The Core Projection
In a series of recent reports, strategists at Goldman Sachs have outlined a forecast where the broader stock market's performance is increasingly tied to the pipeline of AI companies going public. The bank anticipates that US companies could raise around
$175 billion through IPOs in 2027 alone, with a significant portion driven by the capital-intensive AI sector. This follows a record-breaking year for equity issuance in 2026. The projection isn't just about the volume of new listings; it's about their significance. Goldman estimates that AI-related capital spending currently accounts for roughly half of the S&P 500's earnings growth, highlighting how central the technology has become to corporate profitability. As this spending matures, the next logical step is for the valuable private companies fueling this boom to enter the public markets, providing a fresh injection of growth.
Why AI is the New Market Bellwether
For the past few years, market gains have been famously concentrated in a handful of mega-cap technology stocks. While profitable, this narrow leadership has created concerns about the market's overall health. According to Goldman's analysis, a wave of major AI IPOs could help broaden the market, diversifying the sources of growth beyond the incumbent giants. The capital required to build out AI infrastructure is immense, driving companies to seek public funding. This demand for capital is so strong that the average IPO size in 2026 has surged, reflecting investor confidence and the high valuations of these tech firms. The emergence of these new, high-growth public companies is seen as essential for sustaining the bull market, providing new opportunities for investors and signaling a healthy appetite for risk and innovation.
A Potential Thaw in the IPO Freeze
The IPO market has been relatively subdued for several years, but the sheer scale of the AI opportunity appears to be changing that. Historical data shows that IPO activity rises when macroeconomic fundamentals are strong and equity markets are performing well. The current surge in expected AI listings reflects this renewed confidence. Even in India, Goldman Sachs projects that a wave of AI-led IPOs could add between $50 billion and $100 billion to the country's market capitalisation over the next two to five years. This suggests a global trend where AI is not just a dominant technological force but also a key driver of capital markets activity, capable of reopening the IPO window for a new generation of companies.
The AI Contenders to Watch
The speculation is centered on several high-profile, private AI companies that have achieved massive valuations. Names like Anthropic and OpenAI are at the top of the list, with both having reportedly filed confidential paperwork for public listings. Anthropic, the company behind the AI model Claude, has been in discussions for a fundraising round that could value it at nearly $900 billion, with a potential IPO as early as October 2026. OpenAI, creator of ChatGPT, is also preparing for a mega-listing. Other major players in the pipeline include Databricks, a profitable enterprise AI platform, and Cerebras Systems, which designs AI supercomputers and recently priced its IPO. The combined value of the top dozen AI firms nearing public offering is estimated to be over $3 trillion, indicating the monumental scale of the anticipated listings.
Risks and Market Realities
Despite the optimism, Goldman Sachs and other market observers point to significant risks. The sheer volume of new shares from IPOs and expiring lockup periods could create a supply glut that pressures stock prices. Furthermore, Goldman strategists have warned that the market's leadership is currently extremely narrow, a situation that can lead to volatility and sharp reversals in momentum trades. There is also the risk of an 'AI bubble', where valuations become detached from underlying profitability. The immense capital required by these firms has led to heavy debt loads for some, and rising interest rates could make servicing that debt more challenging, as seen in recent volatility among AI-linked stocks. Successful execution will depend on whether corporate earnings can remain strong enough to absorb the new supply of stock and justify the high valuations.
