Semiconductor Manufacturing International Corp (SMIC) said the global artificial intelligence boom is increasingly pushing overseas chip orders toward Chinese factories as foreign foundries divert production capacity to high-margin AI processors and advanced memory products.

The comments from China’s largest contract chipmaker provide one of the clearest indications yet that the worldwide AI infrastructure race is beginning to reshape the broader semiconductor manufacturing landscape far beyond cutting-edge AI chips themselves.

Speaking during an earnings call on Friday, SMIC co-chief executive Zhao Haijun said many foreign customers are now turning to China because capacity for mature or legacy semiconductor production overseas is tightening sharply.

“There are still quite a lot of semiconductor capacity expansion projects and companies in China,” Zhao said.

“These are among the few places with available production capacity, so we are seeing many overseas customers shift their orders to be manufactured in China.”

He added that SMIC, as China’s largest domestic foundry, was likely capturing a significant share of that redirected demand.

“This is happening across the board,” Zhao said.

The remarks highlight a major secondary effect emerging from the AI investment boom. As companies such as Nvidia, Advanced Micro Devices, and hyperscale cloud providers dramatically increase orders for advanced AI processors and high-bandwidth memory, global foundries are reallocating manufacturing resources toward those more profitable products.

That shift is squeezing capacity for older-generation semiconductors used in automobiles, industrial equipment, consumer electronics, appliances, and a wide range of everyday technologies.

The result is creating an unexpected opening for Chinese foundries specializing in mature-node manufacturing.

“Some products that were previously made at overseas foundries are no longer being produced there,” Zhao said.

The development is important because it may accelerate China’s role in global semiconductor supply chains even as the United States intensifies efforts to restrict Beijing’s access to advanced chip technology.

Pushing Through Emerging Paradox

While China still faces major obstacles in cutting-edge semiconductor manufacturing because of U.S. export controls, the country is rapidly strengthening its position in legacy and mature-node production. According to data cited from Semicon China, Chinese foundries’ share of global capacity for legacy-node chips in the 22-nanometre to 40-nanometre range is expected to rise to 37% this year and 41% by 2027, up from 32% in 2025.

Those chips may not attract the same attention as advanced AI processors, but they remain essential to global manufacturing supply chains and account for enormous production volumes across multiple industries.

The AI boom is therefore creating a paradoxical outcome for the semiconductor industry. On one hand, Washington’s export restrictions are designed to slow China’s technological progress in advanced chips. On the other hand, the global scramble for AI capacity is indirectly strengthening Chinese foundries in mature-node manufacturing because non-AI products are being crowded out elsewhere.

SMIC itself has been expanding aggressively to capitalize on that opportunity. The company added 9,000 12-inch equivalent wafers of production capacity during the first quarter and continues to build new fabrication facilities despite mounting geopolitical and technological pressures.

Its expansion comes as Chinese authorities push heavily for semiconductor self-sufficiency amid intensifying technology tensions with the United States. Beijing has prioritized domestic chip production through subsidies, financing support, and industrial policy initiatives aimed at reducing reliance on foreign suppliers.

SMIC sits at the center of that strategy.

The company has also been attempting to move into more advanced 7-nanometre manufacturing, although those efforts remain constrained by U.S. restrictions on access to advanced lithography equipment and semiconductor tools.

Despite those limitations, analysts say China’s growing dominance in mature-node chips could still give the country significant leverage in parts of the global electronics ecosystem.

The economics of expansion, however, are becoming increasingly costly. Zhao said SMIC expects depreciation expenses to rise roughly 30% this year as new factories and equipment come online. First-quarter depreciation and amortization expenses were already up 26% from a year earlier.

SMIC’s utilization rate stood at 93% in the first quarter, slightly below levels recorded in late 2025.

Zhao attributed part of the decline to temporary order reductions from smartphone manufacturers concerned about shortages in memory chip supply.

