The Pan-Canadian AI Strategy
Canada is a global AI leader
The Pan-Canadian Artificial Intelligence Strategy strengthens Canada’s leadership by fostering world-class research and top-tier talent in AI.
Launched in 2017 as the first national AI strategy in the world, it supports the recruitment and retention of top researchers and the training of emerging leaders to ensure long-term excellence and innovation in AI.
Our three National AI Institutes — Amii in Edmonton, Mila in Montreal, and the Vector Institute in Toronto — are the vibrant hubs that foster cutting-edge research and cultivate talent. Together, we forge national and international collaborations in the rapidly advancing field of AI.
These efforts are translating into real-world impacts for Canada such as the creation of new startups and jobs, catalyzing the commercialization of innovative products and services and supporting a vibrant Canadian economy.
AI News & Updates
AI and Society
CIFAR announces first AI safety Catalyst Grants under new national program
June 04, 2025
Canada CIFAR AI Chairs
From research to real-world impact
June 03, 2025
AI and Society
New program provides expert AI advice for policymakers
April 30, 2025
Canada CIFAR AI Chair - Responsible AI
Reihaneh Rabbany, Mila: Detecting misinformation online
January 31, 2025
AI and Society
Government of Canada announces Canadian AI Safety Institute
November 12, 2024
AI and Society
Nicolas Papernot and Catherine Régis appointed Co-Directors of the CAISI Research Program at CIFAR
December 12, 2024Recent Updates
AI Research and Training Programs
Canadian AI Safety Institute (CAISI) Research Program at CIFAR
The CAISI Research Program at CIFAR supports cutting-edge research to understand and mitigate risks from advanced AI systems, including malicious use and unintended harm. Led by ISED and administered by CIFAR, the program strengthens Canada’s AI safety expertise and positions Canada as a global leader in developing safe and trustworthy AI systems.
Canada CIFAR AI Chairs Program
Canada CIFAR AI Chairs are advancing cutting-edge research in areas like AI safety, drug discovery, machine learning for health, autonomous systems, materials discovery, human-AI interaction, and natural language processing.
Based at Amii (Edmonton), Mila (Montreal), and the Vector Institute (Toronto), more than 125 leading researchers are currently supported through the Pan-Canadian AI Strategy, which attracts global talent, supports long-term research, and trains the next generation of AI leaders.
Solution Networks
Working with national and international partners, CIFAR helps to establish Solution Networks – cross-sectoral teams of interdisciplinary experts who design, develop and implement responsible AI solutions that can address the complex challenges associated with emerging technologies.
AI Catalyst Grants
CIFAR AI Catalyst Grants are designed to catalyze new research areas and collaborations in machine learning and its application to different areas of science and society. Catalyst Grants offer flexible but targeted short-term funding intended to spur interdisciplinary collaborations that push research boundaries and/or address emerging themes within machine learning.
Next Generation AI Programs
Each year, CIFAR and its partners provide training opportunities to hundreds of Canadian and international students — from high school students to postdoctoral fellows — to help them develop the skills, expertise and networks they need to be successful in their future careers. These programs, such as the Deep Learning + Reinforcement Learning Summer School and AI4Good Summer Lab, are dedicated to engaging equity-deserving groups in AI, and supporting programs that advance AI approaches for positive societal benefits.
AI Insights for Policymakers
The AI Insights for Policymakers program provides a platform for policymakers and scientists to have timely and meaningful interactions to inform their thinking around AI and policy.
Pan-Canadian AI Compute Environment (PAICE)
The PAICE initiative is a collaborative effort to provide dedicated computing capacity for research teams who are applying AI methods to their research.
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