On 28 November 2025, the Treasury Board launched the government’s first publicly available AI Register, documenting over 400 instances of AI usage within the federal public service – from automated systems to policy content creation. Our research team at Evidence for Democracy carried out a broad review of the AI register, showcasing how AI is being actively deployed across 42 federal agencies, and what the next steps are for rebuilding public trust in Canada’s democracy.
It’s no surprise that public trust is facing record lows across the country. Statistics Canada reports that two-thirds of all Canadians have low trust in the federal government, and a recent OECD study found that the majority of Canadians have low to no trust in the civil service (46%) and political parties (66%) – with the lowest trust levels among historically marginalized demographic groups, including female, low-income, and younger (18-29 year old) Canadians. That growing distrust is actively being fuelled by feelings of alienation and perceptions of the government’s inability to act in the public interest. More than 3 in 5 Canadians say that the government does not effectively involve the public in federal decision-making, and three-quarters of all Canadians believe that the federal government would not refuse a corporation’s demand that could be harmful to the public.
The AI register has been framed as a solution to public trust issues and as a practical tool for showing how the federal government uses AI systems. Treasury Board President Shafqat Ali has claimed that the federal government is “committed to providing Canadians with information about how it is being used to support programs and services” – seemingly suggesting that the AI register was designed to increase public transparency.
However, this framing is not entirely accurate. Further on in the announcement, the government highlights the true inspiration for the AI register. “The Register will serve as an additional tool to support planning, reduce duplication, and to help departments identify opportunities to work more efficiently.” Rather than being originally created to increase transparency and public accountability, the AI register instead aims to encourage and accelerate AI adoption across other federal departments. This goal to maximize AI adoption expresses itself not only in what the AI register includes — but in how it communicates these insights publicly.
Our latest report, “AI and Democracy – Navigating Trust, Truth, and Technology in Policymaking,” is part of the What Does the Evidence Say? Series – a collection of reports diving into the evidence behind major government policies. In the report, we found three key insights on how AI is impacting federal decision-making.
1. AI Usage Varies Across Departments, But It’s Most Often Used for Public Services, Industry, and Security Purposes
Deployment of AI systems across the federal public service varies widely by department, from lowest usage rates (just 1 use for the Canadian Grain Commission) to highest (31 uses by the Canada School of Public Service).
When we looked at grouping agencies and departments by theme, we found that AI was most commonly used in three key areas: (1) governance and public services, (2) industry and innovation, and (3) immigration, borders, and security. Departments from these three key areas were often associated with the deployment of more concerning uses of AI systems, such as the use of AI facial recognition technologies to flag “high risk” travellers (eg CBSA’s “Fuzzy Search (SSAName3)” tool), and to make recommendations on immigration decisions (eg CBSA’s “Client Reporting and Engagement System (CRES)/ReportIn” tool).
2. AI is Actively Shaping Federal Policy Decisions
In terms of usage, the majority of AI systems in the federal government have been deployed for “Analysis” purposes, meaning cases in which AI technologies were employed to analyze and evaluate data without actively generating content (e.g. machine learning analytic tools and virtual assistants). Examples from the AI register include the Department of Fisheries and Oceans (DFO)’s “Oceanographic Anomaly Detection tool” and the Canadian Radio-television and Telecommunications Commission (CRTC)’s “CANchat generative AI chatbot”.
More concerningly, we found multiple cases where deployed AI technologies in the “Content Creation” category directly impact federal policy decisions. For example, the RCMP’s “Draft One AI software” transcribes audio material and drafts LLM-generated police reports of incidents to officers, while Global Affairs Canada’s “AI-generated briefing notes” tool creates AI-generated policy documents.
While not always directly influencing policymaking, the use of AI to generate content without rigorous review can lead to serious mistakes, AI slop, and outright falsehoods, as demonstrated in the Government of Newfoundland and Labrador’s education action plan, which was found to be riddled with fake sources and citation errors. Not only do these types of AI tools expose Canadian residents to potential privacy violations and racial biases, they actively shape federal policies and decision-making processes within security, border, immigration, and policing bodies.
3. Major Security and Privacy Concerns Given Heavy Reliance on American AI Technologies and Infrastructure
Lastly, we also found that approximately half the AI systems being used were developed by external vendors, ranging from small local companies (e.g., Knockri) to megascalers (e.g., Microsoft).
Diving deeper into these “external vendors”, we found that the vast majority (69.4%) are American, followed by Canadian (18.8%) and UK-based companies (4.4%). Out of all AI systems developed by “external vendors”, we found that 2 in 5 AI tools were created by just three American hyperscalers: Microsoft, Amazon, and Google.
This heavy reliance on American-owned, designed, and operated AI systems and infrastructure is understandable, but also presents potential threats to national security and data sovereignty, given that 1 in 3 AI systems used by the federal government use Canadians’ personal and private data.
Next Steps
Ultimately, efforts to improve transparency and accountability around AI usage in the federal government must be multifaceted. This means we need more inclusive public consultations that meaningfully engage communities, as well as better communication around technologies listed in the AI register, and continued sustained investment in digital media literacy for Canadians. Furthermore, international best practices, especially the EU Digital Services Act and EU Artificial Intelligence Act, provide valuable models for improving platform accountability, content regulation, and risk management, and for referencing when designing our own legislation and strategies. Our latest report outlines a variety of policy options, including clearer legislation on managing AI-generated content, a new centralized monitoring entity for AI usage, systemic data and privacy safeguards for vulnerable groups, and a renewed commitment to public trust and democratic resilience in the digital age.
At a time when Canada’s democracy is facing historic lows in public trust, coordinated misinformation campaigns, and major disruptions posed by new AI systems and technologies, we need to take action to safeguard our democracy and ensure that evidence-informed decision-making continues to build a better future for all Canadians.
