The Rise of the AI Industrial Complex: How America is Quietly Building Its Sovereign AI Semiconductor Ecosystem

Why is the U.S. investing heavily in semiconductors? Is TSMC’s Arizona expansion merely a response to political pressure?

In reality, U.S. semiconductor policy is focused on building a sovereign AI manufacturing ecosystem. OpenAI can be seen as the starting point of America’s AI and semiconductor strategy, but the true battleground is in chip manufacturing. The U.S. is quietly orchestrating an “AI Semiconductor Industrial Renaissance.”

To clarify this argument, we will break it down into several parts:

1. How the U.S. AI semiconductor “sovereign version” is taking shape.
2. TSMC’s critical role in this framework.
3. The hidden AI supply chain the U.S. is constructing and how it aims to curb China’s competition.
4. Finally, we will revisit TSMC’s dual role in this transformation and Taiwan’s unique position as a supply chain management hub.

Our Analysis

1.  How is the U.S. Sovereign AI Semiconductor Ecosystem Taking Shape?

1.1  The 2019 U.S.-China Trade War: The Beginning of the “Semiconductor Security Era”

For the past 30 years, the global semiconductor supply chain has prioritized efficiency, operating under a vertical specialization model (with design, manufacturing, and packaging handled by separate companies). This approach lowered chip costs but concentrated critical technologies in a few countries and corporations. However, this model was disrupted in 2019 by the U.S.-China trade war.

At that time, the U.S. imposed chip restrictions on Huawei but was unable to fully block Chinese companies from accessing advanced semiconductors. This experience highlighted that controlling design alone was insufficient—securing manufacturing and equipment supply chains became equally crucial. From then on, U.S. semiconductor strategy shifted from an “efficiency-first” to a “security-first” approach, accelerating efforts toward localization and establishing a sovereign supply chain.

1.2  The 2022 CHIPS Act: America’s Semiconductor Policy Takes Shape

In 2022, the CHIPS Act became the cornerstone of U.S. semiconductor policy, with the Biden administration committing $52.7 billion to subsidize domestic chip manufacturing and R&D. However, this funding is not merely aimed at revitalizing the semiconductor industry—it is focused on establishing a U.S.-led AI semiconductor ecosystem.

This ecosystem spans the entire supply chain, from materials to AI design, and includes:

• Materials: DuPont, Entegris
• Equipment: Applied Materials, Lam Research
• Manufacturing: TSMC Arizona, Amkor
• Design: NVIDIA, OpenAI

Through this structure, the U.S. seeks greater autonomy in AI semiconductors while reducing reliance on foreign supply chains.

1.3  The Trump Administration Extends Biden’s Policy, Strengthening AI Semiconductor Independence

While the Trump administration may differ from Biden’s policies in other areas, both share a common strategy in semiconductor localization. In fact, the Trump administration has further reinforced this direction.

By 2025, the Trump administration prioritized the localization of the AI chip supply chain, aiming to establish a fully domestic production ecosystem. This includes materials, equipment, manufacturing, packaging, design, and even research and development. This shift marks a move from “partial U.S. manufacturing” to a fully sovereign AI semiconductor supply chain, further securing the industry’s stability.

1.4  AI Semiconductors as a Strategic Technological Asset in the Geopolitical Landscape

Under both the Biden and Trump administrations, AI semiconductors have become a national strategic asset. The U.S. is not just revitalizing manufacturing but positioning itself as the global leader in AI semiconductor technology.

This tightly integrated ecosystem—spanning materials to design—has been deliberately structured through regulations and subsidies to exclude China and other potential competitors, ensuring full control over the supply chain.

Currently, the U.S. AI semiconductor sector is focused on six key areas (as shown in Table 1):

• Materials Supply
• Semiconductor Equipment
• Chip Manufacturing
• Packaging
• GPU Design
• AI Software Infrastructure

Through a deliberate strategy, the U.S. government is securing its dominance over the entire AI chip ecosystem, further strengthening its technological competitive edge.

