Jensen Huang’s Candid Speech Reflects NVIDIA’s Reality and the U.S. Economy’s Dependence on AI

When I first saw Jensen Huang’s recent statement, I honestly thought it was a bit extreme. Saying, “Any manager who suggests cutting AI investment is out of their mind,” seemed bold, even for someone as confident as him. However, upon delving into the article, I realized that his confidence is well-founded. Particularly, the notion that NVIDIA’s performance is propping up the U.S. economy might not be an exaggeration.

As of November 2025, NVIDIA’s market capitalization exceeds $3.6 trillion, which is about 13% of the entire U.S. GDP. If a single company has such an impact on a national economy, Jensen Huang’s statement seems more than mere bravado. In fact, NVIDIA accounts for 7.2% of the S&P 500 index, indicating that fluctuations in NVIDIA’s stock price significantly affect the entire U.S. stock market.

What I found most intriguing was Jensen Huang’s direct criticism of managers advocating for reduced AI investment. This also reflects that some companies currently hold a skeptical view of AI investment. In reality, AI-related investments by U.S. companies increased by 15% in the third quarter of 2025 compared to the previous quarter, but the growth rate is slowing. In this context, Jensen Huang’s firm stance seems intended to send a strong message to the market.

NVIDIA’s recent performance helps to understand Jensen Huang’s confidence. In the third quarter of 2025, revenue reached $35.1 billion, a 206% increase year-on-year, and net income surged by 485% to $16.9 billion. Notably, revenue from the data center segment hit $30.7 billion, accounting for 87% of total revenue, demonstrating NVIDIA’s dominant position in the AI semiconductor market. Demand for H100 and the latest H200 GPUs far exceeds supply, with current orders taking an average of 6-8 months to fulfill.

Structural Changes in the AI Semiconductor Market and Competitive Environment

NVIDIA’s strong stance is due to the structural characteristics of the AI semiconductor market. Currently, NVIDIA holds about 88% of the market share for high-performance GPUs needed for generative AI training. While there are competing products like AMD’s MI300X and Intel’s Gaudi series, they have yet to catch up to NVIDIA in terms of performance and software ecosystem.

The existence of the CUDA platform further solidifies NVIDIA’s competitive edge. Global AI developers are already familiar with the CUDA environment, and the cost and time required to migrate existing codebases to other platforms are substantial. This creates a sort of ‘technological lock-in’ effect, making it difficult for competitors to capture market share solely based on hardware performance.

However, signs of change are emerging. Google’s TPU v5p, Amazon’s Trainium2, and Microsoft’s Maia 100, all developed in-house, are significantly improving in performance. Particularly, Google’s TPU v5p shows 2.8 times faster performance than the H100 for specific workloads, suggesting that large cloud providers’ reliance on NVIDIA may gradually decrease.

The Chinese market is another variable that cannot be ignored. Due to U.S. government semiconductor export restrictions, NVIDIA cannot directly sell high-performance GPUs to China, but Chinese tech giants like Baidu and Alibaba are accelerating their own AI chip development. Although Baidu’s Kunlun chip and Alibaba’s Hanguang chip currently lag behind NVIDIA in performance, they are rapidly advancing and could pose a long-term threat.

The Impact on the U.S. Economy and Policy Implications

Jensen Huang’s statement that “NVIDIA’s performance supports the U.S. economy” might not be an exaggeration. In fact, analyses suggest that AI-related investments contribute approximately 0.8 percentage points to the 2.4% U.S. GDP growth rate in 2025. This means that the revenue growth of AI semiconductor companies, including NVIDIA, is directly contributing to U.S. economic growth.

More specifically, NVIDIA’s direct employment impact is significant. Currently, NVIDIA employs about 76,000 people worldwide, with 65%, or 49,400 employees, working in the U.S. Considering the average salary is around $230,000, the consumer spending by NVIDIA employees significantly impacts the U.S. domestic economy. Additionally, the 35% increase in real estate prices in the Santa Clara area of California, where NVIDIA’s headquarters is located, over the past two years is not unrelated.

The indirect ripple effects are even greater. Fueled by NVIDIA’s growth, AI startup investments have surged, with U.S. AI startup investments reaching $48.7 billion in the first three quarters of 2025, a 73% increase year-on-year. This accounts for 42% of total venture capital investments. The rising valuations of AI unicorns like OpenAI, valued at $157 billion, and Anthropic, valued at $18.3 billion, are also based on strong demand for NVIDIA GPUs.

From a policy perspective, interesting changes are occurring. While the Biden administration has focused on AI safety and regulation, there is a growing recognition that securing AI competitiveness is more important. Considering the rapid pace of AI technology development in China, there is a growing voice that the U.S. must support the growth of key companies like NVIDIA to maintain technological superiority in the AI field. In fact, the U.S. Department of Defense has allocated $18.4 billion for AI-related budgets in 2025, a 45% increase from the previous year, with a significant portion intended for purchasing NVIDIA GPUs.

However, concerns are being raised about whether such dependence on NVIDIA is healthy. If a single company has too much influence on the national economy, any issues with that company could have significant repercussions on the entire economy. Reflecting on the examples of companies like Cisco and Intel during the dot-com bubble in 2000, it’s hard to say that NVIDIA’s current situation is entirely different.

Personally, I believe Jensen Huang’s statement serves as a strong signal to the market. At a time when skepticism about AI investment is spreading, the CEO of the industry’s leading company sending such a confident message is certainly meaningful. In fact, following his statement, AI-related stocks have shown a collective upward trend, and institutional investors are expanding their AI sector allocations.

Ultimately, Jensen Huang’s recent statement is not mere bravado but is based on the structural characteristics of the current AI semiconductor market, NVIDIA’s dominant position, and its tangible impact on the U.S. economy. While competition will intensify in the long term and technological alternatives will continue to emerge, NVIDIA’s dominance seems likely to continue for at least the next 2-3 years. However, whether this concentration is a healthy market structure and a sustainable growth model remains to be seen.

This article was written after reading the article “Is the manager who suggests cutting AI out of their mind… NVIDIA’s performance supports the U.S. economy”, and includes personal opinions and analysis.

Disclaimer: This blog is not a news outlet, and the content reflects the author’s personal views. Responsibility for investment decisions lies with the investor, and no liability is accepted for investment losses based on the content of this article.