
Canva, the design software company, has cut its revenue growth forecast by a third to 20% because the cost of delivering AI features turned out to be far higher than expected.
The company decided to slow its AI rollout and rebuild its technology architecture to reduce costs before rolling out broadly, rather than launch at unprofitable economics.
This signals a broader challenge across the software industry: AI capabilities are costly to deliver, threatening the low-cost operating model that made SaaS software so lucrative.
What happened
Canva slashed its expected revenue growth rate to 20% from its prior forecast, citing unexpectedly high costs to deliver AI features. CEO Melanie Perkins said user demand for new AI capabilities "significantly exceeded" expectations, forcing the company to slow its rollout and rebuild its architecture to reduce unit costs.
Why it matters
Canva has long been a rare startup combining rapid growth with profitability—a model now threatened by generative AI. The cost problem is acute because AI is central to Canva's strategy to expand from design software into a broader workplace platform. The situation reflects a broader industry challenge: companies cannot afford to skip the AI boom, yet embracing it undermines the traditional zero-marginal-cost economics that made SaaS software so profitable.
What to watch
Canva has reduced cost per task by nearly 90% since launching Canva AI 2.0 in April, but users are creating three times as many designs, offsetting the efficiency gain. The company is eyeing a potential IPO as early as next year, making the margin pressure particularly consequential for investor perception.
Ask the AI about this article →
Canva's revenue growth cut represents a reckoning that is spreading across the software industry as companies confront a fundamental economic shift. For years, the SaaS business model rested on a critical advantage: once built, software could be delivered to millions of users at nearly zero marginal cost, making each additional customer almost pure profit. AI inference—the ongoing computational cost of running an AI model to answer a user request—breaks that assumption. Every time a Canva user asks the AI to generate a design, the company incurs a real, recurring expense that scales directly with usage.
Canva's situation is particularly telling because the company had achieved what few high-growth startups accomplish: sustained rapid growth alongside genuine profitability. The introduction of AI features validated massive user demand, but revealed that Canva's margins could not support the cost structure at scale. Rather than launch unprofitably and hope to improve economics later, Canva chose to slow its rollout—a decision that, as analyst Derek Hernandez notes, reflects concern about investor appetite for a company heading toward an IPO. Figma, Canva's closest public comparable, disclosed similar margin compression: its free-cash-flow margin fell from 27% to 14% in consecutive quarters. Both companies hit the same economic wall within days of each other, suggesting the problem is structural, not company-specific.
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