From hype to impact: How Canadian SMBs can close the AI adoption gap

Whether it’s uncertainty about cost, a lack of technical know-how, or confusion over use cases, AI can feel out of reach for SMBs that already have too much on their plates. Fewer than 20% of mid-sized businesses in Canada are currently using it, citing barriers including limited technical talent, high costs, and an uncertain return on investment.

To help bridge that gap, AXL, a Toronto-based venture studio transforming world-class AI research into high-growth companies, has teamed up with RSM Canada, a leading provider of assurance, tax and consulting services. As part of the collaboration, RSM serves as the exclusive provider of accounting, tax, and consulting services to AXL, while also acting as a preferred provider for AXL’s portfolio of startup companies.

In this exclusive Q&A, Dr. Daniel Wigdor, CEO and co-founder of AXL, and Harry Blum, national managing partner at RSM Canada, share what’s holding SMBs back and how relationships like theirs are helping Canadian businesses move from interest to impact.

Dr. Daniel Wigdor is the Co-Founder and CEO of AXL, a Canadian venture studio turning world-class applied AI research into scalable companies. For over two decades, he has been at the forefront of human-computer interaction and applied AI through his work in academia, industry and entrepreneurship.

Harry is responsible for the strategic vision and direction of RSM Canada. In his commitment to the growth and culture of RSM Canada, Harry actively leads expansion and acquisition strategies as well as service line and business development.

Canada is known for AI research, but adoption, especially among small and medium-sized businesses, has lagged. What’s holding businesses back?

Daniel: Most SMBs aren’t lacking interest, they’re lacking confidence. They’re being told AI is the future, but they don’t know where to start, what’s relevant or whom to trust. The result? Inaction. That’s Canada’s real AI gap: not invention, but implementation. While we lead globally in research, we haven’t built enough infrastructure to turn that research into usable tools for Canadian businesses. The stakes are high: if we don’t solve the commercialization problem, we risk exporting the value of our innovations before they ever scale at home.

AXL and RSM recently partnered to tackle this issue. What makes your approach different from typical tech vendor models, and how can partnerships support AI adoption among SMBs?

Daniel: What makes our relationship with RSM so effective is that we’re building AI ventures around real, validated needs, not abstract concepts. From day one, we’re focused on developing practical tools that solve business problems and scale quickly. RSM Canada is part of our AI Catalyst program, where we team up with organizations ready to apply AI to solve real business problems. They help ensure those problems are rooted in the realities of mid-sized and large Canadian organizations, not just assumptions from a lab or demo.RSM brings strategic guidance, adoption context and internal innovation leadership—and together, we accelerate commercialization in a way that works for real businesses, not just research labs.

What are some of the most practical ways you’re seeing SMBs begin to adopt AI today in the different industries you work with, and where do you see the most potential?

Harry: We’re seeing our clients take a pragmatic approach to AI, starting with use cases that are easy to implement and deliver quick wins. In industries like manufacturing and logistics, AI is being used for predictive maintenance and supply chain optimization. In financial services and professional services, firms are automating document processing, client onboarding and even elements of tax compliance. 

What’s encouraging is that 72 per cent of middle market leaders we surveyed said they’re already experimenting with generative AI. That tells us the interest is there, but the real opportunity lies in helping them move from experimentation to integration. The most potential, in our view, is in areas where AI can reduce manual effort, improve decision-making and enhance client experiences—especially in data-heavy, process-driven environments.

What needs to happen for more Canadian SMBs to move from experimenting with AI to truly adopting and scaling it?

Daniel: The short answer? You have to treat AI adoption like any other strategic investment, with clear objectives, tracking and support along the way. That’s one of the core reasons we built AXL the way we did.

The truth is that the tooling that is available now only really supports the “crawl” phase of AI, where you automate what is being done now: a specific business challenge that’s causing friction.   Manual paperwork, process bottlenecks or gleaning insights from data are some obvious examples. You can then design AI solutions around that problem, with a laser focus on usability and ROI. 

AXL’s approach is to accelerate to the “run” phase of AI adoption, where we uncover whole new solutions to business problems that are not yet apparent, or which our partner is currently solving in some other way for their clients.

Many SMBs benefit from simple, repeatable wins that build confidence and momentum. If you start small, measure results and build on what works, that’s how adoption scales. And that’s exactly what our Catalyst model is designed to do: reduce risk, prove value early and make AI something that drives your business, not distracts from it.

RSM Canada is known as a trusted advisor to the middle market. Why was it important for RSM to take such an active role in AI adoption?

Harry: Because the middle market is where innovation meets execution. These businesses are agile enough to adopt new technologies quickly, but they often lack the internal resources to do it confidently. At RSM, we see AI as a defining force in the future of business and believe it’s critical that mid-sized companies aren’t left behind. 

That’s why we’ve committed over US$1 billion globally to AI innovation. Our role is to help clients not only understand what’s possible, but also implement AI in a way that’s practical, secure and aligned with their goals. By collaborating with AXL, we’re bringing together deep business insight and world-leading AI to help Canadian businesses close the adoption gap and excel in a digital economy.

What advice do you have for SMB leaders who want to explore AI, but don’t know where to begin?

Daniel: Start with the problem, not the technology. AI isn’t something you adopt for its own sake. It’s a tool to help you work smarter, faster or more accurately. So the simplest place to begin is by identifying a repetitive, manual or time-consuming task in your business. Then ask: is there a smarter way to do this?

You don’t need a PhD or a data science team to get started. There are solutions already out there, and many of them are built specifically for businesses of your size. 

The biggest risk is standing still. You don’t have to go all-in overnight, but you do have to start.

Harry: Start with a business problem, not a technology pitch. The most successful AI projects we’ve seen begin with a clear pain point—something repetitive, time-consuming or prone to error. From there, it’s about identifying the right tool or partner to help solve it. 

Our survey found that while 91 per cent of middle market leaders believe AI will significantly impact their business, only 27 per cent feel prepared to manage that impact. That’s a big gap, and it’s why we emphasize education, experimentation and trusted guidance. You don’t need to go all-in on day one. Start small, measure results and scale what works. And don’t be afraid to ask for help; this is a space where the right advice can make all the difference.

Disclaimer:

The views and opinions expressed in this interview are those of the interviewee and do not necessarily reflect the official policy or position of CanadianSME Small Business Magazine. The content provided is for informational purposes only and should not be construed as professional advice. CanadianSME is not responsible for any actions taken based on the information provided in this interview.