How founders are rethinking capital in the AI era | BetaKit

AI is giving early-stage founders more room to experiment before raising significant amounts of capital, and this is changing how entrepreneurs think about when to raise and where that money gets deployed.

“What has become possible with a small team of really good people is phenomenal.”

George Babu, Aire Labs

George Babu is taking a more deliberate fundraising approach to his latest venture, Toronto-based Aire Labs. In 2007, he joined David Stein and Daniel Debow to co-found Toronto-based performance management company Rypple, which was acquired by Salesforce in 2011. He later co-founded San Francisco and Toronto based robotics firm Kindred Systems before it was acquired by the Ocado Group in 2020.

When he built Kindred, the company raised substantial capital early, which Babu said created room for mistakes. With Aire Labs, he is focused on keeping the company lean while it experiments. 

“You can take very little capital, have a lot of control, and do a lot of experiments until you feel confident, and then you take a lot of capital,” Babu said on a recent episode of The Gradient Ascent Podcast.

The episode, hosted by CIBC Innovation Banking Executive Managing Director Paul McKinlay and CIBC Capital Markets Managing Director Daniel Lee, featured Babu and Gideon Hayden, Co-Founder and Managing Partner at Leaders Fund.

The conversation explored a changing funding calculus for tech companies as AI raises investor expectations, expands what small teams can accomplish, and shifts where startups allocate their spending.

Capital follows conviction

At project development platform Aire Labs, AI has already helped Babu’s team run more experiments without having to add headcount. The company has accumulated hundreds of transcripts from customer discovery calls that can be searched and analyzed when the team is considering building a new feature. AI tools also allow Aire Labs to customize and test messaging for particular customers and market segments, without the need for a 40-person team.

“What has become possible with a small team of really good people is phenomenal,” Babu said. “I can run way more experiments on much less capital, until I find that thing that then can be venture-fuelled. And you can keep doing that again and again and again, and ultimately that’s how you build an enduring company. You just keep making these bets.”

Babu pointed to Shopify’s early development as an example, noting the company did not take much capital in its early days because the market didn’t have conviction that another e-commerce company was needed at the time. 

“They were very lean,” Babu said of Shopify. “They had to build their culture, build their processes, find where the real product-market fit was, and then they could raise a ton of money and go and just dominate the market.”

Staying lean early has become particularly important as expectations for venture-backed startups have skyrocketed. Babu noted that the bar for Seed and Series A startups is considerably higher compared to a few years ago, and raising a larger round creates an expectation that the money will be put to work quickly.

“If you’re going to take a lot of money, you better go fast and very far,” Babu added. “I don’t think it changes that you still need a lot of capital to build an enduring company.”

What a round buys

None of this means that AI has made building a successful company cheap, according to Hayden. “We have not seen the cost of building come down at all. If anything, it’s gone up,” he said.

His firm, which invests primarily at the seed and Series A stages across enterprise software, cybersecurity, and  AI-native infrastructure, has seen a change in the composition of startup spending. He explained that many R&D-heavy teams plan to add employees at a slower pace because existing engineers can do more in less time with the help of AI tools. He has seen budgets increasingly account for both engineers and the token or compute spending required to equip those employees.

“What these tools effectively allow you to do is buy time,” Hayden said, noting that AI can give a company the capacity of many engineers working simultaneously, which compresses the time it takes to pursue an opportunity.

McKinlay noted that product development is only one part of a company’s cost base, and that reaching and retaining customers remains the most expensive part of company building. Babu estimated that a company may end up spending 30 percent of the budget on R&D and 70 percent on go-to-market, sales, and marketing, which makes the application of AI in the latter functions of the business particularly important to him.

AI also introduces a new variable into startup spending: model costs can be difficult to predict. “Part of enterprise buying enterprise software as a subscription is [that] you have some predictability to what that line item is,” McKinlay said. “AI can throw a wrench in that to some extent.”

While he expects the cost of AI tools to get cheaper in time, Babu has already seen Aire Labs’ bills rise enough in the short term to accelerate plans for multi-model workflows. His company has made its own architecture model-agnostic, which allows it to switch between providers if prices change.

“Right now, everyone’s exploring and no one minds the bills, but once you operationalize something, you don’t want to pay that bill,” Babu said. “The vendors that optimize [for model costs] from the beginning are going to be in a better position than those that don’t.”

At the seed and Series A stages, Leaders Fund places relatively little emphasis on a company’s margin profile, though the firm does need to believe the business can eventually produce sustainable unit economics.

The more immediate concern is whether the company is creating products customers find sufficiently valuable. Hayden expects this test to become more important as the enthusiasm around AI adoption matures. He sees many businesses currently buying AI products because of pressure to demonstrate that they have an AI strategy. Hayden expects that buying frenzy to eventually subside.

“There’s going to be this rationalization period that will come,” Hayden said, “when companies are going to say, ‘OK, this is cool, but is this actually delivering value?’”

Building the capital flywheel

The changing economics of company building also raises questions about whether Canadian founders can access the early capital required to fuel the experimentation stage. Research from Leaders Fund found that from 2015 to 2020, roughly 75 percent of Canadian-founded startups were started in Canada. But in 2024, nearly half of Canadian founders who had raised over $1 million were based in the United States.

Hayden, who presented his firm’s research in the House of Commons last year, has argued that Canada could encourage more early-stage investment through measures such as a long-term capital gains exemption and an angel investor tax credit. The latter, he said, would be particularly useful for companies raising their first angel round, often one of the more challenging milestones for young startups.

McKinlay said successful startup outcomes create a “flywheel effect,” as founders who build wealth in the sector reinvest it in former colleagues and new ventures.

“That’s one of the things you see in the Valley that is so powerful,” McKinlay added. “To enable that here further would be amazing.”

Creating that cycle also requires financing beyond the first cheque. As startups move from experimentation toward larger rounds and global expansion, their capital needs to evolve alongside them. CIBC Innovation Banking has spent more than 25 years providing financial advice, growth capital, and debt financing to tech companies and investors across Canada, the US, and Europe. 

“Silicon Valley is a gravitational force. We’re not going to replicate that,” Hayden said. “But I think if we can create an environment for entrepreneurs that convinces more of them to build here, I think that’s healthy.”

Watch the full episode of The Gradient Ascent Podcast : The Future of Canadian Startups: AI, Capital, and Brain Drain here.

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