Key Points

• Anthropic is reportedly pushing its IPO from October to November 2026. Its advisors say the company wants to present strong third-quarter results before going public.
• Investors expect a valuation of about $2 trillion and a capital raise of up to $100 billion.
• High costs, competition from OpenAI, rising interest rates, and uninsured cybersecurity risks exposed during testing may also explain the delay. OpenAI has already postponed its own IPO to 2027.

Anthropic is reportedly pushing back its planned IPO from October to November 2026.

The company originally targeted October. According to The Information and The Wall Street Journal, the listing is now expected in late October at the earliest but more likely November. Anthropic's advisors say the company wants to present strong third-quarter results before going public.

That explanation doesn't quite add up, assuming its second-quarter results are already strong enough to support an IPO. Strong third-quarter results could also boost the stock after the listing. Investors expect a valuation of roughly $2 trillion and a capital raise of up to $100 billion. Both would break the records SpaceX set in its June IPO.

Revenue more than doubled between the first and second quarters of 2026, rising from about $4.7 billion to more than $11.5 billion, according to The Information. Spending on computing infrastructure only rose 65 percent over the same period, from $3.4 billion to $5.6 billion. Meanwhile, the company's so-called "adjusted operating margin" rose from negative 13 percent in the first quarter to a positive single-digit percentage in the second, though that figure comes with caveats.

Business spending is growing fast, but Anthropic still needs cash

By the end of 2025, about 1,500 companies had each spent more than $100,000 on Anthropic's AI software over the previous 12 months, according to The Information. By the end of the second quarter of 2026, that number had quadrupled to about 6,000. Over that same 12-month window, more than 100 companies each spent over $10 million, while more than 1,000 each spent over $1 million. Anthropic reportedly projects revenue of roughly $190 billion to $200 billion for 2028.

But that money wouldn't go straight into investors' pockets. The IPO would mainly give Anthropic access to debt and equity markets for the years ahead. Despite reporting $120 billion to $130 billion in cash in early August, the company will likely need more funding as data center spending and model training drain its reserves. The computing infrastructure deal it signed with SpaceX in May alone costs $1.25 billion a month.

Competition, costs, and cybersecurity risks complicate the IPO

Several factors could explain the delay, and the answer is probably a combination of them. Anthropic recently claimed to be profitable, but its figures excluded major costs such as stock-based compensation and didn't follow standard accounting rules.

At the same time, OpenAI has regained ground thanks to Astra and pulled ahead on the AI model platform OpenRouter. Both companies need to sustain rapid growth over the coming months to justify their massive data center buildouts. Rising interest rates are making those facilities more expensive to build, while cheaper open-weight models are adding competitive pressure.

Another concern is the safety debate over AI models deemed too dangerous. Their cybersecurity capabilities have already led to "unintended hacks" during safety tests involving OpenAI as well as Google, Anthropic, and Meta. Those incidents suggest substantial operational risks as long as the resulting damage isn't covered by insurance. So far, these incidents haven't been treated as attacks or led to sanctions or lawsuits. They've largely been dismissed as an "AI novelty," but that response is unlikely to hold up once the company goes public and faces greater scrutiny.

OpenAI has also pushed its IPO back to 2027. Sam Altman cited safety concerns, arguing that an AGI company has good reasons to stay private through such sweeping changes. But given the other pressures both companies face, that's only part of the story at best.

The biggest question is still whether all that spending on AI pays off. How much more revenue are companies generating, or how much are they saving, compared with having people do the same work? Those returns remain hard to measure, as we explain in our closer look at AI productivity.