compliance assessment involves evaluating the technical controls in your AI platforms, not just the governance documentation around them. We assess the data residency configuration of cloud AI services — Azure OpenAI, Google Cloud Vertex AI, Amazon Bedrock, and others — against the data residency requirements of applicable Canadian legislation, identifying mismatches between contractual commitments and actual data flows. We review the access control architecture of AI systems, the encryption standards applied to AI model inputs and outputs, the logging and audit trail capabilities of AI platforms relative to regulatory audit requirements, and the data retention and deletion capabilities relevant to individual rights requests. For automated decision-making systems subject to the Directive on Automated Decision-Making, we assess the technical implementation of human oversight mechanisms and verify that decision logic is sufficiently documented for transparency requirements. We also review API integrations and data sharing arrangements with AI vendors to identify contractual gaps in data processing agreements, subprocessor disclosure, and breach notification obligations.

Canadian Regulatory Context

Canada's regulatory environment for AI is among the most active in the world. AIDA (Part 3 of Bill C-27) is advancing through Parliament and will impose mandatory requirements on organisations deploying high-impact AI systems: mandatory impact assessments, risk mitigation measures, human oversight requirements, incident reporting obligations, and record-keeping requirements subject to ministerial review. Penalties for the most serious violations are set at the greater of $25 million or 3% of global gross revenues. Quebec's Law 25, already in force since September 2023, has added new obligations including mandatory privacy impact assessments before deploying technology with profiling capabilities, mandatory transparency obligations for automated decision-making, and new individual rights to challenge automated decisions — obligations that apply to many AI systems currently in production across Canadian organisations. The Office of the Privacy Commissioner issued guidance in 2024 clarifying that the use of personal information to train AI models without appropriate consent basis constitutes a potential violation of PIPEDA. Organisations with AI systems deployed before this guidance should assess whether their consent and purpose documentation remains adequate.

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Further reading: AI Privacy Compliance in Canada | AI Governance Enterprise Framework