“In the fourth quarter of last year, smartphone makers cut orders because they were worried about shortages of supporting memory chips and part of that impact carried into the first quarter,” he said.

“At the same time, new fabs began operations in the first quarter, which increased total capacity and made utilization appear lower.”

As memory manufacturers and foundries prioritize AI-related demand, supply imbalances are emerging elsewhere across the electronics sector, affecting smartphones and other consumer devices.

China remained SMIC’s dominant market, accounting for 89% of first-quarter revenue, while the United States contributed 9%. The company shipped 2.5 million 8-inch equivalent wafers during the quarter, unchanged from the previous three months.

The relatively stable shipment volumes suggest that SMIC’s current expansion is being driven less by sudden surges in unit demand and more by the repositioning of global semiconductor manufacturing capacity.

The broader implication is that artificial intelligence is no longer merely driving demand for advanced chips. It is now restructuring the economics and allocation of the entire semiconductor industry. Factories globally are increasingly prioritizing AI accelerators, high-bandwidth memory, and data-center hardware because of their superior margins and explosive growth prospects.

That leaves less room for legacy semiconductor products and creates opportunities for Chinese foundries to absorb displaced production.

“As demand for AI-related chips and edge applications keeps growing next year, it could further squeeze capacity for non-AI products,” Zhao said.

“We believe this is a long-term trend.”

If that assessment proves correct, China’s semiconductor sector may end up benefiting from the AI boom in ways that go beyond Beijing’s original strategic calculations.

Anthropic has delivered one of the most direct and urgent warnings yet from a leading AI lab, stating that the United States can still lock in a meaningful 12- to 24-month advantage in frontier AI capabilities over China — but only if it moves immediately to close critical loopholes in chip exports and prevent advanced model distillation.

In a detailed post published Thursday, Anthropic outlined two starkly different scenarios for the global AI industry in 2028. In one, the US and its allies successfully tighten controls, preserving technological superiority. In the other, continued leaks in hardware and knowledge allow China to rapidly close the gap or even pull ahead in key areas.

How China Is Closing the Gap

Anthropic highlighted two main vectors accelerating China’s progress:

• Persistent weaknesses in chip export controls, despite existing restrictions, allow Chinese entities to access advanced computing hardware through loopholes, smuggling, or third countries.
• Distillation attacks, a technique in which Chinese labs use powerful Western “teacher” models (such as Anthropic’s Claude) to train smaller, more efficient “student” models. This process enables rapid capability transfer with far less compute than originally required.
• The company stressed the narrow window of opportunity: “If the US and its allies act now to address both issues, it may be possible to lock in a 12-24 month lead in frontier capabilities.”

It added a blunt note of urgency: “The window of opportunity to lock in that lead will not necessarily remain open for long.”

Why Maintaining the Lead Matters

Anthropic framed technological superiority as essential not just for economic or military advantage, but for the safe development of AI itself. A close “neck-and-neck” race, the company argued, would create dangerous incentives for both sides to rush model releases while cutting corners on safety testing and alignment research.

“A neck-and-neck race between American and Chinese AI labs could make industry and government-led safety and governance efforts more difficult,” it said.

This concern aligns with Anthropic’s founding mission, which emphasizes constitutional AI and responsible development. In a tight competition, the pressure to deploy ever-more-powerful systems faster could outweigh caution, raising risks of unintended consequences, misuse, or loss of control.

The post also carried a direct message about protecting hard-won advantages: “Our past success means that our present task is largely to avoid squandering our advantage: to decide not to make it easier for the CCP to catch up.”

Policy Recommendations

Anthropic called for immediate policy actions, including:

• Strengthening and expanding chip export controls
• Significantly increasing enforcement budgets and resources
• Developing specific measures to detect and prevent large-scale distillation of frontier models

The warning comes at a sensitive geopolitical moment. It was published on the same day President Donald Trump met with Chinese leader Xi Jinping in Beijing, Trump’s first visit to China since 2017, accompanied by a powerful delegation of American tech executives, including Elon Musk, Tim Cook, and Jensen Huang.

