Canada is continuing its investment in world-leading artificial intelligence research, announcing the appointment and renewal of 42 Canada CIFAR AI Chairs, which includes 32 at the Alberta Machine Intelligence Institute.

Backed by a $24M investment, this announcement reinforces Canada's position as a global leader in AI by securing the world's top AI researchers to drive innovation and train the next generation of AI talent.

The announcement was made on stage by Evan Solomon, Minister of Artificial Intelligence and Digital Innovation, and Elissa Strome, Executive Director of the Pan-Canadian AI Strategy at CIFAR, during the third day of Upper Bound, Amii’s AI-focused conference that drew thousands of attendees from across the world. 

“These 42 new and renewed Chairs represent the absolute pinnacle of research excellence. Their work will ensure that the AI of tomorrow is developed and deployed right here in Canada, under our values of innovation and safety,” Solomon says.

The chair announcements come near the end of the second phase of the government’s Pan-Canadian AI Strategy. Established in 2017 as part of the world’s first national AI strategy, the Chairs program has earned a prestigious global reputation. Collectively, the Canada CIFAR AI Chairs are the third-highest impact AI research cluster in the world.

With this announcement, the Canada CIFAR AI Chairs program now supports 143 Chairs at universities nationwide, all affiliated with the country’s three national AI institutes: Amii, Mila, and the Vector Institute. 

​"Reaching the milestone of 140+ Canada CIFAR AI Chairs is a testament to the enduring success of the world’s first national AI strategy. Our focus has always been on people, because they represent the greatest value in any AI ecosystem. This diverse group of researchers is conducting high-impact work that is improving the lives of Canadians,”  Strome says. 

Thanks to the successful completion of its AI+X cluster hire, Amii is now home to 32 Canada CIFAR AI Chairs. Their groundbreaking work in machine learning includes topics such as reinforcement learning, explainable AI, AI use in medical imaging/disease prediction, and AI in space exploration.