
The investment trend in AI has changed! The market now demands less "promising" and more "monetization."

NVIDIA's financial report and the hundreds of billions of dollars in circular transactions between NVIDIA, Microsoft, and Anthropic failed to boost the market, indicating a shift in the investment logic of artificial intelligence. Market attention on AI has shifted from long-term vision to short-term profit realization. Investors are no longer buying into the "investment - procurement" circular transaction model among giants, but are instead placing greater importance on whether companies can demonstrate tangible profitability and commercialization results in the near term
The "build success first, then achieve success" model is facing skepticism from investors in the field of artificial intelligence.
Despite NVIDIA's latest financial report exceeding market expectations, its stock price closed down on the same day, experiencing the largest fluctuation since April during intraday trading. Additionally, on November 18, NVIDIA and Microsoft announced a $15 billion investment in Anthropic, which promised to purchase $30 billion worth of computing power from Microsoft. The market reacted tepidly to this news, whereas similar circular investment announcements in the past typically drove stock prices up.

Current market sentiment has clearly shifted from the past belief that AI investments would inevitably yield returns to a more cautious attitude. Investors are losing interest in the long-term strategy of "investing heavily now and waiting for future returns," and are instead focusing on AI business models that can achieve profitability in the near term. This trend poses new pressure on AI companies that rely on long-term visions and infrastructure suppliers like data centers.
The market re-evaluates the logic of "burning money for growth"
The core issue facing AI service providers is that the cost of providing services exceeds the price customers are willing to pay, leading to greater losses as the customer base grows.
These companies' strategy is to subsidize customer growth through shareholder funding, creating a virtuous cycle: user growth stimulates investor funding and boosts valuations, allowing companies to hire engineers (partly paid in equity), subsidize more customers, and invest heavily in infrastructure, hoping to eventually develop high-quality products that can be sold at full price.
However, investors have gradually recognized the fragility of this model, and are unwilling to continue bearing massive investments in pursuit of highly uncertain returns. The widespread decline of AI infrastructure stocks this month reflects the market's re-evaluation of this "burning money for growth" logic.
Investors shift to short-term profit strategies
The market's attitude towards AI investments is shifting from "inevitable returns" to cautious assessment, but it is far from a complete denial phase. NVIDIA's stock price has still accumulated over a 30% increase this year, Microsoft has risen by 14%, and CoreWeave, which has expanded from cryptocurrency business to cloud services since its IPO in March, has seen an increase of nearly 80%.
The investment logic of artificial intelligence is undergoing a profound transformation, with market attention shifting from long-term visions to short-term profit realization. Investors are no longer blindly chasing the elusive narrative of "superintelligence," but are more focused on whether companies can demonstrate tangible profitability and commercialization effects in the near term. This shift also explains why Alphabet has performed steadily during this round of market fluctuations, as the company focuses on translating existing technologies into actual value for enterprise customers, showcasing a clear monetization path.
It is evident that the market is bidding farewell to concept hype and demanding companies to demonstrate clear profit pathways. This shift poses pressure on companies that rely on long-term narratives, such as Meta Platforms, OpenAI, and related data center suppliers. However, for now, this is merely a rational adjustment of investment logic, rather than a collapse of the AI bubble

