China’s domestic chip ecosystem is accelerating even as US export controls tighten. With tungsten up 557% and Nvidia’s China share halving, we map the permanent splitting of the global semiconductor supply chain.The global semiconductor supply chain is bifurcating. This statement was contested in 2023, hedged in 2024, and is now — as of 2026 — treated as a structural baseline by supply chain strategists, chipmakers, and government planners on both sides of the Pacific. The question has shifted from whether the split will happen to how deep and permanent it will become.

The evidence is visible in multiple datasets simultaneously. Nvidia, which once commanded over 90% of the Chinese AI chip market, had seen that share decline to approximately 50% by early 2026 — not because US export controls had successfully denied China access to capable chips, but because the combination of tariffs, “buy local” mandates, and regulatory uncertainty had accelerated Chinese enterprises’ migration to domestic alternatives. Meanwhile, China’s semiconductor output surged 87% year-on-year in May 2026, underscoring that domestic production capacity was advancing at a pace that few had forecast five years ago.

The Tungsten Shock: A Materials Leverage Beijing Chose to Use

In February 2026, China added tungsten to its export control list as trade tensions with the United States escalated. The consequence was rapid and severe. Tungsten prices rose 557% in just over a year — outperforming gains in gold, copper, and oil by a wide margin. Chinese exports of restricted tungsten products fell approximately 40% in 2025. The strategic logic was precise: China controls roughly 79% of global tungsten mine production, and tungsten’s exceptionally high melting point and density make it an essential input for chipmaking — both in chips themselves and in multiple fabrication processes at advanced nodes.

The move demonstrated that materials leverage extends far beyond rare earths. For semiconductor supply chains already under AI-driven demand stress, the tungsten shock added a new category of critical bottleneck that western efforts to build alternative supply chains cannot resolve in the near term.

Nvidia’s Paradox: Export Controls and the H200 Restart

The Nvidia-China relationship in 2026 illustrates the inherent contradiction of export controls applied to commercially motivated technology companies. After a roughly ten-month freeze on advanced chip exports to China — during which Nvidia absorbed a $5.5 billion charge tied to stranded inventory — a December arrangement allowed H200 sales to approved Chinese customers, with the US government taking a 25% cut of revenues. The arrangement normalised commerce while creating a fiscal mechanism for the US government.

Chinese tech firms collectively placed orders for more than two million H200 units for 2026 delivery — a volume that simultaneously demonstrates unmet demand and the limits of export control effectiveness. Where legal channels are closed, demand finds other pathways: a DOJ indictment unsealed in 2026 detailed a scheme involving approximately $2.5 billion in Supermicro servers containing restricted Nvidia GPUs being smuggled to Chinese buyers.

China’s Domestic Progress: Real but Incomplete

China’s semiconductor self-sufficiency ambitions are advancing, but the trajectory is uneven across subsectors. SMIC and Hua Hong have made genuine progress at mature nodes. Equipment vendors Naura and AMEC are gaining market share globally. The country’s AI chip domestic alternatives — while not yet matching Nvidia’s leading-edge capability — are advancing at an accelerating pace under the pressure of necessity.

The critical constraint remains high-bandwidth memory. CXMT, China’s domestic HBM producer, is targeting viable HBM3 yields in 2026 and HBM3E by 2027. If those milestones are achieved on schedule, Nvidia’s current China advantage — which exists precisely because China’s domestic HBM production remains constrained — will narrow materially. The competitive window is real but finite.

The Strategic Implication: Permanent Bifurcation as Business Baseline

For supply chain strategists, the most consequential shift is not any individual export control or price spike — it is the recognition that the global semiconductor supply chain’s bifurcation is permanent. Semiconductor leaders navigating this environment most effectively are treating the US-China bifurcation as a structural feature of the landscape, not a temporary disruption awaiting resolution.

This means conducting detailed audits of supplier dependencies, stress-testing revenue models against scenarios where China access is restricted or structurally changed, and tracking China’s domestic chip progress as a competitive variable rather than a geopolitical curiosity. Revenue projections that assume stable China market access now carry geopolitical risk that most financial models have not historically priced.

The age of a single, integrated global semiconductor supply chain is over. The question is how many chains will replace it, and at what cost.

