That’s according to a report Monday (Sept. 28) from Reuters, which had gotten a look at the artificial intelligence (AI) startup’s initial public offering (IPO) plans.
The prospectus outlines a costly path to Anthropic’s vision. The company reported a $42 billion net loss last year, and projects $518 billion in spending on cloud, computing and infrastructure needs in the years ahead.
The prospectus shows sharp growth for Anthropic in the past year, along with wider losses. The company’s revenue came to nearly $4.6 billion, a 12-fold increase, while it lost more than $8 billion on an operating basis, not counting writedowns of various liabilities mostly related to past fundraising, the Reuters report said.
Anthropic said close to 25% of its revenue last year came from two customers. As part of its risk factors, the company cautioned that many of its biggest clients had not signed long-term contracts and could reduce or cease spending.
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Reuters notes that the company’s IPO, which could value Anthropic at more than $2 trillion, would leverage the rapid rise of the five-year old AI lab while cementing it as a benchmark for how Wall Street values AI firms, OpenAI included.
The IPO is scheduled to happen after the November midterm elections, according to earlier media reports. OpenAI is not expected to list until 2027 at the earliest.
The plans are also happening as Anthropic and other companies deal with evidence that more powerful AI models can behave in harmful ways, whether that means helping carry out fraud or sabotaging code, the report added.
Anthropic CEO Dario Amodei has called for the AI industry to slow the pace of new model rollouts in response to these concerns, the report said. However, the company last week debuted its Opus 5.5 model, following OpenAI’s launch of GPT-6 Astra.
In other AI news, recent research by PYMNTS Intelligence shows that 62% of surveyed enterprises — companies with $1 billion in revenue interviewed in July — spent more than $10 million on new AI tools in the last year. Companies with deeper deployment saw more obstacles, such as skill gaps and unclear responsibility for the technology.
“Earlier experience may help. Among firms that had embedded older forms of AI in at least two functions before 2022, 47% have now embedded newer AI in three or more,” the report said.
“The survey offered a snapshot rather than a history of each company, but it pointed to a practical opportunity. Firms can build on the processes they’ve already developed as they bring AI further into everyday work.”
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