Table 1   U.S. AI Semiconductor Industry Landscape

Source: Researcher and Research

2.  TSMC’s Critical Role

As shown in Table 1, TSMC is the sole non-U.S. company within the American AI semiconductor ecosystem. This raises an important question: why has the U.S. placed such heavy reliance on TSMC?

2.1  Using TSMC to Bridge Intel’s Manufacturing Gap

TSMC serves as the technological foundry within the U.S. “sovereign supply chain.” While this position appears crucial, it is also a highly risky intermediary role. The U.S. aims to strengthen Intel but must simultaneously compensate for its technological lag. Through a “critical gap-filling policy”, the U.S. leverages TSMC’s U.S. operations to sustain the overall AI semiconductor ecosystem.

In other words, the U.S. strategy is to have TSMC temporarily fill Intel’s manufacturing gap, gaining 5 to 10 years for Intel to catch up technologically. We have previously suggested that a potential response from TSMC could be acquiring part of Intel’s advanced manufacturing fabs (though TSMC currently has no such plans).

TSMC’s role can be likened to a metaphor: If the U.S. AI semiconductor ecosystem is a castle, TSMC is the only gateway to the inner stronghold. Currently, the U.S. needs TSMC to guard this gate. However, once Intel becomes strong enough, will this gateway remain—or will it be dismantled entirely? This question will be further explored in the final section.

2.2  The U.S. Steering the Supply Chain Toward Closure

TSMC’s Arizona plant is positioned as a “strategic partnership” with the U.S. government, which is why the U.S. has emphasized the importance of an R&D center. However, while TSMC has committed a $100 billion investment in U.S. manufacturing, it has resisted fully transferring its most advanced technologies. The key reason lies in the evolving trajectory of the global supply chain.

The U.S. AI semiconductor supply chain is increasingly moving toward greater closure, which poses a long-term risk to TSMC. Historically, TSMC’s competitive edge has been built on a globalized supply chain, but as the supply chain becomes more self-contained, TSMC’s bargaining power will be substantially weakened. This is why TSMC CEO C.C. Wei has repeatedly stressed the importance of resilience—TSMC recognizes that if the global supply chain becomes fragmented, its leverage and market influence will be significantly challenged.

3.  The Hidden U.S. AI Manufacturing Chain

3.1  The True Focus of the U.S. Strategy: Materials and Equipment

Let’s begin with two publicly available yet less-known pieces of information. First, in 2023, Applied Materials announced the establishment of an EUV material R&D center in Arizona; second, in 2024, the U.S. government provided a $310 million grant to Lam Research for advanced packaging technology. What lies behind these actions? In reality, they are part of a larger plan to revive high-tech heavy industries. While the U.S. AI industry’s spotlight often focuses on OpenAI’s product launches, NVIDIA’s soaring stock prices, or TSMC’s Arizona plant investments, the true driving forces behind future AI sovereignty lie in Applied Materials’ photoresist formulations, Lam Research’s atomic layer deposition equipment, and DuPont’s EUV photoresist material plants. In other words, the U.S. AI manufacturing chain is gradually taking shape, with companies like Applied Materials, Lam Research, and DuPont playing a key role in constructing the U.S. AI Industrial Complex.

3.2  Highly Vertically Integrated Closed Systems Are Key

To understand the backbone of this ecosystem, we need to examine the roles of companies like Applied Materials, Lam Research, TSMC, OpenAI, and NVIDIA, and how the U.S. government uses subsidies and policy incentives to integrate them into its supply chain. For clarity, we’ll use a three-tier framework to show how the U.S. is leveraging policies and industrial alliances to forge a tightly integrated closed system.

