AI Adoption and Its Barriers

Understanding Barriers to AI Adoption in Canada

Artificial intelligence (AI) is transforming industries worldwide, yet Canada faces significant barriers to widespread adoption. This C.D. Howe Institute policy paper will examine the current state of AI adoption in Canada, assess its economic, social, and productivity implications, and identify key challenges hindering broader implementation. These challenges include regulatory uncertainty, workforce skill gaps, limited access to capital for AI-driven businesses, infrastructure limitations, data accessibility and interoperability issues, privacy and security risks, AI bias concerns, and a lack of understanding of AI’s capabilities. While Canada has made progress through initiatives like the Pan-Canadian AI Strategy, gaps remain in translating research leadership into tangible economic benefits and productivity gains. Understanding where these gaps exist and how to bridge them is crucial to ensuring that AI adoption drives efficiency, innovation, and competitiveness across industries.

To provide a deeper analytical foundation, this paper will also examine historical patterns of technology diffusion, highlighting why some countries and industries embraced new technologies faster than others. These insights will inform targeted policy recommendations to accelerate AI adoption while ensuring responsible development. Solutions will focus on regulatory clarity, AI investment incentives, workforce upskilling, and integration into public and private sectors. Informed by industry trends, government policies, and international best practices, this paper will outline key policy levers to strengthen Canada’s AI ecosystem and competitiveness.

Faculty Supervisor:

Bertrand Malsch

Student:

Partner:

C.D. Howe Institute

Discipline:

Sociology

Sector:

Professional, scientific and technical services

University:

Queen's University

Program: