On a dreary Tuesday morning in Toronto’s financial district, a mid-sized commercial bank’s elevators appeared abnormally crowded. Framed images of oil rigs and prairie wheat fields, remnants of a lending culture that once relied on handshake deals and intuition, were hurried past by young analysts with laptops. Today, the majority of loan files are never on paper. Algorithms process them.
The small business lending industry in Canada is undergoing a nearly complete structural change. In addition to streamlining procedures, artificial intelligence is subtly shifting the balance of power among the nation’s 1.2 million small businesses, fintech competitors, and traditional banks. It appears that investors see this as a permanent recalibration rather than a technology cycle.
| Category | Details |
|---|---|
| Organization | SCALE AI |
| Headquarters | Montreal, Quebec, Canada |
| Founded | 2018 |
| Recent Investment | $98.6 million across 23 AI projects (2025 funding round) |
| Sector Influence | AI adoption across finance, manufacturing, logistics and SMEs |
| Government Alignment | Federal AI Strategy 2025–2027 |
| Reference Website | https://www.scaleai.ca |
Coordination at the federal level is partly responsible for the momentum. The recent formalization of Immigration, Refugees, and Citizenship Canada’s own AI strategy places a strong emphasis on the ethical and open application of AI in public services. Despite the apparent distance between immigration and commercial lending, the message was clear: Ottawa feels at ease incorporating AI into critical decision-making processes. Banks took notice.
Last summer, executives at SCALE AI’s headquarters in Montreal announced new AI investments totaling almost $100 million. Predictive forecasting and logistics optimization were among the projects. Lenders were keeping a close eye on the finance industry, even though it wasn’t the news. AI could most likely predict credit risk if it could predict retail demand and aircraft maintenance.
The change is subtle but noticeable if you visit any regional bank branch in Ontario today. Loan officers continue to sit across from trucking company founders and café owners. Beside them, however, is software that silently scores apps in real time by examining supplier histories, cash flow patterns, and even the timing of invoices. Once-weekly decisions now happen in a matter of days. Hours, sometimes.
In this case, speed might be the true revolution. Small companies have narrow profit margins. Payroll or inventory windows may be missed if you wait 30 days for approval. That timeline is being compressed by AI-driven underwriting models that were trained on years’ worth of anonymized transaction data. It’s incredibly efficient. Nevertheless, there’s a slight unease in the air. Who is the caller exactly?
Since the global financial crisis, Canadian banks—long considered to be among the most stable in the world—have made significant investments in digital infrastructure. Convenience, customization, and control are the customer expectations that are driving technology spending, according to industry interviews that World Finance published. Customers of small businesses are calling for the same smooth experience that they get from consumer apps.
Meanwhile, the incumbents are under pressure from FinTech startups. One AI-focused lender in downtown Vancouver offers revenue-based financing with approval decisions produced nearly instantaneously, out of a glass office with a view of Burrard Street. Executives assert that their models identify patterns that conventional credit scoring overlooks. It seems like a generational shift is taking place when business owners sign digital contracts on tablets rather than fumbling with bank drafts.
But beneath the optimism lies subtlety. Bias in historical data can be passed down to AI systems. Federal guidelines place a strong emphasis on privacy, accountability, and transparency. Particularly in borderline cases, lenders insist that human officers continue to be involved. But it’s still unclear how much discretion humans will maintain as models become more precise, or at least more certain.
It’s hard to overlook the growth figures. The Canada Forum for Impact Investment and Development reports that since 2019, impact investment assets in Canada have doubled. One of the top allocation sectors is still financial services. That story fits in nicely with AI-enhanced lending platforms, which are scalable, quantifiable, and promise both profit and inclusion.
More data-driven evaluations seem to be helping female entrepreneurs, one of Canada’s fastest-growing small business segments. In private, some bankers claim AI lessens subjective bias in credit assessment. That might be accurate. Or it might just switch out one type of opacity for another. After all, the assumptions that algorithms are based on determine how fair they are.
Diversification is subtly taking place in Calgary, where lending appetites were previously determined by the volatility of the energy sector. AI tools are locating areas of growth in specialty manufacturing, logistics companies, and clean technology startups. As commodity prices fluctuate, the models are continuously updated to recalculate risk exposure. The outcome has a lively, almost agitated feel.
The macroeconomic context is another. By historical standards, interest rates are still low, which promotes borrowing. Regulatory scrutiny is also getting more intense at the same time. Cybersecurity issues are major. Banks are investing in defensive AI systems that are intended to identify fraud and unusual patterns before funds leave the vault, in addition to smarter underwriting.
The range of adoption is what sets this moment apart from earlier technological advancements. AI is already being used internally by almost one-third of small businesses in Canada, whether for marketing, accounting, or logistics. It is nearly a given that lenders will operate in data-rich environments when borrowers themselves do.
As this develops, it seems as though Canada’s historically conservative financial system is about to embark on a more daring stage. Not careless—that term hardly ever describes Canadian banks—but unquestionably more innovative. AI is no longer limited to innovation labs or pilot projects. It influences thousands of business owners’ daily credit decisions.
It’s unclear if this extraordinary AI-driven expansion will eventually increase access to capital or focus it on the companies with the most data visibility. Often, technology quietly rewards scale while promising democratization. It’s difficult to ignore the fact that something fundamental has changed when you’re standing in those crowded elevators in Toronto and listening to analysts talk about model refinements rather than loan files.
The small business lending market in Canada is evolving beyond simple digitization. It’s thinking in a different way. Additionally, the old rhythms seldom return unaltered once an industry starts relying on machines to assess risk.