3.2.1  Materials and Equipment Layers

Continuing with the metaphor of the U.S. AI semiconductor ecosystem as a “castle,” Lam Research’s etching and cleaning equipment, Applied Materials’ thin-film deposition equipment, along with advanced photoresists from companies like Entegris, serve as the gatekeepers of this castle, guarding the U.S. key technologies in semiconductors. The control over these technologies represents the “invisible hegemony” of the U.S. in the global semiconductor competition. Since the U.S. cannot fully control photolithography machines (ASML), strengthening its control over materials and equipment has made all advanced processes reliant on critical materials and equipment supplied by U.S. companies. This means that even TSMC, with its advanced manufacturing processes, would face a bottleneck if the U.S. decided to cut off the supply of equipment or materials.

3.2.2  Manufacturing Layer

In the advanced process field, TSMC is the only foundry capable of mass-producing 3nm and 2nm processes globally. However, the U.S. government’s goal in supporting local foundry Intel is to close the technological gap, as Intel is at least two generations behind TSMC. As mentioned in the section “TSMC’s Critical Role,” the U.S. strategy is not to replace TSMC with Intel but to support TSMC’s U.S. plants to bridge the gap while allowing Intel to gradually catch up with the technological disparity.

3.2.3  Design Layer

This layer represents the core of AI hardware and software architecture. The emerging key players are OpenAI and NVIDIA. OpenAI, through its ChatGPT and GPT series, defines the computational patterns of AI workloads (based on Transformer models); NVIDIA, with its CUDA platform and GPUs, leads the design of AI chip hardware architecture. These two companies together drive the co-design of hardware and software, locking in AI chip design from the start to NVIDIA’s hardware architecture. In other words, once OpenAI’s model becomes the industry standard, NVIDIA automatically becomes the hardware standard for global AI chips. This structure creates an industry-binding effect, which is not merely the result of market competition.

3.3  The Landscape of the U.S. AI Industrial Complex

After deconstructing the U.S. AI semiconductor ecosystem, it becomes clear that the U.S. plans to control three key areas of the AI semiconductor supply chain: materials, equipment, and design. The goal is to build a closed AI semiconductor ecosystem. While this vision will take time to fully materialize, the critical factor lies in whether U.S. equipment and materials suppliers, along with Intel, can rise to the challenge. Their success will determine whether the U.S. can establish a complete AI semiconductor sovereign supply chain. The U.S. goal is not to monopolize the global semiconductor industry, but rather to rebuild a national security-driven semiconductor ecosystem through the AI technological revolution.

3.4  Restricting China’s Access to Advanced Chips

As previously mentioned, the U.S. is not only building the AI semiconductor ecosystem through geopolitical, industrial competition, and supply chain restructuring but also reshaping the global supply chain power structure. Another critical objective is to prevent China from accessing advanced chips. However, the U.S. doesn’t intend to entirely block China from acquiring AI chips—this would not prevent Chinese companies from obtaining the latest chips. The strategy is to create multiple technical barriers that gradually isolate China from the global technology competition, ensuring it remains two generations behind the U.S. This containment strategy can be broken down into three layers:

3.4.1  Materials and Equipment Layers

By controlling key semiconductor technologies from companies like Lam Research, Applied Materials, and Entegris, and collaborating with ASML, the U.S. ensures that China cannot independently manufacture advanced-process chips.

3.4.2  Manufacturing Layer

Through subsidies and technological cooperation with TSMC, the U.S. ensures that TSMC does not transfer its most advanced packaging technologies to other countries, limiting China to using 7nm process chips.

3.4.3  Design Layer

With technical barriers like CUDA and Transformer technologies, the U.S. ensures that China cannot independently develop AI chip architectures.

4.  Discussion: The Future of AI Semiconductor Supply Chains

When we shift our focus from the technical specifications of chips to the entire supply chain structure, a striking phenomenon emerges: the competition in the U.S. AI industry is not limited to technological development but seems more like a global re-coding process. The U.S. aims to establish an autonomous AI semiconductor supply chain, but will this ecosystem truly remain fully closed as planned?

