OpenAI and Anthropic have together raised $187 billion in funding in just a few months, while simultaneously preparing for stock market listings. Their IPO prospectuses are expected to expose what private valuations and annualized revenue figures can still obscure: the true cost of compute, the quality of the business model, and the gap between headline growth and underlying economics.
The central issue is that both companies have so far benefited from the opacity of private markets, where soaring valuations can coexist with limited disclosure. Once they move toward an IPO, they will have to publish far more detailed financial information, including the scale of their infrastructure spending, the economics of training and running large AI models, and the sustainability of their revenue growth.
For the AI sector, this would mark a turning point. OpenAI and Anthropic have become the emblematic players of the generative AI boom, attracting extraordinary amounts of capital in a very short time. But public-market scrutiny will force investors to confront the real cost structure behind the technology: massive compute bills, heavy dependence on cloud infrastructure, and the challenge of converting rapid adoption into durable profitability.
In other words, the IPO process may reveal whether the current AI frenzy is supported by solid unit economics or by expectations that remain largely untested. The prospectuses will not just be a financing milestone; they will be the first real accounting of what it costs to build frontier AI at scale.