AI starts with the owner: what the 2026 numbers say about small businesses

In the second quarter of 2026, 19.2% of Canadian businesses used AI to produce goods or deliver services. Two years earlier it was 6.1%. The tools have arrived in small businesses faster than almost anyone expected, and the smallest firms are not far behind: 19.9% of businesses with one to four employees used AI, against 27.8% of those with 100 or more.

So the question for a small business owner is no longer whether AI will reach their industry. It is whether they will lead how it is used in their business, or let it happen by accident. The latest Statistics Canada data points to where the real gap sits, and it is not the software.

The gap is in how owners see AI

Statistics Canada asked businesses whether AI is relevant to them. Among firms with one to four employees, 41.4% said no. Among firms with 100 or more, only 21.3% did. When businesses that had no plans to use AI were asked why, 78.1% said it was not relevant to their goods or services, and 11.3% said they did not know enough about what it could do.

“Not relevant” is sometimes the right answer. A business that runs on skilled hands and repeat customers may have little to gain right now. But it is often a judgment made before looking. When BDC surveyed entrepreneurs in 2024, 39% said they used AI. After seeing a list of common AI-powered tools, the figure rose to 66%. More than a quarter were already using AI inside software they paid for, without knowing it.

That matters because a tool you don’t know you are using is a tool nobody has set rules for. It is drafting emails, summarizing calls or suggesting replies to customers, and no one in the business has decided whether that is a good idea.

Training is where small firms fall furthest behind

The sharpest difference in the 2026 data is not who uses AI. It is who learns how to use it. Among businesses already using AI, larger firms train their people at nearly three times the rate of the smallest ones.

In a business of four people, the “executive” is usually the owner. Fewer than one in six of those owners had any AI training. That is understandable, since nobody else is running the shop while they learn. It also means the person who decides what the business buys, and what risks it takes with customer data, is often deciding without hands-on experience.

What actually holds owners back

The barriers owners report are practical, not ideological. In CFIB’s 2025 survey of 1,683 small businesses, the main obstacles to adopting digital tools, AI included, were:

• Lack of digital knowledge or skills (51%)
• Not enough time to explore options (49%)
• High setup and investment costs (48%)
• Difficulty finding solutions that fit their specific needs (43%)

CFIB found that businesses with fewer than five employees face the most constraints, and that owners in British Columbia and Alberta report more trouble finding technology suited to their needs. Statistics Canada adds two more: among businesses whose AI use is limited, cybersecurity or privacy concerns (13.4%) and cost (10.6%) top the list.

About four in ten small businesses now use generative AI, CFIB found, but only 18% use it daily. Many owners have tried it. Far fewer have made it part of how the work gets done.

Four jobs only the owner can do

None of this requires the owner to become a technologist. It does require four decisions that nobody else in a small business can make.

1. Name the problem first. AI is useful only against a specific goal: fewer hours on quotes, faster replies to enquiries, less time chasing invoices. Without that, every new tool looks equally promising. This is why we start every project with a Zenith Goal.
2. Learn enough to judge. An hour a week of hands-on use, on your own work, teaches more than any webinar. The aim is not expertise. It is knowing what a good output looks like and where the tool tends to be wrong.
3. Set the rules. Which tools are approved, what data can go into them and who checks the output before a customer sees it. A one-page policy is enough to start. Our guide to using AI with client data covers the basics.
4. Protect time to learn and measure. Staff will not change how they work if every hour is already booked. Set aside time for a short trial, measure the task before and after, and decide based on the result. Our two-week test is a simple way to do it.

The challenges AI brings, plainly

AI is not free of risk, and owners who are cautious are not wrong. The common problems we see are ordinary ones:

• Confident mistakes. AI drafts can be wrong while sounding certain. Anything that reaches a customer needs a person to check it.
• Client data in the wrong place. Free tools may store or reuse what you paste in. This is the risk owners worry about most, and with reason.
• Subscriptions that creep. Every product now sells an AI add-on. Without a clear purpose, the monthly bill grows faster than the benefit.
• Worried staff. People wonder what AI means for their jobs. Owners who explain the goal, usually removing tedious work, get far more support than those who simply roll out a tool.

Each of these is manageable when the owner is involved from the start. Each becomes expensive when AI arrives through a software update and nobody owns it.

TopicsAILeadershipTraining