Rise of AI Computing Power Newcomers: Restructuring of US Stock Market Computing Power Landscape and Investment Opportunities in September 2026
With the rapid development of artificial intelligence technology, global AI computing power demand is showing explosive growth. The US stock market, as a frontier for global technological innovation, is experiencing unprecedented changes and opportunities in its AI computing power sector. In September 2026, with the release of next-generation AI chips, the popularization of large model applications, and the continuous increase in computing power demand, the US stock market AI computing power landscape is quietly being reshaped, with new investment opportunities and challenges coexisting.
Market Overview: Continuous Growth in AI Computing Power Demand
In the third quarter of 2026, global AI computing power demand continued to maintain a strong growth trend. According to the latest data from market research institutions, the global AI chip market size grew by more than 60% year-on-year, with the US market accounting for nearly 70% of the global share. Against this backdrop, US stock market AI computing power-related companies have shown outstanding stock performance, with many leading stocks reaching historic highs.
Notably, AI computing power demand is shifting from pure training needs to inference needs, and this shift is profoundly affecting the supply and demand landscape of the computing power market. With the popularization of large model applications and the acceleration of commercialization, AI inference demand is showing explosive growth, becoming a new engine driving the development of the computing power market.
Chip Giants: Next-Generation Products Leading Market Transformation
In the AI chip field, NVIDIA (NVDA) continues to lead the market, with its latest-generation Blackwell architecture chips in continuous high demand. Although the production of the Blackwell Ultra version has been delayed, NVIDIA still firmly maintains its market dominance with its strong technical advantages and ecosystem. Data shows that NVIDIA's share in the high-end AI chip market exceeds 80%, demonstrating strong market control.
Meanwhile, traditional chip giants like AMD (AMD) and Broadcom (AVGO) are accelerating their layout in the AI chip field, attempting to break NVIDIA's market monopoly. AMD's latest MI300X chip has performance close to NVIDIA's H100 and has certain price advantages, starting to win favor from some customers. Broadcom, leveraging its advantages in the network chip field, has launched customized solutions for AI data centers, gradually establishing itself in niche markets.
In addition, Intel (INTC) is also actively transforming, launching the Gaudi 3 AI chip, attempting to gain a foothold in the highly competitive AI chip market. Although Intel's current AI chip market share is relatively small, its strong manufacturing capabilities and complete ecosystem provide a solid foundation for its future development.
Demand-Side Changes: Rise of Large Model Applications and Inference Demand
In 2026, large model applications have entered the commercialization stage, having a profound impact on computing power demand. Tech giants such as Google (GOOGL), Microsoft (MSFT), and Meta (META) are increasing their investment in large model R&D while promoting the application of large models across various industries, which directly drives strong demand for AI computing power.
Notably, AI inference demand is becoming a new growth point in the market. With the popularization of large model applications, companies' demand for AI inference is showing explosive growth, and the diversity and complexity of inference scenarios put higher demands on computing power. Market data shows that the growth rate of AI inference demand has exceeded that of training demand, becoming the main driving force for the development of the computing power market.
In addition, edge computing and the AI transformation of terminal devices are also bringing new opportunities to the computing power market. With the popularization of IoT devices and the penetration of AI technology, edge AI computing demand is growing rapidly, creating new market space for chip manufacturers and data center providers.
Industrial Chain Restructuring: Supply Chain Optimization and Data Center Transformation
In the face of rapid growth in AI computing power demand, the entire industrial chain is undergoing profound restructuring. In terms of supply chain, chip manufacturers are actively optimizing supply chain layouts, strengthening cooperation with upstream equipment and material suppliers to ensure stable production capacity. Meanwhile, chip foundries like TSMC (TSM) and Samsung Electronics (SSNLF) are also increasing investment in advanced process capacity to meet the production needs of AI chips.
In the data center field, the construction of ultra-large-scale data centers continues to accelerate. Tech giants like Microsoft, Google, and Amazon (AMZN) are investing heavily in building next-generation AI data centers to meet the growing computing power demand. At the same time, the design concept of data centers is also changing, with more emphasis on energy efficiency optimization and green low-carbon approaches to address the huge energy consumption brought by AI data centers.
Power supply has become a key factor constraining the development of AI data centers. With the rapid growth of AI data center energy consumption, power supply and energy costs have become the focus of corporate attention. Some companies are beginning to explore alternative energy solutions such as nuclear energy and renewable energy to solve power supply issues.
Investment Opportunities and Risks: Grasping the Main Investment Themes in AI Computing Power
In the face of the vigorous development of the AI computing power market, how can investors seize investment opportunities and avoid potential risks? From an investment perspective, the AI computing power market mainly has the following investment themes:
- Chip leaders: AI chip leaders like NVIDIA, AMD, and Broadcom, with their technical advantages and market share, have high certainty for long-term growth.
- Computing power leasing: With the growth of computing power demand, computing power leasing service providers like CoreWeave are expected to benefit from price increases due to the scarcity of computing resources.
- Data center infrastructure: Data center builders, server manufacturers, and data center infrastructure providers will directly benefit from the AI data center construction boom.
- Power solutions: For the high energy consumption problem of AI data centers, power solution providers such as nuclear small reactor technology companies are expected to encounter development opportunities.
However, AI computing power investment also faces many risks. First, the risk of technological iteration cannot be ignored. AI chip technology is updated and replaced quickly, and companies need to continuously invest in R&D to maintain competitiveness. Secondly, supply chain risks still exist, and geopolitical factors may affect the stability of the global chip supply chain. In addition, valuation risks also need attention. Some AI computing power-related companies are already at high valuation levels, and investors need to be alert to the risk of corrections.
Conclusion: Grasping the Long-Term Investment Value of AI Computing Power
Overall, in September 2026, the US stock market AI computing power market is in a vigorous development stage, with the market landscape being reshaped and new investment opportunities constantly emerging. In the long run, as the infrastructure supporting artificial intelligence development, AI computing power demand will continue to grow, and related companies are expected to enjoy the dividends of industry development.
For investors, attention should be paid to leading companies with core technical advantages, leading market share, and reasonable valuations, while also paying attention to investment opportunities in the upstream and downstream of the industrial chain. In terms of risk control, attention needs to be paid to risks such as technological iteration, supply chain, and valuation, adopting a diversified investment strategy to grasp the long-term investment value of AI computing power.
With the continuous advancement of artificial intelligence technology and the continuous expansion of application scenarios, the AI computing power market will maintain a strong growth trend, bringing generous returns to investors. Grasping the main investment themes of AI computing power will be an important direction for US stock market investment in the coming years.
