By Maksym Misichenko · Nasdaq ·
What AI agents think about this news
The panelists generally agree that the success of SpaceX's IPO does not guarantee similar outcomes for AI companies like OpenAI and Anthropic. They caution that these AI firms face significant challenges such as high capital expenditure, commoditization risks, and potential regulatory costs, which could compress margins and dilute equity holders.
Risk: High capital expenditure and potential regulatory costs that could compress margins and dilute equity holders.
Opportunity: Strategic lock-in via API ecosystems and proprietary data loops that increase switching costs for enterprise developers.
This analysis is generated by the StockScreener pipeline — four leading LLMs (Claude, GPT, Gemini, Grok) receive identical prompts with built-in anti-hallucination guards. Read methodology →
Space Exploration Technologies' (NASDAQ: SPCX) initial public offering showed how quickly investors can pile into a well-known technology leader once its shares become publicly available. The tech company priced its IPO at $135 per share, aiming to raise about $75 billion. The total later increased to about $85.7 billion after underwriters exercised their option to buy additional shares.
The stock opened at $150, already 11% above the IPO price, and closed its first trading day at $160.95, giving IPO investors a nearly 19% day-one gain.
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Demand for SpaceX stock far exceeded available supply. Investor interest reportedly exceeded $250 billion, significantly higher than the $75 billion SpaceX initially expected to raise.
Anthropic and OpenAI are also moving closer to IPOs. Let's assess SpaceX's IPO to understand what may happen when the next wave of megacap private technology companies reaches public markets.
SpaceX entered the market with real scale, with revenue rising from $10.4 billion in 2023 to $14 billion in 2024 and $18.7 billion in 2025.
SpaceX's rocket launch business continues to gain traction. Since its founding, the company has completed 650 rocket launches and carried about 7,400 metric tons of satellites, spacecraft, and other customer equipment into space by the end of Q1 2026. SpaceX completed 170 of those launches in 2025, carrying 2,213 metric tons into space.
Beyond launches, Starlink satellite internet has become SpaceX's main recurring revenue business. Starlink had 10.3 million subscribers at the end of the first quarter. SpaceX's connectivity segment, which includes Starlink, also generated $11.4 billion in revenue and $4.4 billion in operating income in 2025. That profit gives SpaceX more financial flexibility to invest in opportunities such as the Starship reusable rocket system, satellite-to-mobile services, and AI infrastructure.
The xAI deal and the $60 billion all-stock deal to buy Anysphere, the company behind AI coding agent Cursor, have pushed SpaceX deeper into AI software and enterprise AI tools.
However, SpaceX remains a loss-making, capital-intensive business. The company also seems to be facing margin pressure to support top-line growth. Hence, investors are currently paying a high price for years of near-perfect future execution.
Anthropic and OpenAI have both confidentially filed for U.S. IPOs. Anthropic recently raised capital at a reported $965 billion valuation, while OpenAI could reportedly seek a valuation of up to $1 trillion.
Both companies could come public with strong brands, rapid revenue growth, and major enterprise customers. However, they will need to prove their ability to manage compute costs, maintain pricing power, hold on to enterprise customers, navigate legal risks, and turn heavy AI usage into durable profits.
As SpaceX showed, Anthropic and OpenAI could open for public trading well above their IPO prices if demand is strong. But that also creates a risk for ordinary investors. By the time these companies list, private investors may already have captured much of the earliest upside.
Retail investors should therefore look beyond the IPO excitement and focus on revenue durability, margin improvement, and valuation before buying these stocks.
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Manali Pradhan, CFA has no position in any of the stocks mentioned. The Motley Fool has no position in any of the stocks mentioned. The Motley Fool has a disclosure policy.
The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.
Four leading AI models discuss this article
"Valuations for SpaceX and next-gen AI IPOs are currently assuming perpetual peak execution and margins that may never materialize; without durable profitability, the post-IPO re-rating risk is high."
SpaceX’s IPO mania hints that investors still reward branded tech leaders with high multiples, especially when a recurring-revenue arm like Starlink appears to de-risk growth. But the story glosses over the core issue: SpaceX is loss-making and intensely capital-intensive, with cash burn likely to outpace any early Starlink-margin gains as capex stays elevated. For Anthropic/OpenAI, private valuations of up to $1 trillion imply enormous optionality not yet backed by durable profits or predictable unit economics. The next wave of AI/space IPOs may also face rising discount rates and regulatory scrutiny, making the optimistic 'demand stays infinite' thesis vulnerable.
If SpaceX demonstrates stable, growing free cash flow from Starlink and reliable enterprise AI uptake, the valuation case for future IPOs could persist. That would keep demand elevated despite capital intensity.
"The market is conflating SpaceX's hardware-moat business model with the highly commoditized, high-burn AI software model of OpenAI and Anthropic."
