As Nvidia’s quarterly revenue approaches $100 billion and its market capitalization surpasses $5 trillion, CEO Jensen Huang made a striking admission during the company’s latest earnings call: “My only regret is that we didn’t start earlier and invest more.”
Nvidia released its fiscal second-quarter 2027 results on Aug. 26. Quarterly revenue reached $96.2 billion, an increase of 106% from a year earlier. Data center revenue climbed 117% to $89 billion, marking the segment’s sixth consecutive quarter of triple-digit growth. Net income surged 158% year on year to $55.26 billion.
While the results were impressive in their own right, Huang’s comments on Nvidia’s artificial intelligence investments drew particular attention from the market.
“Investing in these companies represents a once-in-a-lifetime opportunity,” Huang told analysts. “My only regret is that we didn’t start earlier and invest more.”
A “Once-in-a-Lifetime Opportunity”
The companies Huang referred to are the AI laboratories and infrastructure providers that Nvidia has backed heavily in recent years.
In February, Nvidia announced a $30 billion purchase of OpenAI shares, making it one of the AI company’s largest shareholders. That same month, Nvidia also participated in Anthropic’s Series G funding round, which valued the startup at $380 billion.
This is not the first time Nvidia has used equity investments to deepen its position across the AI value chain. Since the beginning of 2026, the chipmaker’s AI investment commitments have exceeded $40 billion. Its portfolio spans leading model developers, including OpenAI, Anthropic and xAI; AI cloud providers such as CoreWeave and Nebius; and data center infrastructure companies including Corning and IREN.
Huang also said during the call that OpenAI and Anthropic “could go public soon, with other companies likely to follow.”
His remarks underscore Nvidia’s broader investment strategy. By securing stakes in key AI companies before they go public, Nvidia can strengthen long-term computing demand and ecosystem relationships while positioning itself to benefit from potential gains in the public markets.
Huang’s “Regret” as AI Spending Accelerates
Huang’s expression of regret appears to reflect Nvidia’s comparatively cautious approach to external investment in earlier years. Although the company began investing in AI startups through NVentures in 2023, its most aggressive expansion did not begin until the second half of 2025. By then, the valuations of leading AI companies such as OpenAI and Anthropic had risen severalfold from earlier funding rounds.
Nvidia has committed more than $40 billion to AI-related equity investments in 2026. The portfolio is anchored by its $30 billion investment in OpenAI, its participation in xAI’s $20 billion Series E round and Anthropic’s $30 billion Series G financing.
During the earnings call, Huang said returns on AI investment had reached an inflection point and were poised to accelerate.
“Each new generation of architecture significantly lowers the cost per token while improving reasoning capabilities, enabling a broader range of applications,” he said. “We are seeing AI move from training to inference and from niche adoption into the mainstream.”
Nvidia’s Compute Hedge
Nvidia’s investment strategy gives it exposure to both the financial upside of leading AI companies and their continued demand for computing infrastructure.
Based on OpenAI’s latest valuation, Nvidia’s $30 billion stake has already appreciated substantially. Its investment in Anthropic is also sitting on significant gains following confirmation of the company’s $965 billion valuation.
If these portfolio companies eventually go public, Nvidia could benefit from both equity appreciation and continued purchases of its computing systems. This combination of capital returns and entrenched demand for Nvidia hardware lies at the heart of Huang’s strategy.
“AI factories will become the next generation of critical infrastructure,” Huang said. “Nvidia is providing the most important raw material for this era.”
When Huang speaks of regret, the broader message may be that Nvidia’s effort to consolidate its position across the AI ecosystem is only beginning.
This article is provided for informational purposes only and does not constitute investment advice.