SpaceX is in early discussions about purchasing data from troubled or failed startups to improve its artificial intelligence models, according to internal talks revealed this week. The aerospace company's AI unit, SpaceXAI, is exploring this unconventional data sourcing strategy as a way to access affordable training material for Grok, its large language model (LLM), which is an AI system trained on vast amounts of text to understand and generate human language. While these conversations remain informal and may not result in actual deals, the move signals how aggressively Elon Musk's companies are pursuing AI development.

The strategy would give SpaceX access to operational data, customer information, and other datasets from companies that have shut down or are struggling financially. This approach mirrors a tactic used by Google, which spent $10 million to acquire business data from Spirit Airlines after the carrier ceased operations. However, Google's purchase sparked significant data privacy concerns, raising questions about whether similar moves by other companies could face similar backlash.

Why Would SpaceX Need Outside Data for AI Training?

SpaceX has historically relied on two primary methods to train its AI systems. First, the company has used data from X, the social network owned by CEO Elon Musk, to help develop its models. Second, SpaceX employs specialized staff called AI tutors, who are engineers that manually refine and improve AI software by providing feedback and corrections. However, the company recently paused hiring for these AI tutors, suggesting it may be seeking alternative ways to enhance its models without expanding its internal workforce.

The financial stakes are substantial. SpaceX invested $15.8 billion in AI-related capital expenditures in the second quarter of 2026 alone, demonstrating the company's commitment to becoming a major player in artificial intelligence. Despite generating $2.56 billion in AI business revenue during that same period, SpaceX reported an operating loss of $1.26 billion, indicating that the company is willing to absorb significant costs to build out its AI capabilities.

How to Understand the Data Privacy Implications of AI Training

• Customer Data Concerns: When companies purchase data from failed startups, that information often includes customer records, transaction histories, and behavioral patterns that users may not have explicitly consented to be used for AI training purposes.
• Regulatory Risk: Data acquisition deals like this could face scrutiny from regulators concerned about privacy violations, especially if the original data collection occurred under different terms than AI training.
• Competitive Intelligence: Operational data from startups may contain proprietary business information, trade secrets, or strategic insights that competitors could exploit if purchased and analyzed.

The precedent set by Google's Spirit Airlines deal shows that such transactions can attract public attention and criticism. While Google's purchase was technically legal, it raised ethical questions about whether companies should be able to repurpose customer data for AI training without explicit consent. SpaceX's exploration of similar deals suggests the company believes the benefits of improved AI models outweigh these concerns, though the company has not yet committed to any specific purchases.

What Does This Mean for SpaceX's AI Ambitions?

SpaceX's interest in acquiring external data reflects the broader challenge facing AI companies: training state-of-the-art models requires enormous amounts of high-quality data. As public datasets become saturated and harder to access, companies are increasingly turning to alternative sources, including purchasing data from other organizations. For SpaceX, this strategy could accelerate the development of Grok and reduce the company's reliance on internal tutors, who are expensive to hire and train.

The discussions remain preliminary, and Bloomberg's sources indicated that these conversations within SpaceXAI teams are informal and may not lead to actual deals. However, the fact that SpaceX is considering this approach at all demonstrates how seriously the company is taking AI development as a core business priority. With billions in capital expenditures already committed and significant operating losses being absorbed, SpaceX appears willing to explore unconventional strategies to gain competitive advantages in the rapidly evolving AI landscape.

Meanwhile, SpaceX continues to expand its AI infrastructure in other ways. The company is building Terafab, a joint venture with Tesla to create a $16.8 billion chip fabrication plant that will produce semiconductors specifically designed to power AI systems, including Grok and other applications. This vertical integration strategy, combined with data acquisition efforts, suggests SpaceX is building a comprehensive AI ecosystem that spans data, computing power, and specialized hardware.

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