AI governance is important to ensuring public trust in these technologies and their ethical, safe deployment. This report offers a comparative study of AI governance in Canada and the United States as of 2026. In conducting our assessment of AI governance across both countries, we assessed six core dimensions: (1) Institutional Readiness and Capacity, (2) Governance, Law and Oversight, (3) Transparency and Public Record, (4) Public Trust, Democratic Resilience, Rights, and Social Impact, (5) Technical Robustness and Data Governance, and (6) Public Value. Each dimension was scored using our scoring rubric (Appendix B), and letter grades were assigned using a standardized scale (Appendix A).

Our findings reveal the strengths and weaknesses of both nations’ approaches to AI governance, with Canada possessing many institutional foundations for responsible AI alongside major implementation gaps. By contrast, the United States shows how quickly AI governance can shift when policies become politicized. Frequent policy changes create uncertainty around safety standards, oversight, and governance, leading to innovation pitfalls and implementation gaps, and, in some cases, long-term harms for citizens.

As our results show, Canada and the U.S. have each taken different approaches to AI governance but share similar policy gaps in safety, privacy, and enforcement, and face similar struggles in implementing transparency and accountability measures. While both nations appear to have the institutional capacity to develop and deploy AI systems, the U.S., in particular, still has major leadership and regulatory gaps that limit its ability to do so while addressing AI-caused harms to its citizens.

Effective AI governance is not just about rules; it is about the public good. If done poorly, it erodes trust and causes real harm to citizens. This report offers an evidence-based framework for understanding those patterns and strengthening government decision-making that ultimately benefits the public interest.