Per new Stanford research, of all US-based VC-backed unicorns that have exited, only 33 achieved decacorn status at exit.
Not at paper, but on exit.
With 1,200+ unicorns still waiting for an exit, will there be enough $10B+ exits? Figma is about to IPO, we had Wiz, and Zuck is on a tear buying Scale.ai and more.
But we need a lot of decacorns and bigger to make the unicorn bets pay off.
Stanford Professor Ilya Strebulaev’s latest research reveals that for US-based VC-backed unicorns that have exited, the largest concentration is in the $1-2 billion valuation range, with 306 unicorns exiting at these levels.
306 have exited at $1-2 Billion. Only 33 at $10B … so far.
The exit funnel breakdown from Stanford’s data:
- Sub-$1B exits: 113 unicorns (58 IPOs + 27 reverse mergers + 28 acquisitions), including some that went bankrupt with minimal value
- $1-2B range: 306 unicorns (126 IPOs + 33 reverse mergers + 147 acquisitions)—the largest concentration
- $2-3B range: 93 unicorns (45 IPOs + 17 reverse mergers + 31 acquisitions)
- $10B+ decacorn territory: Only 33 unicorns (29 IPOs + 1 SPAC + 3 acquisitions), including Palantir Technologies and Meta
IPOs dominate the mega-exits, representing 88% of decacorn outcomes, while IPOs consistently represent the largest share across all valuation ranges, followed by acquisitions, then reverse mergers.
And despite achieving billion-dollar post-money valuations, most unicorns don’t dramatically exceed their unicorn threshold by exit time. The concentration in the $1-2 billion range suggests that many companies struggle to maintain momentum beyond their initial unicorn valuation.
The Math Behind the Bottleneck
Stanford’s data provides the clearest picture yet of the unicorn exit landscape. Of the 545 total US-based VC-backed unicorn exits analyzed:
- 55% exit in the $1-2B range (306 companies)
- 17% exit in the $2-3B range (93 companies)
- 21% exit below $1B (113 companies)
- Only 6% achieve decacorn status (33 companies)
The “unicorn premium”—the expectation that reaching $1B valuation guarantees outsized returns—is largely a myth. The majority of unicorns exit close to their initial unicorn threshold.
What Separates Future Decacorns
The companies that will break through the $10 billion barrier share specific characteristics that go far beyond traditional SaaS metrics:
Scale Requirements True decacorn candidates operate with 500-2000+ employees and demonstrate the ability to scale operations across multiple geographies and market segments. They’re not just growing revenue—they’re building sustainable competitive moats.
Revenue Velocity Canva, which is now valued at $40 billion, added $157 million in value daily since its prior funding in April 2021. These aren’t incremental growth stories—they’re companies experiencing parabolic expansion in massive markets.
Market Timing and Category Creation The current decacorn landscape is dominated by companies that didn’t just enter existing markets—they created entirely new categories. From fintech startups like Stripe and Revolut to AI leaders like OpenAI, these companies represent the pinnacle of startup success.
The New Exit Math
The traditional venture capital power law is becoming even more extreme. Stanford’s data confirms this concentration: only 33 companies have achieved decacorn exits, representing just 6% of all unicorn exits but likely driving a disproportionate share of venture returns.
The reality check for VCs:
- Only 6% of unicorn exits achieve decacorn status ($10B+)
- 88% of decacorn exits happen through IPOs, not acquisitions
- 55% of unicorns exit in the narrow $1-2B range, suggesting limited value creation beyond initial unicorn status
- 40% of US unicorns have been held in portfolios for at least nine years, and that group accounts for more than $1 trillion in value
Will AI Change the Math? (That’s The Bet We’re All Making, At Least)
The emergence of artificial intelligence as a dominant force in venture capital is fundamentally altering the unicorn-to-decacorn trajectory in ways that Stanford’s historical data couldn’t have predicted. Early 2025 marked the highest VC investment in AI on record, with global AI-related deals totaling $73.1 billion, accounting for 57.9% of all VC-backed funding. This isn’t just a trend—it’s a seismic shift that may rewrite the rules of startup valuations.
The AI Unicorn Speed Run
Traditional startups take an average of 7 years to reach unicorn status. AI companies are obliterating this timeline, achieving billion-dollar valuations in an average of 3.9 years—and some are moving even faster. Consider these acceleration case studies:
- Cognition AI: Reached $2 billion valuation in just 5 months after founding in November 2023, becoming “the world’s first fully autonomous AI software engineer”
- xAI: Elon Musk’s AI venture achieved a $24 billion valuation in under 10 months, breaking records for rapid value creation
- Scale.AI IP purchased by Meta for $14B+
- Anthropic: Founded by former OpenAI employees in early 2021, reached unicorn status in 19-25 months and is now valued at multiple billions
- Safe Superintelligence: Founded in 2024 by OpenAI co-founder Ilya Sutskever, raised $1 billion at a $5 billion valuation in its first year
- Character.ai: Reached $1 billion valuation in March 2024 with a $150 million Series A led by Andreessen Horowitz, founded by former Google AI researchers
- Adept AI: Achieved unicorn status in March 2024 with a $350 million Series B at over $1 billion valuation, focusing on AI that can use software tools
- Mistral AI: Paris-based foundation model company reached $2 billion valuation with $415 million Series A in just one year, led by Andreessen Horowitz
- Perplexity AI: The AI-powered search engine reached $14 billion status in record time, challenging Google’s search dominance with conversational AI
- Groq: AI inference chip company achieved $1 billion+ valuation after Tiger Global co-led $300 million round, revolutionizing AI processing speed
- Harvey: Legal AI platform raised $100 million from Google Ventures, OpenAI, and Sequoia at $5 billion valuation, transforming legal workflows
- Cohere: Toronto-based enterprise AI company reached multi-billion valuation, competing directly with OpenAI in the enterprise market
- Inflection AI: Founded by DeepMind co-founder, achieved $4 billion valuation before being acquired by Microsoft for talent and technology
The OpenAI Effect: Redefining Mega-Valuations
OpenAI’s trajectory is simply s a new paradigm. The company saw the fastest valuation increase globally, adding $80 billion in value to reach $100 billion, before eventually reaching $300 billion—making it the world’s most valuable AI startup and the third most valuable unicorn globally, after ByteDance and SpaceX. This $40 billion private funding deal led by SoftBank broke the record for the largest private tech investment of all time.
