US AI trading enters a structural restructuring phase: from chip frenzy to system-level bottleneck pricing

In today’s U.S. stock market, AI remains one of the most core themes driving the market. The semiconductor sector has continued to perform strongly in 2026. AI-related assets have consistently contributed to the upward momentum of the index, and technology stocks remain the most important driving structure for the U.S. stock market.

However, if you only look at the index, you may miss a more critical change: AI hasn’t ended—it has moved into a new mode of operation.

The market is still revolving around AI, but capital is no longer concentrating on a single flagship. Instead, it is beginning to spread along the AI industry chain. This shift means that the U.S. stock market is gradually moving from a “single-point-driven rally” toward a “structural rotation-driven rally.”

1. The Starting Point of the AI Rally: The Chip-Driven Concentrated Breakout Phase

In the early stages of the AI rally, the market structure is very clear. Growth is almost entirely centered on GPUs. The expansion of computing power becomes the only certain direction. GPUs, cloud computing, and leading technology companies form the core chain.

The defining feature of this phase is high concentration, with a straightforward and direct market logic: the stronger the computing power, the faster the growth, and the higher the valuations.

Capital concentrates in a small number of core assets, forming a distinct single-core driven structure. In this phase, AI is more like a “computing power story” rather than a complete system.

2. The Starting Point of Structural Change: AI Moves from a Computing Power Issue to System Engineering

As the scale of AI models continues to grow, a key change gradually becomes visible: bottlenecks begin to overflow. When models move from tens of billions of parameters to the trillions-parameter level, computing power is no longer the only limiting factor. New bottlenecks begin to spread across multiple layers, including storage bandwidth, data transmission efficiency, network interconnect capability, and data center energy consumption. This means AI has upgraded from a single computing problem to a complex system engineering problem.

After system complexity increases, growth no longer concentrates on a single node—it expands to multiple stages along the industry chain.

3. Migration of Capital Structure: From GPU Single-Point Driving to AI Industry Chain Diffusion

The most critical change in the current U.S. stock market is that capital structure is being rebuilt. In the early stages, the capital path was GPU → cloud providers → AI applications. The structure was highly concentrated, and the growth logic was clear. But now, the path is expanding to GPU → HBM → network chips → data centers → electricity and infrastructure.

The essence of this change is the migration of AI bottlenecks. When GPUs are no longer the only constraint, the market starts to focus on how data flows, how it is stored, and how it is efficiently scheduled within the system. As a result, capital spreads from a single computing node to the entire AI system chain.

4. The Core Market Change: From “Buying Computing Power” to “Buying Bottlenecks”

The essence of the AI rally is changing.

In the past, the market traded on computing power expansion. Now, the market trades on bottleneck positions.

Different stages correspond to different investment logic:

• When computing power is scarce, GPUs are the core;
• When bandwidth is insufficient, HBM becomes the core;
• When data transmission is constrained, network chips become the core;
• When system scale expands, data centers and energy become the core.

This means AI pricing logic is shifting from “single-technology-driven” to “system-bottleneck-driven.”

5. Changes in the Influence of the Magnificent Seven: From Leading the Market to Becoming Structural Components

It is important to emphasize that the Magnificent Seven have not lost their influence. However, their ability to “explain the market” is declining. The reason is that AI growth is no longer concentrated—it is distributed across multiple industry nodes. After capital expenditures expand, the benefits of growth are split across the entire supply chain system. In the past, one company could represent AI. Now, one company can only represent a certain segment.

Therefore, market pricing power is gradually shifting from the company level to the industry chain level.

6. A Multi-Center Driven Structure: The U.S. Stock Market Enters a New Pricing System

The current U.S. stock market is forming a new structural model: a multi-center driven system. In this system, there is no single core—multiple driving centers exist simultaneously, including a computing power center, a storage center, a network center, and an infrastructure center.

These centers are not in a linear relationship; they influence each other in a cross-linked way. For example, GPUs drive demand for HBM, but HBM supply in turn limits GPU expansion. Network chips improve data flow efficiency while also affecting computing power utilization.

As a result, the market is shifting from a single-direction trend to a multi-dimensional rotation structure.

7. Changes in Market Behavior: Higher Volatility and Structural Divergence

Market behavior is showing clear changes.

• Industry correlation is declining, and the performance of different sectors is starting to diverge;
• Rotation speed is accelerating, with capital switching frequently among segments along the AI chain;
• The index diverges from its internal structure: the index remains at a high level, but internal volatility rises significantly.

This means the market is shifting from trend trading to structural trading.

8. AI Is Entering a Structural Cycle Phase

The fundamental change in the current AI rally is that it is moving from theme-driven momentum to a structural cycle.

Theme rallies are characterized by concentrated breakouts, while structural cycles are characterized by segmented rotation.

In a theme rally, the market focuses on whether AI is rising. In a structural cycle, the market focuses on which segment of AI is experiencing bottlenecks.

So the current rally has not ended—it is entering a more complex stage of development.

9. Cross-Market Linkages: AI Pricing Is Being Distributed Globally

With the globalization of the AI industry chain, the U.S. stock market is no longer the only pricing center. Korean stocks price storage and HBM, Hong Kong stocks participate in AI applications and parts of the hardware chain, and the U.S. stock market leads in computing power and system architecture.

AI investment therefore shows a globally distributed, decentralized structure, and cross-market linkages have become a new feature.

10. Gate Stock Trading: Cross-Market Tracking of AI Structural Changes

As the AI industry chain expands across multiple dimensions such as computing power, storage, networking, and energy, a single market can no longer fully reflect industry changes. Clear division of labor forms among different markets, making cross-market tracking increasingly important.

Gate Stock Trading supports 7 × 24 hour all-day trading of U.S., Hong Kong, and Korean stocks. This enables investors to continuously track price changes and capital flows of AI-related assets across different markets—from computing chip leaders, to storage leaders, to infrastructure chains—allowing for more flexible participation in global AI industry chain rotation opportunities.

11. Conclusion: AI Is Entering the Era of System-Level Pricing

The AI rally in the U.S. stock market is undergoing deep structural changes, moving from concentrated pricing by the Magnificent Seven to distributed pricing across the industry chain.

The key question for the future market is no longer whether a single company is rising, but which segment in the AI industry chain becomes the new bottleneck.

AI is evolving from an investment theme into a long-term structural cycle, and is redefining the pricing logic of the U.S. stock market.

FAQs

Q1: Has the AI rally ended?

No. It hasn’t ended—it has entered a phase of structural differentiation.

Q2: Why does AI cause changes in market structure?

Because AI changes from a single-point computing power issue into a system engineering problem.

Q3: Is the market a bull market or a consolidation right now?

It is more of a structural bull market, but internally it features a high-volatility rotation structure.

Q4: What is system-level bottleneck pricing?

The market no longer only prices companies—it prices the bottleneck segments within the AI system.

Q5: What is the core variable for the future AI rally?

The core is the change in bottleneck positions, not the performance of a single flagship.