AI Startups Selling Equity at Dual Prices: The Unicorn Trick

Introduction

The artificial intelligence startup ecosystem is witnessing a concerning trend that challenges traditional valuation methodologies. According to recent reporting from TechCrunch, some AI founders are employing a novel mechanism to artificially inflate their company's valuation—selling the same equity at two different prices simultaneously. This practice raises serious questions about transparency, investor protection, and the integrity of the startup funding ecosystem.

As the AI industry continues to attract record-breaking investments, with venture capital flowing into the sector at unprecedented rates, the temptation for startups to manipulate their perceived value has grown correspondingly. Understanding this mechanism is crucial for investors, regulators, and industry observers who seek to navigate the complex landscape of AI startup financing.

Understanding the Dual-Price Equity Mechanism

The mechanism at the heart of this controversy involves startups issuing shares to different investors at varying prices within the same funding round or across closely timed rounds. Traditionally, a funding round establishes a single price per share that applies to all investors participating in that round, creating a clear and verifiable valuation.

However, some AI startups have begun structuring deals where new investors receive shares at a higher price point—often deliberately set to achieve a unicorn valuation (>$1 billion)—while existing investors or certain preferred investors maintain their equity position at significantly lower prices. This creates a bifurcated capital structure where the same company appears to have different values depending on which shares one examines.

This approach effectively allows startups to claim a public unicorn valuation based on the highest price paid, while the actual fair market value—as reflected by the lower-priced transactions—may be substantially different. The discrepancy between these two values can be dramatic, with some analysts suggesting gaps of 30-50% or more between claimed and actual valuation.

Why AI Startups Are Adopting This Strategy

Several factors are driving the adoption of this valuation mechanism within the AI startup space:

• Market Pressure: The AI sector has seen extraordinary valuation multiples, with investors FOMO (fear of missing out) driving them to pay premium prices for access to promising companies. Startups leverage this pressure to negotiate higher prices from new entrants.
• Status and Credibility: Unicorn status carries significant weight in the technology industry, attracting talent, media attention, and follow-on investment. The title of "unicorn" has become a self-fulfilling prophecy in many cases.
• Competitive Positioning: In a crowded AI market, startups compete not just for funding but for visibility. Claiming a billion-dollar valuation provides marketing advantages and differentiates a company from competitors.
• Down Round Avoidance: By manipulating valuation through dual pricing, startups can avoid the stigma and practical challenges of conducting a down round (raising at a lower valuation than previous rounds).

The Implications for Investors and the Ecosystem

This practice introduces significant risks for the startup ecosystem. Investors purchasing shares at the higher valuation may find themselves with positions that are overvalued relative to the company's true fundamentals. When market realities eventually assert themselves, these investors could face substantial losses.

Furthermore, the practice undermines the reliability of valuation metrics that the venture capital industry has traditionally relied upon. If reported valuations can be artificially constructed rather than organically achieved through market forces, the entire framework for assessing startup worth becomes questionable.

Regulatory scrutiny may also increase as authorities examine whether this practice constitutes securities fraud or misleading marketing. The Securities and Exchange Commission (SEC) has historically taken action against companies that misrepresent their financial condition, and artificially inflated valuations could fall within their purview.

Expert Analysis and Industry Response

Industry experts have offered mixed reactions to this emerging practice. Some argue that dual-pricing represents a sophisticated financial engineering approach that, while unconventional, does not necessarily constitute wrongdoing. Others contend that it represents a fundamental breach of trust between founders and investors.

The practice of selling equity at multiple price points within the same corporate structure raises serious questions about fiduciary duty and investor protection. Founders have an obligation to provide accurate information to all shareholders, and manipulating valuation metrics potentially violates that duty.

Major venture capital firms have begun implementing more rigorous due diligence processes, including detailed examination of share issuance history and capital structure analysis. Some investors are now requiring comprehensive disclosure of all transactions, including those involving existing shareholders or related parties.

The Path Forward

As the AI industry continues its rapid evolution, the need for transparent and honest valuation practices becomes increasingly critical. Startups that succeed in the long term will likely be those that build genuine value through technical innovation and sustainable business models, rather than those that rely on accounting tricks to manufacture artificial growth.

For investors, the lesson is clear: conduct thorough due diligence, question reported valuations, and demand full transparency regarding capital structure. The era of taking startup valuations at face value may be coming to an end.

Conclusion

The practice of AI startups selling equity at dual prices represents a troubling development in the venture capital ecosystem. While the immediate impact may be inflated valuations and manufactured unicorn status, the long-term consequences could include diminished investor trust, regulatory intervention, and a correction in how the market values AI companies. As the industry matures, stakeholders must work together to establish clearer standards and ensure that valuation practices align with genuine economic value creation.