A Competitive Edge: How AI Adoption Could Give Your Business the Advantage

Canada’s businesses are falling behind leading global peers when it comes to AI adoption, with significant implications for the country’s long-term economic growth.

Adoption has been rising steadily among Canadian firms, growing from 3% in 2022 to 12% in 2025 to nearly 20% as of mid-2026, but remains well behind global peers, especially at the small business level. Just 8% of Canadian small and medium enterprises (SMEs) have adopted the technology. By comparison, 18% of small businesses in France, 26% of those based in Germany and between 29% and 42% of those based in Nordic countries used AI to produce goods and services between mid-2024 and mid-2025.

That’s a troubling prospect considering 99% of Canadian businesses fall into the small to medium category, and collectively employ nearly two-thirds of the country’s working population. While nearly half of SME owners have experimented with generative AI tools, only one in eight Canadian businesses have formally integrated them into their operations.

“Canada’s economy is mostly made up of small and medium enterprises, so how quickly they adopt AI matters for productivity across the whole economy” explains Sabreena Shukul, a senior research associate for RBC Thought Leadership. “Canada is producing fast-growing AI startups, and Toronto is ranks third in North America for tech talent, but broad adoption by businesses has been slower.”

Released in June of 2026, the federal government’s National Artificial Intelligence Strategy: AI for All seeks to motivate greater AI adoption among Canadian businesses, and especially SMEs. It introduces roughly $2.3 billion in direct investments towards the country’s AI infrastructure, including $1 billion in dedicated financing and regional grants intended to support adoption among SMEs.

“AI for All was a really big signal that the Canadian government is taking AI adoption seriously,” Shukul says. “It’s organised around three ideas: trust, opportunity, and sovereignty. It pairs support for adoption with commitments on privacy, safety, and safeguarding Canadians.”  

Why do Canadian businesses appear to be taking it slow with AI adoption?

A 2025 report from RBC Thought Leadership and the University of Toronto’s Munk School of Global Affairs & Public Policy found that barriers facing AI implementation included a proclivity towards the status quo; a lack of understanding around potential benefits; difficulty in deciding where to start; low quality of data and data integration; and inadequate computing infrastructure.

“With some enterprise technology, waiting was the right call,” Shukul says. “The technology matured, implementation got cheaper, and later adopters paid less for a better product.”

While slow and steady won the race in previous waves of technological advancement, Shukul suggests that this time around is different. 

“With AI, the cost of experimenting with off the shelf tools is already fairly low. The scarce input is organizational learning, which only accumulates through use,” she explains. The bigger costs, like integrating systems and cleaning up data, should be considered and may be worth planning for.

Canadian businesses may also be slower to embrace AI than international peers because of the domestic competitive landscape. A relatively low adoption rate could indicate that business leaders don’t feel the same competitive pressure that they would if adoption was more widespread among direct competitors. However, Shukul notes that many of the forces that shielded Canadian businesses from global competition are less firm than in the past.

“The conditions that produced that shelter—geography, market structure, trade agreements, being next to the U.S.—they’re less reliable than they were before,” she says. “AI is arriving in a different environment, businesses that start learning about it now, even on a small scale, will be better placed to judge where it does and doesn’t fit.”

While concerns and challenges to successful AI adoption persist, business leaders can take advantage of resources, case studies and government programs to assess whether there’s a business case, and if so, how to adopt AI responsibly.

What’s the business case for AI adoption?

For many business owners, AI’s value can be hard to pin down, challenging in part because the technology has so many potential use cases.

AI applications can range from operational efficiency and speed to data-driven insights, improved customer experience, innovation, risk management, employee development, and marketing insights.

“The proof is in the pudding, and you want to be able to see it work before you invest time and money into implementing something,” Shukul says. “The best way to do that is to explore the businesses that are doing it successfully, how they’re using it, where it hasn’t worked, and how it could be applicable.”

Examples of Canadian companies using AI successfully

RBC’s Bridging the Imagination Gap report seeks to highlight some of those use cases in hopes of providing inspiration to others seeking to solve similar challenges. Examples include:

• Hopper, a Montreal-based travel platform that is handling customer inquiries 75% faster while reducing costs by 90% without compromising customer satisfaction by imbedding AI into its customer support function.

