Tech • AI • Robotics • Game
Anthropic vs OpenAI: the IPO war won't happen!
9.4/10TL;DR
OpenAI and Anthropic have delayed planned stock market debuts as mounting losses, governance questions and fears of an AI-driven financial bubble complicate what had been expected to be landmark IPOs.
KEY POINTS
IPO delays raise doubts
Anthropic, developer of Claude, pushed a highly anticipated listing from October to November, while Sam Altman said OpenAI would not go public this year, calling it an inappropriate moment. The shift came after expectations of record-breaking fundraising and valuations, with Anthropic reportedly targeting about $2 trillion and seeking to raise up to $100 billion.
Warnings over AI risk changed the backdrop
The delays followed a series of public alarms from AI researchers and executives. In September, a former OpenAI and Anthropic researcher resigned while accusing leading labs of endangering society, and another alignment specialist publicly suggested existential risk from advanced AI could be significant. Soon after, Anthropic chief Dario Amodei called for the industry to slow down, with Altman later echoing the need for caution.
OpenAI faces scrutiny over losses
Internal projections reported by the Financial Times showed OpenAI could post cumulative losses of $278 billion by 2030. Those figures cast doubt on whether public markets would accept the company’s economics at current private-market valuations, especially as heavy spending on models, data centers and chips continues to outpace revenue growth.
Anthropic wants capital without losing control
On September 25, it emerged that Anthropic’s seven founders, each holding roughly 2% of the company, were open to a flotation only if they could retain more than 50% of voting rights. That structure would let management override short-term market pressure and keep control over safety decisions, even if outside investors owned most of the equity.
Private funding remains an alternative
Both companies still have access to deep private capital, reducing the urgency of an IPO. OpenAI reportedly filed confidentially in June, but fresh private fundraising at valuations above $1.2 trillion could make a public listing unnecessary for now. If private investors remain willing to fund losses, management avoids the disclosure burden and market volatility that come with a listing.
China and open models are pressuring business models
A major concern is the rapid rise of cheaper open-weight and Chinese AI models. Usage appears to have shifted sharply in recent months, with open models accounting for the majority of tokens consumed, up from a minority share earlier in the year. Even if frontier closed models still capture most spending, the trend suggests that premium pricing power could weaken quickly.
The real money may be moving to infrastructure
Investors increasingly see the strongest economics in compute, power and data centers rather than in the models themselves. The analogy is a modern gold rush in which the biggest winners may be the sellers of picks and shovels: Nvidia, foundries, cloud providers and power infrastructure. That shift undermines the original investment case for model makers that expected to dominate the value chain.
Debt markets are becoming part of the story
The scale of AI infrastructure spending has become macroeconomically significant. Estimates discussed by market participants put AI-related data center investment at as much as $10.3 trillion between 2025 and 2033, or around 3.6% of GDP annually. That spending is increasingly financed not only by equity but by debt, making AI projects competitors for capital that might otherwise fund US Treasury borrowing.
A bubble risk is seen as financial, not technological
Demand for AI services remains strong, and revenue growth at top labs is unusually fast by historical standards. The concern is not that the technology lacks users, but that the financing structure could crack if one major player fails to meet expectations. In that scenario, a default or sharp repricing could hit suppliers, private investors and eventually public markets, turning an AI boom into a broader financial shock.
Public markets may force a strategic rethink
Going public would expose the labs to quarterly earnings pressure just as they are debating existential-risk safeguards and long-term research spending. That tension helps explain why management teams may prefer to wait, especially if they expect to monetize AI through vertical products in healthcare, defense, finance or proprietary intellectual property rather than through token sales alone.
CONCLUSION
The postponed IPOs reflect more than timing. They show that the AI leaders are still trying to prove that frontier models can become durable businesses without surrendering control, safety priorities or financial stability.
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