Morgan Stanley estimates AI-related global debt issuance will hit $570 billion in 2026, with hyperscaler spending exceeding $1 trillion by 2027. Oracle’s crisis may be the first systemic warning sign.
The question Wall Street was reluctant to ask openly throughout 2024 and most of 2025 is now unavoidable: is the AI infrastructure buildout generating a debt burden that markets have not yet properly priced?

The numbers have become too large to dismiss as routine capital expenditure cycles. Morgan Stanley estimates that AI-related global debt issuance will more than double to nearly $570 billion in 2026, with aggregate hyperscaler capital expenditure projected to exceed $1 trillion by 2027. That figure encompasses spending by Amazon, Microsoft, Alphabet, Meta, Oracle, and a growing constellation of second-tier infrastructure providers building the physical layer of the AI economy.

How the Debt Stack Has Built

The trajectory of Oracle’s balance sheet is instructive as a case study in the speed at which leverage can accumulate. In fiscal 2025, Oracle carried a net cash deficit of approximately $394 million after free cash flow. By the end of fiscal 2026, that had deteriorated to negative $23.7 billion in free cash flow, with long-term debt reaching approximately $124.7 billion. Capital expenditures of $55.7 billion in a single fiscal year represent a 162% increase from the prior year.

Oracle is not alone, though its position is the most stretched. The structural dynamic across the hyperscaler complex is that the companies investing most aggressively in AI data centre capacity are simultaneously facing competitive pressure on their existing software and cloud businesses from AI-native tools — creating a margin squeeze that occurs precisely when cash demands are highest.

Credit Default Swaps as an Early Warning System

One underappreciated signal in this cycle is the behaviour of credit default swaps. Fortune reported that Morgan Stanley’s Lisa Shalett flagged Oracle’s CDS widening as a potential early indicator of broader AI trade stress. CDS spreads — which function as insurance premiums against corporate default — had reached record levels for Oracle by early 2026, even before the most recent earnings-related stock decline.

The concern Shalett articulated was systemic rather than company-specific: “If people start getting worried about Oracle’s ability to pay, that’s gonna be an early indication to us that people are getting nervous.” For a company whose debt is included in major corporate bond indices, the widening of Oracle’s CDS spreads has implications not just for Oracle investors but for anyone holding investment-grade credit exposure broadly.

Bank of America Research described “the lack of clarity on hyperscaler borrowing” as “the key risk going into 2026” — a view validated by subsequent events as Oracle’s stock collapsed and CDS widened even further.

The OpenAI Nexus

A critical vulnerability embedded in the current AI infrastructure cycle is concentration around OpenAI as both the defining customer and the primary justification for hyperscaler spending. Oracle‘s remaining performance obligations are concentrated at least $300 billion in the OpenAI relationship. OpenAI itself is burning cash at what one analyst described as “an insane rate” and has committed to more than $1.4 trillion in total AI buildouts — a commitment that depends on the company’s own ability to sustain fundraising and ultimately generate revenue at scale.

The logical chain from that dependency is a concern articulated plainly by Melius Research: “It is hard to know if Oracle can stick to this capex plan if incremental business arises from the likes of OpenAI and Anthropic. Also, its competitors are unlikely to slow spending and could use Oracle’s spending moderation as the means to gain share.” The competitive dynamic creates a collective action problem: no single hyperscaler can slow down without ceding ground, yet the collective pace of spending is generating balance sheet stress across the sector.

Second-Order Vulnerabilities: Data Centre REITs and Chip Suppliers

The debt accumulation in hyperscaler balance sheets has second-order effects that are not captured in the headline AI capex numbers. Data centre real estate investment trusts — which provide the physical infrastructure that hyperscalers increasingly lease rather than own — have their own exposure to counterparty concentration and lease extension risk. Reports that Blue Owl, Oracle‘s primary data centre financing partner, declined to back the Michigan facility highlighted the fragility of the supporting ecosystem even when the primary tenant appears solvent.

Nvidia, whose chips underpin the entire AI buildout, has been insulated from these concerns by persistent demand that exceeds supply. But if even two or three hyperscalers simultaneously scaled back data centre spending in response to balance sheet pressures, the chip demand outlook would shift rapidly.

