The preparation of major AI startups for public capital markets is taking place amid the intensifying competition for both investment and sustainable business models. The Anthropic IPO, expected in October 2026, aims for a potential raise of over $60 billion, positioning it as one of the largest debuts in tech history. The company focuses on the corporate segment and has a more transparent monetization model than OpenAI, which is also anticipated to appear on the IPO calendar this year, making the developer of Claude more attractive to investors. However, the industry’s capital-intensive nature remains clear: a significant portion of previously raised funds, including approximately $30 billion, is already allocated for infrastructure development and data center construction in particular, further heightening the pressure for future profitability.
At the same time, the planned IPO faces substantial regulatory risks. A recent federal court ruling, blocking Pentagon restrictions on the company, temporarily alleviates the pressure but does not eliminate the uncertainty. Potential appeals and ongoing disputes with government agencies continue to threaten access to federal contracts — a critical revenue stream. As a result, the legal environment becomes a factor that directly affects both the company’s valuation and investor appetite.
A broader context for AI companies’ valuations is also being shaped by the state of related industries — most notably the memory market. Recent technological initiatives, such as Google’s TurboQuant compression method, are already influencing investor expectations regarding infrastructure demand. The sharp decline in share prices for SK hynix, Samsung Electronics, and Micron Technology following the announcement of the new technology highlights the market’s sensitivity to any signals that could disrupt the balance of supply and demand. While long-term fundamentals such as memory shortage and rising prices remain intact, this reaction underscores how heavily AI sector valuations depend on expectations around infrastructure costs.
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