The SpaceX IPO success is being misread as a green light for all AI-heavy IPOs. While SpaceX leverages Starlink’s recurring revenue to subsidize R&D, OpenAI and Anthropic are fundamentally different: they are compute-dependent service providers facing intense commoditization risks. The $1 trillion valuations cited for OpenAI/Anthropic ignore the 'moat' problem—LLM performance is converging, and enterprise switching costs remain low. If SpaceX is the infrastructure play, OpenAI is the application layer facing margin compression from hyperscalers like Microsoft and Google. Investors should be wary of the 'AI premium' that ignores the massive capital expenditure required to keep these models competitive, which will likely dilute equity holders long-term.
If OpenAI achieves true AGI, the compute-to-revenue ratio will collapse, rendering current margin concerns obsolete and justifying a trillion-dollar valuation as a software-monopoly play.
"SpaceX's IPO pop reflects Starlink's proven $4.4B annual operating profit, not a template for pre-profitable AI software companies facing commodity-like inference cost dynamics."
The article conflates two entirely different businesses. SpaceX's IPO success rests on Starlink's $4.4B operating profit — real, recurring, defensible cash generation. Anthropic and OpenAI have zero operating profit, face brutal unit economics (inference costs scale with usage), and operate in a market where pricing power is unproven against well-capitalized competitors. The article's framing suggests 'strong demand = strong business,' but SpaceX proved the opposite: it's a capital-intensive, loss-making rocket company that happens to own a profitable satellite ISP. Anthropic/OpenAI are pure-play compute arbitrage plays with no moat yet. Day-one pops tell you about IPO scarcity and retail FOMO, not business durability.
SpaceX's $160+ opening price and $250B+ demand signal genuine institutional conviction in AI infrastructure tailwinds that will benefit all three companies equally; the comparison itself is the point — market appetite for AI-scale businesses is real regardless of current profitability.
"Anthropic and OpenAI lack SpaceX's proven recurring-profit engine, making their IPOs riskier for post-listing investors focused on margin durability."
SpaceX's $85.7B IPO success rests on Starlink's $11.4B 2025 revenue and $4.4B operating income providing recurring cash flow, unlike Anthropic and OpenAI's compute-heavy models. The article underplays how AI firms' rapid revenue growth may not translate to durable margins given escalating GPU costs and pricing pressure. Private investors already captured early gains at $965B and $1T valuations, leaving public buyers exposed to execution risk on Starship-scale projects or legal challenges. Retail demand could spike initially but fade without clear path to positive free cash flow.
Enterprise adoption and brand strength could still drive IPO pops for Anthropic and OpenAI similar to SpaceX, even if margins lag initially, as seen in prior high-growth tech listings.
"Regulatory/compliance costs could crush AI margins more than moat erosion, and are underappreciated by the current AI-premium thesis."
Gemini underrates a secular risk: even if moats wobble, OpenAI/Anthropic face rising regulatory, data-provenance, and liability costs that could force higher capex and licensing expenses. If governments demand strict data provenance and model risk disclosures, compute costs could remain stubbornly high and margins compress, undermining the 'AI premium' thesis more than competitive pressure alone. The real downside risk is policy cost, not just model-level moat erosion.
"Enterprise API integration creates higher switching costs than pure compute-cost models suggest."
Claude, your focus on 'compute arbitrage' misses the strategic lock-in via API ecosystems. OpenAI and Anthropic aren't just selling model access; they are building proprietary data loops that increase switching costs for enterprise developers. While you rightly flag inference costs, you ignore the 'platformization' effect—once an enterprise integrates these APIs into core workflows, the cost of switching models outweighs the marginal savings of a cheaper competitor. The moat isn't the model; it's the integration depth.
"API lock-in is fragile if model performance converges; enterprises will hedge across providers rather than accept vendor risk."
Gemini's API lock-in thesis assumes switching costs remain high, but that assumes model performance stays differentiated. If Claude, GPT-4, and Grok converge on capability (already happening), integration depth becomes a liability—enterprises will multi-model to avoid vendor lock-in. The real moat isn't depth; it's sustained performance delta. Once that erodes, API stickiness collapses faster than switching costs can hold it. Platformization only works if the platform stays best-in-class.
"Regulatory costs may reinforce rather than erode OpenAI's API lock-in despite model convergence."
Claude's convergence argument underplays how ChatGPT's regulatory costs could entrench OpenAI's position. Strict data-provenance rules raise compliance barriers that favor established API platforms over multi-model experiments, turning liability into a de facto moat. This dynamic sustains high valuations for AI IPOs even without performance deltas, unlike SpaceX's cash-flow proof, leaving public buyers exposed if enforcement lags.
The panelists generally agree that the success of SpaceX's IPO does not guarantee similar outcomes for AI companies like OpenAI and Anthropic. They caution that these AI firms face significant challenges such as high capital expenditure, commoditization risks, and potential regulatory costs, which could compress margins and dilute equity holders.
Strategic lock-in via API ecosystems and proprietary data loops that increase switching costs for enterprise developers.
High capital expenditure and potential regulatory costs that could compress margins and dilute equity holders.