The juxtaposition highlights the tension between commercial interests (market access and revenue in China) and national security imperatives. While companies like Nvidia continue to seek controlled sales to China, Anthropic’s intervention underscores the cost of overly permissive policies.

However, not all experts agree with Anthropic’s assessment of the gap. In April, former ByteDance engineer Zhang Chi, now at Peking University, argued that China is actually falling further behind due to chronic shortages of high-quality training data and restricted access to the most advanced chips.

Nevertheless, Anthropic’s perspective carries significant weight given its deep technical expertise and front-row seat in the frontier AI race.

Maintaining even a modest multi-year lead could have profound consequences. It would give the US and its allies more time to shape global AI norms, standards, and safety frameworks aligned with democratic values.

Militarily, it would preserve advantages in autonomous systems, intelligence analysis, and cyber capabilities. Economically, it would help ensure that the enormous productivity gains and new industries created by advanced AI are disproportionately captured by open societies.

Conversely, some analysts believe that losing the lead could accelerate authoritarian applications of AI, complicate efforts to manage existential risks, and shift the global balance of power. A true arms-race dynamic would likely reduce overall safety investment across the industry.

Anthropic’s call to action is therefore seen as a reflection of a growing consensus among some frontier labs that the era of relatively open AI development is ending. The challenge for policymakers is to implement targeted, enforceable controls without stifling American innovation or triggering unintended escalations.

Adam Smith’s The Wealth of Nations (published in 1776) remains one of the foundational texts of modern economics. It shifted humanity’s understanding of wealth away from merely accumulating gold and treasures toward productivity, labor, specialization, and trade. It introduced enduring concepts such as the Invisible Hand and the Division of Labor.

On the Invisible Hand, Smith argued that individuals pursuing their own self-interest within a free market can unintentionally create broad benefits for society by driving innovation, efficiency, and value creation. On the Division of Labor, he explained that breaking production into specialized tasks dramatically increases productivity and expands overall wealth. He also criticized excessive government interference through tariffs and monopolies, arguing that natural competition often allocates resources more efficiently.

OA Lawal did an exceptional job teaching many of us these ideas through O’Level Economics textbooks. But for me, things evolved when I entered Federal University of Technology Owerri (FUTO) as an undergraduate.

There was a course called Polity and Economy of Nigeria; if memory serves me right, GST 108. Like the Logic and Philosophy course, this one expanded many constructs carried from secondary school. The Professor introduced another variable into the equation: Power. She noted that Nigeria was running a Mixed Economy.

She explained Wealth. Then she explained Power. And somewhere in that lecture came a statement that shocked me: much of Nigeria’s government revenue came not from crude oil, but from taxation and broader economic activities around it. Good People, education truly liberates the mind because great learning rearranges assumptions.

Today, see this photo from Trump’s trip to China; Power vs Wealth. And in many ways, Power appears to win. Power is seated; Wealth is standing. Why? Because Power is concentrated. It commands attention. It can direct resources and shape outcomes rapidly. But political power, especially in a democracy, is often transient. Within a few years, many seated around today’s tables of power may exit those positions.

Wealth behaves differently. Foundational wealth often compounds over decades. It continues producing influence long after political cycles expire. While wealth may not possess the concentrated force of political power at a specific moment, it carries an enduring form of power of its own.

Of course, some individuals possess both Power and Wealth simultaneously.

If I model political power mathematically, I often see a Gaussian curve: it rises, stabilizes briefly, and eventually declines. Wealth, especially productive wealth, can continue compounding over time. Nations therefore require both. Development is rarely driven by Power alone or Wealth alone. The real challenge is optimization: creating a healthy balance where institutions provide direction while wealth creation sustains prosperity.

Because Power has clocks.

But Wealth has time.