BAKU, Azerbaijan, August 15. Anthropic is preparing for what could become one of the largest initial public offerings in history, with bankers and investors looking well beyond the company’s current financial performance to assess its potential valuation.
The artificial intelligence company is projecting revenue of roughly $190 billion to $200 billion in 2028, according to two people familiar with its financials. The forecast has not previously been reported.
The projection is dramatically higher than Anthropic’s previously disclosed revenue run rate of about $47 billion, which the company publicized as recently as May. The gap highlights the extraordinary growth expectations investors may be asked to price into the company ahead of a potential IPO.
Four sources said bankers and investors are using enterprise value-to-revenue multiples based on projected future revenue to assess Anthropic’s potential valuation.
Revenue multiples are commonly used to value high-growth software companies that have yet to establish a mature and consistent profit profile. However, looking two years into the future is less common and reflects the exceptional pace at which Anthropic’s business is expanding.
The approach also reflects the difficulty of establishing reliable valuation benchmarks for an AI company that continues to spend heavily on computing capacity, data centres and other infrastructure required to support the rapid expansion of its products.
Anthropic’s projected 2028 revenue would represent a major increase from its current business scale and could become a central factor in determining how investors value the company when it eventually enters public markets.
At the same time, the company’s aggressive investment in AI infrastructure highlights one of the major risks surrounding the sector. Heavy AI spending has contributed to pullbacks in several highly valued technology stocks in recent months, including companies viewed as potential peers of Anthropic.
The company’s expected IPO could therefore become an important test of whether public-market investors are willing to assign exceptionally high valuations to AI firms based largely on future growth expectations.
