Goldman Sachs has issued a projection that SpaceX’s artificial intelligence revenue could reach $322 billion by 2030. The bank says that growth is expected to lift the company’s valuation when it eventually goes public.
A $322 Billion Revenue Bet
The figure from Goldman Sachs covers SpaceX’s AI-related income over the next seven years. The projection suggests a massive scaling of revenue tied to artificial intelligence, but the bank did not detail which specific AI products or services would generate the bulk of that money. SpaceX operates Starlink satellite internet and develops rockets and spacecraft; AI plays a role in autonomous operations and data processing across those businesses. The $322 billion target implies annual AI revenue of roughly $46 billion by the end of the decade, though the projection likely includes compound growth from multiple lines.
IPO Valuation Lift
Goldman Sachs noted that the expected AI revenue growth would boost SpaceX’s valuation ahead of an initial public offering. The company has long been considered a candidate for one of the largest IPOs in history, but founder Elon Musk has not set a firm timeline. The projection gives potential investors a specific revenue anchor tied to AI, a sector that has drawn heavy market interest. A higher valuation would mean SpaceX could raise more capital per share, or that early investors and employees could see greater returns when shares begin trading publicly.
SpaceX has not commented on the Goldman Sachs report. The company remains private, and its current valuation is estimated at roughly $180 billion based on secondary share sales. The AI revenue projection, if realized, would more than double that figure by 2030.
What Comes Next
The IPO date is not set, and the revenue projection from Goldman Sachs is just one forecast. Investors will watch for SpaceX to release its own financial data or for Musk to signal when a public listing might come. The $322 billion AI number will likely be debated in boardrooms and on trading desks as the 2030 deadline approaches.
