- According to Statistics Canada (June 2026), 19.2% of Canadian businesses used AI to produce goods or deliver services in the second quarter of 2026, up from 6.1% in 2024.
- Finance and insurance ranks among Canada’s most advanced sectors, with 40.4% AI adoption in 2026 (Statistics Canada).
- AI-based decision-making systems more than doubled in one year among AI users, from 5.7% to 13.7% (Statistics Canada, 2026).
- In Quebec, 12.7% of businesses used AI in production according to the Institut de la statistique du Québec (November 2025).
The executive committee wants to know whether the company is behind on AI. Someone mentions a competitor that supposedly automated its order entry, someone else doubts the payback. Nobody around the table has a reliable number to settle it.
Those numbers now exist.
In the second quarter of 2026, 19.2% of Canadian businesses used AI to produce goods or deliver services, triple the 2024 rate, according to Statistics Canada.
Where does AI adoption in business stand in Canada?
AI adoption in business reached 19.2% of Canadian companies in the second quarter of 2026, up from 12.2% in 2025 and 6.1% in 2024, according to Statistics Canada. The proportion has tripled in two years, with no sign of a plateau.
The most telling number in the survey sits elsewhere. Two in five businesses (40.0%) say AI is not relevant to them. One in five already uses it, while two in five have stopped looking. The competitive advantage of the next few years lives in that spread.
The results come from the Canadian Survey on Business Conditions, run from April to May 2026 with 9,251 responding businesses, which makes it the most solid measure available in the country.
In Quebec, the Institut de la statistique du Québec measured use at 12.7% of businesses for the 12 months preceding the second quarter of 2025. The next update will show whether Quebec follows the national curve or falls behind.
Which sectors lead AI adoption in 2026?
Information and cultural industries (42.3%), finance and insurance (40.4%) and professional services (32.4%) show the highest AI adoption rates in Canada, according to Statistics Canada (2026).
Sector benchmarks for the second quarter of 2026:
- Information and cultural industries: 42.3%
- Finance and insurance: 40.4%
- Professional, scientific and technical services: 32.4%
- Businesses with 100 or more employees: 27.8%
- Canadian average, all sectors: 19.2%
- Construction: 9.2%
- Wholesale trade: 7.9%
Size matters as much as sector. More than one in four businesses with 100 or more employees already uses AI. A distributor or manufacturer that feels safe should look at the finance line: that is where its customers, insurers and bankers are tooling up.
What are businesses actually doing with AI?
Data analytics (36.6%), text analytics (34.5%) and virtual agents (28.2%) are the most common AI applications among Canadian AI users in 2026, according to Statistics Canada.
The fastest-growing use hides further down the list. AI-based decision-making systems jumped from 5.7% to 13.7% in one year, more than doubling. Businesses are moving from summarizing documents to making operational decisions with AI.
We see the same shift inside ERP systems, where agentic AI is settling into finance processes. Cash application automation is a clear example of analysis turning into action: payments get applied to the right invoices instead of feeding one more report.
What barriers still hold back AI adoption in business?
Cybersecurity and privacy concerns, cited by 13.4% of businesses, rank ahead of cost (10.6%) as barriers to AI use in Canada in 2026.
Among businesses with 100 or more employees, that concern climbs to 30.0%. The caution is warranted: plugging a model into customer or financial data requires proper access and data governance before the first use case.
The 2026 divide separates businesses that wire AI into their processes from those that leave it at the edges.
AI is also reshaping teams. Among users, 44.4% changed their training or staffing practices, and 30.2% of businesses with 100 or more employees brought in external consultants or vendors, again according to Statistics Canada.
Where should you start without an AI roadmap?
Start with a measurable operational pain point, one process at a time, rather than with the tool of the moment.
In our ERP mandates and AI workshops at PlanAxion, the use cases that survive the first quarter all pass the same filter: a problem to solve, expected value, available data and a realistic effort.
That is the approach behind our four-week AI workshop: prepare, identify, prioritize, validate the data, then decide and deliver. The investment varies with scope and is confirmed during a short exploratory call.
What should you do with these numbers before the end of 2026?
National averages decide nothing for you. They only show that your competitors, customers and bankers are moving. If your sector sits at 40% adoption, waiting has become a risky position. If it hovers at 8%, you have a window to get ahead at low cost.
Frequently asked questions about AI adoption in business
How many businesses use AI in Canada in 2026?
According to Statistics Canada, 19.2% of Canadian businesses used AI to produce goods or deliver services in the second quarter of 2026. That proportion has tripled since 2024, when it stood at 6.1%. Businesses with 100 or more employees reach 27.8%, and urban businesses 21.0%.
What is the main barrier to AI adoption in business?
Cybersecurity and privacy concerns top the list, cited by 13.4% of Canadian businesses in 2026, ahead of cost at 10.6%. Among businesses with 100 or more employees, the proportion reaches 30.0%. Clear rules for data access and governance resolve a large share of those concerns.
Which Canadian sectors are furthest ahead on AI?
Information and cultural industries lead with 42.3% adoption, followed by finance and insurance at 40.4%, then professional, scientific and technical services at 32.4%. At the other end, wholesale trade (7.9%) and construction (9.2%) remain largely in observation mode, according to Statistics Canada’s 2026 survey.
How should a business get started with AI?
Start from a specific operational pain point rather than a technology. Screen every idea for the problem to solve, expected value, available data and required effort, then test a single measurable use case. A structured workshop of a few weeks is often enough to turn scattered ideas into a prioritized roadmap.