AI unicorns may not follow traditional scaling patterns. They aren’t right now. Instead of the typical unicorn-to-decacorn bottleneck, leading AI companies appear capable of jumping directly to super-decacorn status ($50B+) or even hectocorn territory ($100B+).
AI Unicorn Creation Acceleration
The data reveals AI’s disproportionate impact on unicorn creation:
- 48% of new 2025 unicorns are AI companies (11 out of 23 in Q1 2025) – showing acceleration from 44% in 2024
- AI now represents 25% of all global unicorns, and going way up – meaning 1 in 4 unicorns is an AI company
This concentration suggests that AI isn’t just creating more unicorns—it’s creating a fundamentally different class of unicorns with accelerated growth trajectories and potentially higher ceiling valuations.
The Billion-Dollar Question: Will AI Unicorns Follow Traditional Exit Patterns?
Stanford’s research shows that only 6% of traditional unicorns achieve decacorn status at exit. But AI companies are demonstrating characteristics that could dramatically alter this percentage:
- Massive Market Opportunity: AI represents a multi-trillion-dollar market transformation affecting every industry
- Winner-Take-Most Dynamics: Network effects and data advantages create natural monopolies
- Capital Intensity: Leading AI companies require billions in infrastructure investment, supporting higher valuations
- Enterprise Adoption: Corporate AI spending is accelerating, providing sustainable revenue streams
The New Aristocracy
Several AI and AI enhanced companies are already operating at scales that suggest they’ll bypass traditional unicorn exit patterns entirely:
- ByteDance (TikTok’s parent): $220 billion valuation, the world’s most valuable unicorn
- OpenAI: $300 billion valuation after record-breaking funding
- Anthropic: Multi-billion valuation with $3.5 billion funding round led by Lightspeed
- Stripe (AI-enhanced payments): $65 billion valuation
- Databricks (AI/ML platform): $43 billion valuation
Potential Decacorn Exits: The IPO Pipeline
Based on current valuations, revenue metrics, and market positioning, here are the companies most likely to achieve decacorn status ($10B+) at exit. Figma will almost be there or already there when you read this.
Looking Forward: The 2025 Landscape
The AI revolution is reshaping not just how we think about unicorn creation, but potentially the entire venture capital return model. Pitchbook’s base case scenario for 2025 is 12 unicorn IPOs—with an exit value of around $70.5 billion. But here’s the crucial question: how many of these will be AI companies, and will they achieve post-IPO valuations that justify their unicorn premiums?
The market is becoming increasingly discriminating. While many investors expect more unicorn exits in 2025, valuations are likely to be lower than previous years as the market shifts toward more realistic pricing and stricter evaluation criteria.
Key trends shaping the decacorn pipeline:
- AI Infrastructure and Applications: Companies building fundamental AI infrastructure and transformative applications are achieving unprecedented valuations
- Global Market Leaders: Businesses that can demonstrate true international scale and market dominance, particularly in AI-enabled sectors
- Capital-Efficient AI Models: Despite massive infrastructure investments, some AI companies are achieving billion-dollar valuations with relatively modest funding rounds
- Enterprise AI Adoption: The rapid corporate adoption of AI solutions is creating sustainable revenue streams that support higher valuations
The Bottom Line
Stanford’s research answers the traditional question definitively: based on historical data, there won’t be enough decacorns to satisfy the current unicorn population. With only 33 companies achieving decacorn status at exit out of 545 total unicorn exits—a mere 6%—the mathematics were unforgiving.
But AI may be rewriting this equation entirely. If AI companies can maintain their demonstrated ability to achieve 3.9-year paths to unicorn status, command premium valuations, and scale to massive market opportunities, they could represent the first systematic exception to Stanford’s 6% rule.
The question isn’t whether there will be enough decacorns under traditional models—it’s whether AI will create an entirely new category of super-scaled companies that bypass traditional growth limitations. For the 57.9% of venture funding flowing into AI, the stakes have never been higher.
For founders, the message is nuanced: building a traditional unicorn is no longer the ultimate goal—as crazy as it sounds, it may be table stakes. But for AI founders, the rules may be fundamentally different. In 2025 and beyond, the companies that matter will likely split into two categories: the rare 6% of traditional unicorns that navigate the treacherous path to decacorn status, and a new class of AI-native companies that may achieve decacorn status at rates 5-10x higher than historical averages.
The bottleneck is real for traditional companies, the competition is fierce, and Stanford’s data shows the stakes have never been higher. But for AI companies riding the $73.1 billion wave of 2025 funding, the math might be entirely different. Whether this optimism proves justified will determine if we’re witnessing a temporary AI bubble or a fundamental restructuring of how exceptional companies scale in the digital age.
Analysis based on research by Professor Ilya Strebulaev at Stanford University Graduate School of Business Venture Capital Initiative, with additional data from PitchBook, CB Insights, and Crunchbase.
