Goldman Sachs predicts Anthropic's annual revenue will soar to $685 billion in 2030 to support the $1.4 trillion IPO valuation

The Zhitong Finance App learned that according to people familiar with the matter, Goldman Sachs's research team predicts that the annual revenue of artificial intelligence (AI) startup Anthropic will soar to about US$685 billion in 2030, an increase of nearly 150 times over US$4.59 billion in 2025. This aggressive growth forecast supports the approximately $1.4 trillion valuation that Anthropic is seeking in its upcoming initial public offering (IPO).

People familiar with the matter said that according to predictions disclosed by Goldman Sachs's research team in an oral briefing, Anthropic's annual revenue from corporate customers is expected to reach 586 billion US dollars by 2030, while revenue from non-corporate customers is expected to reach about 100 billion US dollars. This means that corporate customers will contribute about 85% of the company's revenue at that time, and will be the main driving force for its business expansion.

Anthropic is currently promoting an IPO that has received much attention in the market. The underwriting bank plans to hold a meeting with potential investors on Tuesday morning to promote the offering. Including a $26 billion private placement, the IPO-related financing target reached US$90.4 billion.

According to media calculations, Anthropic is seeking a fully diluted valuation of around $1.4 trillion in this release. According to the terms of the transaction, the company is expected to determine the release price on November 18 (Wednesday) and officially start trading the next day.

Goldman Sachs's predictions reflect Wall Street's high expectations for the commercialization potential of AI technology. The core logic behind this valuation is that AI is expected to profoundly change the way many professional fields work, and Anthropic's Claude series products may occupy an important market share in this transformation process.

Currently, AI programming tools such as Anthropic's Claude Code have been widely used in the field of software development, but the market believes this may only be the starting point of the AI commercialization wave. In the future, the scope of application of AI technology is expected to be further expanded to fields such as new drug research and development, complex legal and accounting transaction processing, and manufacturing automation, thereby creating new revenue streams for Anthropic.

However, although Goldman Sachs is highly optimistic about Anthropic's future revenue growth, the forecast is that due to the huge investment required to build AI infrastructure, the company may not achieve positive free cash flow throughout the year until 2030.

People familiar with the matter revealed that the Goldman Sachs research team expects Anthropic's computing infrastructure spending to increase more than tenfold by 2030 to reach a scale of nearly 400 billion US dollars. However, the bank also anticipates that profits from the company's computing business will also increase by a similar margin.

This means that although Anthropic is expected to see explosive revenue growth in the next few years, the continued expansion of computing power demand and infrastructure investment will still put tremendous pressure on its cash flow. How to rapidly expand market share and improve profitability will be an important factor for investors to evaluate the company's long-term value.

As Anthropic's listing enters the final stage, investors are facing a critical judgment, whether the current high valuation of AI companies reflects the huge economic value that the technological revolution may bring, or is based on long-term growth expectations that have not yet been fully verified.

In particular, as Anthropic is seeking a valuation of up to $1.4 trillion, Goldman Sachs's forecast for 2030 revenue to reach $685 billion further highlights the market's optimism about AI commercialization prospects. However, at the same time, huge capital expenditure, the late timing of free cash flow, and whether AI technology can actually penetrate more industries also mean that there is still great uncertainty about this growth prospects.