A Wake-Up Call: Nvidia's Reassessment of OpenAI — Why Does It Hit Microsoft the Most?

Nvidia, OpenAI, and Microsoft form an AI collaboration chain, showing signs of loosening due to differences in “execution” and “business discipline.”

On Wednesday, Bloomberg technology writer Parmy Olson stated in her latest column that Huang Renxun’s hesitation toward OpenAI is not just a shift in investment sentiment but also a reminder to Microsoft that exclusive models and intellectual property do not automatically translate into product dominance. Market competition is shifting from “whose model is stronger” to “who can better implement.”

Nvidia CEO Huang Renxun recently told industry insiders that his previous announcement of a $100 billion investment in OpenAI was “not binding,” and privately criticized OpenAI for lacking commercial discipline. Huang denied dissatisfaction with OpenAI and told reporters last Saturday, “We will invest heavily,” but also left room for flexibility in his commitments.

Parmy Olson believes that this originally infrastructure-bound investment is now more likely to appear in OpenAI’s current funding process in the form of “several hundred billion dollars,” and this occurs before its potential IPO. The report also states that OpenAI is in discussions with Nvidia, Microsoft, and Amazon regarding approximately $100 billion in funding, independent of the previously proposed infrastructure deal.

The more direct market impact falls on Microsoft. Although Microsoft gained exclusive access to OpenAI’s intellectual property and models until 2032 through a restructuring agreement announced last October, and integrated Copilot into OpenAI’s latest GPT-5 model in August 2025, the Copilot product still faces user criticism and lags behind competitors in functionality, highlighting the contradiction of “possessing top-tier models but struggling to realize their advantages.”

Huang Renxun’s “Buyer’s Remorse”

According to Parmy Olson, the AI industry has long been numb to massive bets, making Huang Renxun’s cautious stance on commitments particularly noteworthy. The Wall Street Journal mentioned that Huang not only emphasized that investments are non-binding but also privately questioned OpenAI’s management and execution discipline, adding uncertainty to OpenAI’s funding narrative and partner confidence.

For investors, this signals two things: First, the capital and computing power plans around OpenAI may still be rapidly adjusting; second, even one of the core industry partners is re-evaluating risk exposure and return pathways.

Parmy Olson pointed out that Sam Altman’s management style continues to cause concern, including his dramatic dismissal at the end of 2023 and subsequent return, as well as a series of complex, multi-billion-dollar deals. She wrote that these arrangements have burdened OpenAI with commitments to 1.4 trillion dollars in computing resources, roughly 100 times its projected 2025 revenue.

On the product side, OpenAI’s progress also appears rapid. Parmy Olson cited that OpenAI attempted to establish a developer marketplace through GPT Store and custom GPTs but failed due to a lack of clear strategy. Between “model capability leadership” and “fluctuations in commercialization and organizational execution,” OpenAI’s partners need to price the uncertainty.

Microsoft’s Execution Dilemma

Microsoft’s capital returns are extremely impressive. Parmy Olson wrote that Microsoft’s early $1.3 billion investment in OpenAI now accounts for about 27% equity, with a valuation of approximately $135 billion, more than ten times the original investment; meanwhile, the restructuring agreement grants Microsoft a cleaner, exclusive access to IP and models until 2032.

But at the product level, Microsoft has not fully realized this advantage. Olson directly points out the key issue: If OpenAI can still continuously release some of the world’s most powerful AI models, why does Microsoft’s flagship product Copilot, based on OpenAI technology, lag behind competitors? She notes that user feedback on Copilot centers on “confusion, limitations, difficulty,” highlighting a gap between model quality and product implementation.

Competitive pressure is exploding at the application level. Parmy Olson wrote that last month, Anthropic released Claude Cowork, an app reportedly built with its self-developed AI coding tools in just 10 days, capable of operating on personal computers, organizing files, generating PowerPoint and Excel from documents, and replying to LinkedIn messages.

In contrast, she pointed out that despite owning Windows, Office, and LinkedIn, Microsoft’s Copilot cannot achieve these capabilities. This gap makes it easier for the market to attribute the problem to Microsoft’s internal research and productization mechanisms rather than just the models themselves.

Parmy Olson cited David Rainville, head of Sycomore Sustainable Tech, who said that some industry observers are paying attention to the direction of Microsoft’s AI leadership. He stated that if Microsoft cannot release a product comparable to Claude Cowork within the next six months, “someone will have to step down,” and noted a clear disconnect between “model quality” and “execution capability.”