• Lumberhub, a Toronto-based startup using AI to solve the pricing lag between sawmills and home builders, reducing quote-to-order cycles from days to minutes.

• Linamar, a Guelph-based precision manufacturer whose AI solution identified otherwise imperceptible micro-fluctuations in pump pressure that were creating unnecessary costs.

Finding the AI business case for SMEs

While the large, all-purpose AI platforms tend to dominate the headlines, Shukul emphasizes that there are many industry, function and role-specific solutions designed to help SMEs do more with less or unlock entirely new capabilities.

Shukul adds that AI can be particularly valuable for business owners who often need to wear a lot of hats and manage a range of business functions that fall outside of their primary domain. Outsourcing some of those functions to AI can help them become better operators while dedicating more of their time and energy towards those areas of more direct interest and expertise.

Recognizing and mitigating AI-related risks

As businesses start to change established processes and systems to support new AI tools, new risks may be introduced. For example, the quality of AI-generated outputs can lead to the propagation of inaccurate information, and tools can fall foul of sharing hallucinations and bias that could lead to misinformed discussions and decision-making.

Providing employees with guidelines and training on appropriate AI use can empower them to use tools responsibly and monitor outputs. Risk assessments to identify security gaps can help to protect businesses from threats to cybersecurity or privacy – a concern that more than one in ten businesses cite as a reason to limit AI use.

Advice for businesses considering AI

Shukul suggests dedicating some time to understanding how the technology works so you can better identify where it can make the biggest impact in your business.

“The bottom line here is to start thinking about these processes, start talking to your partners and others in your business to see where you can implement it and who can really benefit from it,” she says. “It’s a process, not an overnight decision.”

Common entry points for businesses are data and text analytics, virtual agents or chatbots for customer service and sales functions, natural language processing, and marketing and communication assistance.

“These are popular starting points if you are a business that has a lot of data or your business depends on understanding data, whether it’s market analytics, invoice processing or accounting,” she says. “If your business is in operations or supply chain, looking at demand forecasting, inventory optimization or predictive maintenance could be beneficial, and similarly for sales and marketing, looking at things like proposal responses or CRM data.”

While most businesses can find value in AI adoption, how they extract that value can differ dramatically between them based on the nature of their operations. Understanding where to start requires a deep understanding of those operations, and a basic understanding of the technology’s capabilities. Most business owners already have the former; acquiring the latter comes partly from trying tools on low-risk tasks, and partly from understanding their limits, including accuracy, privacy, and data security.

Resources to help Canadian business owners become more AI literate

With AI familiarity and literacy being a primary enabler of adoption numerous institutions, both public and private, have invested significant resources into making that education widely available.

For example, many of the major AI platform providers offer free education targeted to small business owners, including Google, Salesforce, Anthropic, and OpenAI, as well as Amii, BDC, and Mitacs AI Advantage placements.

Canada’s National AI Strategy, meanwhile, will provide all Canadians with access to free AI literacy training, including free education specific to SME AI adoption administered through Business Development Bank of Canada (BDC), and The National AI Literacy Initiative will offer free AI education to the next generation of Canadian workers. The program seeks to upskill one million post-secondary students to ensure Canadian businesses can access the AI talent they’ll need in the future.

“If you’re curious about whether AI could be useful for your business, there are more free and low-cost ways to learn about it than there were even a year ago, and much of that is government-supported.” Shukul says.

The National AI Strategy also earmarks $700 million to offer affordable, secure, and sovereign AI access to Canadian small businesses, $130 million to support a new generation of AI entrepreneurs, and $159 million to protect Canadian intellectual property.

“On the tax side, Budget 2025 enhanced the Scientific Research and Experimental Development credit and introduced the Productivity Super-Deduction program, which lets businesses write off things like computers and data infrastructure that can lower the cost of investing in technology in general.”

The National AI Strategy also includes additional, industry-specific resources for businesses in five priority sectors where Canada has an opportunity to be a global leader: health and life sciences, energy and natural resources, transportation, agriculture, manufacturing, and robotics.