The venture capital benchmark for elite growth has shifted for AI companies. The old "T2D3" (Triple, Triple, Double, Double, Double) heuristic for SaaS is no longer the gold standard. Investors now consider achieving $100M ARR in under three years as the strongest signal of exceptional product-market fit in AI.

OpenAI's revenue projection of growing from $10 billion to $100 billion in three years is historically unprecedented. For comparison, it took established tech giants like NVIDIA, Meta, and Google between six to ten years to achieve the same growth milestone, highlighting the extreme velocity expected in the AI market.

The time for a new company to challenge an incumbent has compressed dramatically. As private market timelines extend, many unicorns that haven't gone public are already being 'eaten away' by the next wave of startups, creating a significant liquidity challenge for their late-stage investors.

For high-growth companies, reaching a $100M ARR milestone no longer automatically triggers IPO plans. With abundant private capital, many founders now see going public as an unnecessary burden, preferring to avoid SEC reporting and gain liquidity through private growth rounds.

AI companies raise subsequent rounds so quickly that little is de-risked between seed and Series B, yet valuations skyrocket. This dynamic forces large funds, which traditionally wait for traction, to compete at the earliest inception stage to secure a stake before prices become untenable for the risk involved.

AI isn't just an efficiency tool; it fundamentally accelerates core business growth. A portfolio company achieved a 4.5x markup in 9 months by reaching $10M ARR in 14 months. This speed, which cuts the traditional 18-24 month timeline in half, is redefining early-stage venture capital benchmarks.

The enormous private capital available to AI leaders, shown by Anthropic's $10B and xAI's $20B rounds, reduces the urgency to go public. This nearly unlimited appetite from private markets allows these companies to continue their aggressive growth and infrastructure build-outs without the regulatory scrutiny and quarterly pressures of being a public company.

The CEO of Numeral notes that in the current fundraising climate, startups must heavily feature AI in their pitch to secure investor meetings. Furthermore, landing a major AI lab as a customer has become a key signal for VCs, leading to valuation multiples as high as 100-200x revenue for some companies.

AI startups' explosive growth ($1M to $100M ARR in 2 years) will make venture's power law even more extreme. LPs may need a new evaluation model, underwriting VCs across "bundles of three funds" where they expect two modest performers (e.g., 1.5x) and one massive outlier (10x) to drive overall returns.