Several structural challenges are unavoidable, including: high domestic production costs in the U.S., the delicate balance of technology transfer and talent mobility, and the potential backlash from the advanced chip blockade against China during the de-risking process. These factors are commonly seen as important variables that could affect the development of this blueprint.

Therefore, in this discussion, we will focus on two key points that are often overlooked: TSMC’s dual role and Taiwan’s central position in supply chain management. We believe these two factors will play a crucial role in the future AI industry ecosystem.

4.1  TSMC’s Dual Role

Currently, industry discussions about TSMC largely remain centered on its role as “the foundry for the world’s most advanced processes.” However, from the perspective of the complex AI industry ecosystem, TSMC’s role is quietly evolving. It is no longer just a technology supplier but is beginning to act as a supply chain arbiter.

This shift can be attributed to three factors:

First, the time lag in the U.S. establishing domestic manufacturing capacity. Even with the semiconductor plant in Arizona running at full speed, it will take at least 3 to 5 years before stable production can be achieved.

Second, the bottleneck in advanced processes. Even if the U.S. heavily invests in its own capacity, it will still rely on TSMC’s expertise in 2nm and advanced packaging technology. This transforms TSMC from a “pure producer” to a “strategic controller of manufacturing.”

Finally, TSMC’s CoWoS (Chip-on-Wafer-on-Substrate) technology and influence in advanced packaging should not be overlooked. This technology is critical for AI accelerator chips (such as the NVIDIA H100), and TSMC holds a 90% market share in this area. While the U.S. actively rebuilds its semiconductor manufacturing capabilities, it has not prioritized packaging technology as a core policy, which has become a breakthrough point allowing TSMC to maintain its irreplaceability. Even if the U.S. successfully establishes its own production lines, it will still need TSMC for final packaging and integration.

Thus, in the next decade, whether Intel rises or TSMC maintains its leadership, TSMC’s role in the AI semiconductor ecosystem will be indispensable.

4.2  Taiwan as the Hub of Supply Chain Management

The U.S. aims to build an autonomous AI semiconductor supply chain through subsidies and reshoring of manufacturing. However, a complete AI industry ecosystem not only requires domestic manufacturing capabilities but also two invisible core nervous systems: one is Ecosystem Integration, the strategy of the U.S., and the other is Supply Chain Orchestration, which requires cooperation from Taiwan and other countries.

If we compare the U.S. semiconductor ecosystem to a sovereign island under construction, Taiwan and other countries’ roles are akin to the nervous system connecting this island to the global supply chain. They may seem insignificant but are crucial for the overall operation. Therefore, what truly determines the direction of the supply chain is often those seemingly minor but highly flexible and irreplaceable roles.

Although the U.S. is striving to establish a sovereign supply chain, each link in this chain still requires cross-national cooperation and coordination among various companies. Taiwan is not only a manufacturer but also plays a pivotal role in packaging, testing, and supply chain coordination.

This central role does not necessarily rely on cutting-edge technology but is instead based on a deep understanding of and coordination within the supply chain network. This is an advantage that Taiwan has cultivated over time in its industry. Just as in the semiconductor sector, key technological advantages often lie in the lesser-known stages rather than the most visible advanced processes.

This also makes us reconsider the concept of industrial sovereignty: compared to China’s sovereignty-building, which is policy-driven (through government resources invested across the entire industry chain), the U.S. sovereignty-building is geographically driven (by reshoring manufacturing). However, for the ecosystem to thrive, the key lies in technology and supply chain management. This may represent a more flexible form of “Networked Sovereignty” rather than one achievable through a closed ecosystem. It requires embedding itself in critical nodes of the global supply chain to continue thriving.

This article is part of our Global Business Dynamics series.
It explores how companies, industries, and ecosystems are responding to global forces such as supply chain shifts, geopolitical changes, cross-border strategies, and market realignments.

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