"Venture capital poured a record $202 billion into AI startups in 2025, capturing half of all global funding. Yet the math remains brutal: 90% of AI companies will fail, a rate significantly higher than the 70% seen in traditional tech startups. According to Alexander Kopylkov, a venture capital investor focused on long-term business fundamentals, this failure rate is not driven by lack of innovation, but by broken unit economics. "Everyone can build a demo," he notes. "The survivors are the ones who can build a business.""
"Many AI startups at Series A are burning $2 to $5 for every $1 of new revenue. This burn multiple, a metric popularized by investor David Sacks, has become the defining number VCs scrutinize in 2026. For context, top-performing SaaS companies operate at burn multiples below 1.5x. The gold standard is 1x or below: spend a dollar, earn a dollar."
Venture capital poured a record $202 billion into AI startups in 2025, capturing half of global funding. Ninety percent of AI companies are projected to fail, higher than the 70% failure rate for traditional tech startups. The primary cause is broken unit economics rather than lack of innovation. Many Series A startups burn $2 to $5 for every $1 of new revenue, pushing burn multiples that VCs now scrutinize. AI companies often spend 40–50% of revenue on infrastructure versus 15–20% for SaaS, and face higher talent costs, constant retraining, and costly data pipelines. Companies that achieve sub-1.5x burn multiples emphasize disciplined hiring, product-market fit before scaling, AI-enhanced efficiency, and enterprise customers.
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