AI

Anthropic Files for IPO as Amodei Defends AI Spending Against Skepticism

Modern corporate lobby of Anthropic headquarters in San Francisco

Anthropic, the artificial intelligence company behind the Claude model family, has taken a significant step toward going public by filing confidentially for an initial public offering, the company confirmed this week. The move comes as co-founder Daniela Amodei, speaking Thursday at the Bloomberg Tech conference, addressed mounting questions about whether the massive capital expenditures required to train frontier AI models will ever deliver commensurate returns.

“It’s a really big upfront cost to train the models and to serve inference on them,” Amodei said. “My guess is that over time, the sort of core set of companies that are working to advance the frontier are just going to need access to capital, and I think the public market is very well suited to that.”

Also read: GitLab lays off 14% of staff as it rebuilds platform for AI workloads

A $65 Billion Fundraise and a Valuation Question

Anthropic announced last week that it had raised $65 billion at a $965 billion valuation, a figure multiple investors told TechCrunch was heavily oversubscribed — meaning demand for the deal far exceeded the supply of shares on offer. The company’s annualized revenue crossed $47 billion in May, up from roughly $9 billion at the end of 2025, a trajectory that has made it one of the fastest-growing private technology companies in history.

That growth rate, however, faces a real test. Companies including Uber have publicly stated that while AI can deliver returns, not all of their spending on the technology has proven productive. That raises the prospect that corporate AI budgets could face more scrutiny, potentially slowing growth across the sector.

Also read: ZeroDrift raises $10M to build AI guardrails that keep large language models compliant

Amodei dismissed the idea that such skepticism should worry Anthropic. “The use cases today, I expect will continue to be the primary driver of efficiency or creativity, whether that’s coding, financial services, legal, [or] health care,” she said. “But as the business community gets more familiar with the tools, we’re all going to learn together. My hope is that over time it’ll be more incorporated into the day-to-day of how humans do our work, and there will actually be a lot more value realized.”

Why Anthropic Isn’t Building Its Own Data Centers

Unlike rivals such as OpenAI and Elon Musk’s xAI, Anthropic has avoided building its own data centers to meet its growing compute needs. Amodei explained the reasoning directly. “Anthropic’s view has always been wanting to plan for the best outcome but not overextend ourselves such that we’re buying more compute than we could productively use,” she said. “It’s really hard to predict that perfectly. We would much prefer to be on the side of having a little bit more demand for the product than we’re able to serve than the inverse.”

Last month, the company surprised the AI industry by partnering with xAI for compute capacity. A deal later disclosed in SpaceX’s S-1 filing revealed that the arrangement costs Anthropic $1.25 billion per month, underscoring the immense infrastructure demands of frontier AI development.

The confidential IPO filing signals that Anthropic’s leadership believes the company’s revenue growth and market position are strong enough to withstand the scrutiny of public markets. Whether investors will share that confidence — especially given the broader questions about AI spending efficiency — will be one of the most closely watched narratives in the tech IPO pipeline.

Neelima Kumar

Written by

Neelima Kumar

Neelima Kumar is a technology and AI reporter at StockPil who covers artificial intelligence trends, enterprise software, and the intersection of technology with financial markets. She has spent seven years tracking how emerging technologies reshape industries and create investment opportunities. Neelima previously reported on tech for VentureBeat and Wired, and her analysis has been featured in MIT Technology Review.

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