Founders fundraising without a defined strategy for leveraging artificial intelligence (AI) are having a harder time wooing investors, industry leaders said at Startupfest in Montréal.
“There needs to be some powerful reason why, a ‘why now,’ without that business model.”
Amy Wu Martin
Menlo Ventures
This is a particularly acute problem in the software space, they added, where competition is cutthroat.
In conversation with BDC Capital executive vice-president Geneviève Bouthillier for the BDC Women in Technology Bootcamp, Menlo Ventures consumer partner Amy Wu Martin said it’s internally considered an “exception” if the Calif.-based firm invests in a company with no AI strategy.
“There needs to be some powerful reason why, a ‘why now,’ without that business model,” Martin said.
Martin’s remarks echoed a broader theme on day one of Startupfest, as investors shared insights about how they distinguish between promising companies wielding AI tools and those merely jumping on the hype train.
At a panel hosted by Toronto-based venture capital (VC) firm Georgian Partners, investors agreed that AI has increased expectations for startup growth metrics, from the pre-seed stage to the growth stage.
Now, the ideal timeline to hit $1 million in annual recurring revenue has changed from two years to six months, said Elizabeth Yin, general partner at San Francisco-based Hustle Fund, which invests in ventures at “hilariously early” stages.
“The bar has gone up,” she added.
Isaac Souweine, partner at Vancouver-based Pender Ventures, said his firm expects startups to do more with fewer software engineers because of generative AI tools.
“Now you have this mega computer brain you can access with fewer coder efforts,” Souweine said.
As some AI tools show the potential to automate administrative and engineering tasks, some Canadian tech firms have adopted “AI-first” strategies where employees are expected to prove they cannot do work with AI before asking for more resources or headcount, including Shopify and OpenText.
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Investors are now looking for proof of a long-term competitive edge and sustainable revenue, panellists said. Year-over-year revenue growth and a company’s burn multiple—how much cash it spends for every dollar of annual recurring revenue earned—are both key metrics.
However, they warned that the “hypergrowth” observed now in companies building enterprise and consumer-facing AI products, such as software developer tools Cursor and Lovable, is not necessarily sustainable and more akin to a “bubble.”
“How resilient is that revenue over time?” Emily Walsh, lead investor at Georgian, said on stage. “You have to be sure that it’s sticky. Retention matters.”
Some of these companies that achieved impressive revenue within months, particularly those building AI productivity tools, could be easily displaced by similar startups, panellists commented. Yin said she has seen single-feature rollouts from big tech companies such as OpenAI significantly impact a startup’s month-to-month revenue.
For Canadian startups, differentiation is even more important, Yin said. The VC noted a “sense of urgency” among San Francisco-based founders, driven by cutthroat competition, that she has not encountered anywhere else.
“I think that paranoia is what drives people,” Yin told BetaKit after the panel. “People in San Francisco are not any smarter or more talented [than Canadians], but the environment creates that.”
Feature image courtesy Eva Blue.