After nearly a quarter century operating as a private company, with its financial accounts a closely guarded secret, SpaceX on Wednesday afternoon released a detailed accounting of its business in a nearly 400-page report. S-1 Filing with the U.S. Securities and Exchange Commission.
SpaceX, founded in 2002 and still led by Elon Musk, filed in anticipation of an initial public offering of its shares on June 12.
The document revealed no major surprises about the company’s space operations, but it did reveal a wealth of details about its expanding operations, which now encompass launches, spaceflight, space internet, and, thanks to its recent acquisition of Musk’s xAI, social media and artificial intelligence.
The company reported revenue of $18.67 billion in 2025, up significantly from $14.02 billion a year earlier. However, after making a small profit in 2024, the company lost $4.94 billion in 2025, largely due to spending on AI development.
That’s a big market you have there.
SpaceX projects a “total addressable market,” or TAM, of $28.5 trillion across its current and future offerings in space, data and artificial intelligence services. However, of this amount, only about $2 billion is directly related to space or the company’s Starlink network. The remaining $26.5 trillion is believed to come from AI, largely from enterprise applications.
SpaceX estimate of total addressable market.
Credit: SpaceX S-1 Filing
SpaceX estimate of total addressable market.
Credit: SpaceX S-1 Filing
“We believe we have identified the largest TAM in human history,” the company states on page 171 of the document. “We believe our next trillion-dollar market is AI computing, which we envision will leverage our rockets and satellites for massive orbital deployment.”
The company said its estimates for this large market were based on several sources.
“Our AI market estimates are based in part on projections of global data center computing demand from third-party sources, including estimates published by the RAND Corporation, along with internal assumptions about the portion of global computing capacity that can be used for AI workloads and other operational assumptions such as power usage, utilization rates, and pricing,” the document states.
