Navigating Canada’s AI Regulatory Landscape in 2025
Introduction
The past few years have seen a surge of artificial intelligence (AI) applications across the globe. In Canada, AI adoption is growing, yet regulatory frameworks remain a work in progress. For any organization exploring AI — from enterprises to start‑ups and government agencies — understanding the evolving legal landscape is critical. This article provides a clear snapshot of where Canada’s AI regulation stands in late 2025 and offers guidance on preparing for the rules ahead.
Why regulation matters
AI can deliver transformative benefits. From diagnosing diseases to optimizing supply chains and analysing vast datasets, the technology opens new avenues for productivity and innovation. However, powerful AI models also carry risks. They can embed and amplify biases, threaten privacy, and concentrate power among a few developers. Governments worldwide are therefore developing regulatory frameworks to promote safe, fair and transparent AI deployment.
Canadian businesses have been watching the European Union’s AI Act and the United States’ evolving rules and wondering how domestic legislation will unfold. At the moment, the answer is: it’s complicated.
No national AI law yet — but it’s coming
As of May 2025, Canada has no approved federal AI regulation framework. The government has been working on the Artificial Intelligence and Data Act (AIDA) since 2022, but the bill is still making its way through Parliament xenoss.io. The April 2025 federal election temporarily delayed the bill, but it is expected to return to the legislative agenda now that the governing party remains in power xenoss.io.
What AIDA proposes
AIDA would be Canada’s first law specifically focused on regulating AI. It is designed to minimize risks from high‑impact AI applications xenoss.io. The draft bill identifies seven high‑impact categories — healthcare, biometric identification, employment, essential services (such as banking and insurance), education, law enforcement and online content recommendation systems xenoss.io. Systems operating in these areas would need to:
Mitigate risks related to bias, discrimination and public harm xenoss.io.
Provide transparent disclosure about how the AI system is used and the risks it poses xenoss.io.
Maintain records describing training data, intended purpose and risk management methods xenoss.io.
Report incidents such as serious malfunctions or data breaches to regulators xenoss.io.
Cooperate with audits and provide documentation when requested xenoss.io.
Non‑compliance could lead to fines of up to C$25 million or 5 % of global revenue xenoss.io.
AIDA has been criticized for vagueness and insufficient protection of labor and creative sectors xenoss.io. The bill’s definition of “high‑impact” is flexible and could expand once enacted xenoss.io. Nonetheless, businesses should treat AIDA as a bellwether. Investing in explainable and well‑documented AI processes now will put companies ahead of future obligations.
Existing laws still apply
Even without AIDA, AI systems in Canada must comply with existing legislation. The Personal Information Protection and Electronic Documents Act (PIPEDA) governs how organizations collect, use and disclose personal data. For AI platforms, PIPEDA requires:
Obtaining meaningful consent from individuals before collecting or using their data xenoss.io.
Being transparent about how personal information is used and the logic of automated decisions xenoss.io.
Allowing individuals to access and correct personal data used in AI models xenoss.io.
Adhering to fairness, accuracy and accountability principles xenoss.io.
Violations can result in fines up to C$100,000 xenoss.io. Businesses developing AI solutions should embed privacy‑by‑design principles and maintain data audit trails to demonstrate compliance.
Voluntary codes and guidelines
Recognizing that lawmaking takes time, the federal government has issued guidance documents to encourage responsible AI use. The Voluntary Code of Conduct on the Responsible Development and Management of Advanced Generative AI Systems was released in September 2023 xenoss.io. While not legally binding, adherence to the code signals to regulators that a company is committed to ethical AI development. Key points include evaluating models for bias, establishing robust security controls and transparently communicating generative AI’s capabilities and limitations.
For government agencies and vendors, the Directive on Automated Decision‑Making requires an Algorithmic Impact Assessment for any system that supports or replaces human decision‑making. It grades systems on their potential impact and mandates stronger oversight for higher‑risk applications.
How businesses can prepare
Given the mix of upcoming legislation and existing rules, Canadian companies should adopt proactive compliance strategies:
Map your AI use cases. Identify which of your systems may fall into AIDA’s high‑impact categories. Document where and how AI supports decision‑making.
Implement privacy‑by‑design. Collect only the data you need, obtain informed consent, anonymize personal information and implement robust security controls.
Ensure explainability. Maintain documentation on model training, data sources, decision logic and risk management. Use this information to train staff and respond to regulator requests.
Conduct bias testing. Regularly audit AI outputs for unfair patterns. Engage diverse stakeholders to evaluate systems from multiple perspectives.
Establish governance. Create cross‑functional teams (legal, compliance, data science) to oversee AI initiatives and prepare for possible audits.
Monitor regulatory updates. The AIDA bill could evolve before passage. Tracking amendments and participating in consultations will help shape compliance plans.
The role of service providers
Organizations like Greenaty Inc. can support businesses in navigating this complex landscape. By offering AI auditing, workflow automation, LLM fine‑tuning and consulting services, providers ensure clients meet regulatory requirements while unlocking AI’s benefits. Expert partners can help assess current AI systems, implement monitoring dashboards, and train staff on responsible AI practices.
Conclusion
Canada’s AI regulatory landscape is in flux. While the proposed AIDA bill would bring AI‑specific legislation, businesses are already subject to privacy laws and voluntary codes. The smartest course of action is to build responsible, transparent and bias‑mitigated AI processes now. Companies that embrace governance early will be better positioned to innovate safely and build trust with customers and regulators alike.