Canada’s AI Dilemma: Bridging the Gap Between Excitement and AI Tech Adoption

Artificial intelligence, or AI, is reshaping industries worldwide, helping businesses improve efficiency, cut costs and better serve their customers. Yet Canada lags significantly behind other nations in AI tech adoption.

What’s holding America’s northern neighbors back?

In this article

1. Canada’s AI Buzz Isn’t Turning Into Action
2. The Problem: Lengthy AI Adoption Timelines
3. Why Canada Is Behind Its Global Counterparts
4. Large Language Models (LLMs) Are Revolutionizing Knowledge-Based Jobs
5. How Canada Can Move Toward a More Competitive, AI-Friendly Future
6. Canada and AI Tech Adoption: It’s Time To Turn the Enthusiasm Into Action

Canada’s AI Buzz Isn’t Turning Into Action

Why is Canada so much slower in putting AI into action compared to the U.S.?

While some experts attribute it to insufficient funding, others think culture is the culprit.

The lag in AI tech adoption is particularly curious given Canada’s prominence in AI innovation. Canadian companies have been pivotal in advancing AI research, with pioneers like Geoffrey Hinton and Yoshua Bengio leading the charge. However, despite being a global leader in AI talent and research, Canada risks losing its edge as other nations move ahead more decisively.

While the U.S. and Nordic countries are leveraging AI to boost productivity and grow GDP, Canadian businesses face prolonged adoption timelines and cultural barriers that hinder progress.

Should Canadians be blamed for caution? Tight corporate budgets? Lack of government funding? Whatever the reason, turning eagerness into actionable strategies and tangible results is a slow process — much slower than in other parts of the world.

The Problem: Lengthy AI Adoption Timelines

According to AI industry leaders Nick Frosst of Cohere and Nicole Janessen of AltaML, the typical AI tech adoption process in Canada spans three years: 18 months to commit and another 18 months to operationalize. This extended timeline can lead to frustration, stalled projects and missed opportunities.

“I’ve observed firsthand the excitement around AI in our business landscape,” says Dheeraj Jalali, Vice President of Technology at Voices. “However, adoption here is moving at a much slower pace than in the U.S., and we need to find ways to streamline this pipeline from ideation to real-world application.”

Why Canada Is Behind Its Global Counterparts

1. Cultural caution and transparency concerns: Trust, transparency and the demand for explainability in AI are key concerns for Canadian businesses. While these are important values, they can sometimes slow down the adoption of new technologies.
2. Limited funding and tight budgets: Insufficient investment in AI projects is another major hurdle. Businesses hesitate to commit resources without clear, immediate ROI.
3. Missed opportunities for productivity gains: Canada’s cautious approach contributes to its lagging real GDP per capita growth compared to other countries.

“While caution is commendable,” says Jalali, “we must balance it with the urgency to innovate. Our productivity challenges demand creative action in embracing AI solutions.”

Large Language Models (LLMs) Are Revolutionizing Knowledge-Based Jobs

LLMs hold immense potential for Canadian businesses.

These advanced models are sophisticated AI systems trained on vast datasets to understand, generate and analyze human-like behavior. They can perform tasks such as content creation, customer service automation, data analysis and personalized communication at scale.

By augmenting 20% of knowledge-based jobs, including roles in education, healthcare, marketing and finance, LLMs enable professionals to focus on strategic and creative work, improve operational efficiency and drive innovation across industries.

“The potential of large language models to boost productivity and create new revenue streams is immense,” says Jalali. “We need to capitalize on Canada’s strong AI research foundation and build a sense of urgency to translate it into practical business applications.”

How Canada Can Move Toward a More Competitive, AI-Friendly Future

• Foster collaboration between industries and researchers: Bridging the gap between academia and industry can help businesses harness cutting-edge AI innovations faster.
• Invest in training and upskilling: Preparing the workforce for AI integration is critical to successful adoption.
• Encourage risk-taking and pilot programs: Testing AI solutions in smaller, low-risk scenarios can build confidence and demonstrate ROI.

Canada and AI Tech Adoption: It’s Time To Turn the Enthusiasm Into Action

Canada’s cautious approach to AI adoption reflects our commitment to ethics and transparency but risks leaving the nation behind in the global AI race.

By fostering collaboration, increasing investment and embracing a more agile mindset, Canada can transform its enthusiasm for AI into actionable strategies that drive tangible results.

“We need to capitalize on Canada’s strong AI research foundation, build a sense of urgency and translate it into practical business applications,” states Jalali “At Voices, we’re actively exploring how to integrate AI responsibly, efficiently — and, most importantly, ethically.”