Policy Matters: The Big Questions about AI and Canadian Business

February 10, 2026

In this Policy Matters, we’ll try and answer some of the big questions we, and others, have been asking about AI.

How are Canadian companies using AI?

AI is changing how businesses work. Of the Canadian businesses reporting AI use in the last year, the top changes made after adoption were developing new workflows (40%), training current staff to use AI (39%), and purchasing cloud services or cloud storage (26%).

Professional services, finance and insurance, information and culture, and health and social assistance are Canada’s major AI adopters. Between Q2 2024–Q2 2025, each of these four sectors increased their AI adoption by over 10%, some even as much as 15–20%. How are businesses in these sectors using AI?

Professional services: data analytics (44% of businesses); speech or voice recognition and machine learning (32%).
Finance and insurance: data analytics (41%); speech or voice recognition (35%); and machine learning (31%).
Information and culture: virtual agents or chat bots (41%); machine learning (36%); natural language processing (35%).
Health and social assistance: suggestion systems (24%); virtual agents or chat bots (21%); neural networks and machine learning (17%).

Is AI taking Canadian jobs?

According to an Abacus Data survey in 2025, 47% of Canadians were somewhat or very concerned that AI and automation would take over their job or force them to change their job/career in five years. Similarly, 70% of Canadians felt that AI would likely make some jobs in their industry obsolete.

So far, our data shows that AI adoption up does not necessarily equal jobs down. There’s no one-to-one ratio. According to the BDL’s Q4 2025 Business Insights Quarterly, only 6% of Canadian businesses using AI have decreased total employment. Most (89%) have not changed employment.

In industries with rising AI adoption, there were job gains and losses. For example, since Q2 2024, the finance and insurance sector increased their AI adoption by over 20% and their job growth by around 8%. On the other hand, the mining, oil and gas sector increased their AI adoption by less than 5% but employment growth decreased by over 8%. Youth employment — another concern given Canada’s youth unemployment rate of 12.8% (November 2025) — has also been holding up in high AI adoption industries.

Why is Canada behind in AI adoption?

Despite the four sectors leading in AI adoption, Canada overall is lagging. In 2025, roughly 12–14% of businesses were using AI or planning to use AI. BDL projects adoption to reach 17–18% this year — still far short of where we need to be if we’re to keep pace with global peers.

In 2024, BDL put forward two adoption scenarios in the report Prompting Productivity: Generative AI Adoption by Canadian Businesses. BDL predicted that Canada would reach an AI adoption tipping point of 50% between 2027 (fast adoption scenario) and 2030 (slow adoption scenario). Projections for 2026 AI adoption align with the slow adoption scenario.

How can we encourage AI adoption in the private sector?

First the question: Why do Canadian businesses need to adopt AI?

AI can help address one of the greatest economic threats to Canadian prosperity and living standards: low productivity. Productivity is closely linked to a country’s prosperity and long-term standard of living (measured by GDP per capita). By making work more productive, AI could prompt productivity gains for Canada by accelerating and automating workers’ low-value and labourious tasks at little cost, allowing them to focus their time on higher-value activities.

And now, the areas to focus on to encourage adoption in the private sector:

→ Regulation

It’s critical that Canada’s approach to regulating AI creates a favourable environment in which businesses can thrive and contribute to Canada’s economic success. We cannot add red tape that will stifle innovation and undermine private sector investment.

One of our recommendations in the 2025 B7 Communiqué that we developed with our counterparts was to strike a balance between regulation and innovation. Developing more pro-innovation policy frameworks will ensure that technological advancements can thrive, at the same time ensuring the responsible development and use of AI to protect national and personal privacy and security.

→ Investment

In 2024, a third of Canadian businesses reported access to finance as a challenge preventing the adoption of new technology.

Providing targeted financial incentives, establishing sector-specific AI centres of excellence to support SMEs, promoting access to cloud infrastructure, and fostering collaboration between technology providers, industry stakeholders, and academia would help increase adoption.

→ Workforce

In BDL’s Prompting Productivity report, Canadian businesses cited hiring skilled employees (35%) and retraining employees with new tech skills (28%) as challenges to adopting new technologies. To enable widespread and responsible AI adoption, Canada should expand AI-related education, workforce upskilling, and talent pipeline development to address these challenges.

In the B7 Communiqué, there are several recommendations for B7 governments to help with preparing the workforce.

Partner with industry, academia and polytechnics to encourage broad-based AI and digital education by developing certificates and skills programs in addition to graduate and postgraduate programs in AI.
Support industry to upskill/reskill workers by providing targeted funding and resources for organizations that support workers to develop AI-relevant digital skills across sectors

→ Infrastructure

In our B7 Ministerial on Industry, Digital and Technology, one of the panellists described Canada as being in a privileged position because we have the compute, talent and innovators that are necessary for AI leadership.

At the same event, panellists warned that there’s a danger in throwing money at unnecessary infrastructure. Standing data centres at the size and scale needed for general purpose data sets is hugely expensive; they should set up centres only for what is critical, like protected data sets that must remain sovereign. Governments should instead help facilitate demand by ensuring access to compute for researchers who want to work in the country, provide incentives for the local business community to encourage adoption, and expand the capacity of compute infrastructure providers in Canada to incentivize increases in the supply and availability of compute within Canada.

What is compute? According to Innovation, Science and Economic Development Canada, “AI compute refers to the computational resources required for AI systems to perform tasks, such as processing data, running algorithms and training machine learning models. In other words, AI compute is the technology that powers AI.”

→ Public Buy-In

Trust is important for technology adoption. Public interest and acceptance of AI tend to be positively correlated with a country’s business adoption rates, but global IPSOS surveys reveal that Canadians are less knowledgeable and more nervous about AI than citizens of most other countries. Getting Canadians to trust AI will be a big step in increasing overall adoption rates.

What is the Canadian Chamber working on?

Visit our Future of AI Council page for more on our AI advocacy.
Read the 2025 B7 Communiqué for our recommendations to G7 governments.
Register for The Case for Canada: Making AI Count, BDL’s data conference on March 26.

Blog