The Memory Shortage as Collateral Signal

CNBC reported in late June 2026 that “the memory shortage shaking Apple and Microsoft is an ‘existential crisis’ for smaller players” — a reminder that supply chain bottlenecks are not yet resolved, adding cost and execution risk to projects whose timelines are already being stretched. The combination of persistent demand exceeding supply, expensive debt financing, and uncertain monetisation schedules creates a financial engineering challenge that may prove harder to solve than the engineering challenges of building the data centres themselves.

The AI infrastructure cycle is not necessarily a bubble in the sense of zero underlying demand — the use cases are real and adoption is accelerating. But the debt structure being used to finance it, and the concentration of risk around a small number of foundational relationships, has introduced systemic vulnerabilities that markets are only beginning to price.

The World Bank projects global growth at 2.5% in 2026, the weakest since the pandemic, as the US-Iran conflict drives energy price spikes, inflation, and tighter monetary policy worldwide.The World Bank’s mid-2026 baseline carries a number that markets have had to absorb slowly: global GDP growth of 2.5% this year — the weakest since the pandemic — and the culprit is clear.

The World Bank’s latest Global Economic Prospects report identifies the US-Iran conflict that began in late February 2026 as the central shock reshaping the international economic outlook. Energy prices have risen sharply, inflation has re-accelerated across multiple continents, and central banks that had been on the verge of easing cycles have instead begun signalling hikes. The combination has compressed household incomes, widened fiscal deficits, and created a global policy dilemma — fight inflation or protect growth — that has no clean answer.

The Anatomy of the Slowdown

Emerging market and developing economies (EMDEs) face what the World Bank characterises as their weakest per capita income growth since the pandemic era. Growth is projected to decelerate across all EMDE regions in 2026, with the Middle East, North Africa, Afghanistan, and Pakistan bearing the worst damage given direct exposure to the conflict, higher energy import costs, and disrupted shipping. South Asia remains the fastest-growing EMDE region but has nonetheless seen forecasts revised downward.

The mechanism of transmission is threefold. Direct energy price exposure drives headline inflation and suppresses real consumer spending. Disruptions to Strait of Hormuz shipping — which handles roughly 20% of global oil trade — have compressed supply chains and added a risk premium to shipping costs more broadly. And the expectation of prolonged tighter monetary policy has pushed sovereign borrowing costs higher for indebted developing economies.

The Rio Times Global Economy Briefing captured the daily rhythm of the uncertainty: “Whether the US-Iran ceasefire holds. Renewed strikes would push oil higher and add to the inflation problem the Fed is already confronting.” As of the week of June 28, markets remained on edge about the durability of the ceasefire following reports of Iranian targeting of US military assets, which temporarily pushed Brent crude higher and triggered a brief equity sell-off before the market recovered.

Advanced Economies: Slow But Not Collapsing

Advanced nations face a different but related challenge: growth that was already below trend has been further dragged by energy costs and the policy response to inflation. Deloitte’s 2026 Global Economic Outlook noted that after years of disruptive US trade policy, the global trading system has partially reorganised — with numerous bilateral trade deals struck between non-US countries as an alternative to the US-centric framework.

France is projecting GDP growth of just 0.9% in 2026, according to Banque de France, with the contribution of net exports turning negative. Germany and Japan face their own exposure to the China Shock 2.0, as Chinese high-tech exports crowd into categories where both countries previously held competitive advantage. The US itself is navigating a narrowing current account deficit that reflects weaker domestic demand rather than export strength — an ambiguous signal that the Federal Reserve has explicitly flagged as complicating its rate decisions.

Fiscal Pressure and the Poverty Gap

One consequence of the conflict-driven slowdown that policy discussions often underweigh is the distributional impact on the world’s poorest economies. Low-income countries are projected to grow at 5.4% in 2026 — 0.3 percentage points below prior forecasts — as energy import costs consume fiscal space that would otherwise go to infrastructure, healthcare, and education. The World Bank projects that gains in per capita income, averaging 2.7% annually through 2027–28, will be “insufficient to significantly reduce poverty” given the breadth of the setback.

Fiscal pressures will limit governments’ ability to reduce food insecurity and create jobs — a combination the World Bank regards as a medium-term political risk as well as a humanitarian one. A newly identified Ebola outbreak in a low-income economy adds a further downside tail to the forecast.

The 2027 Recovery Thesis

The World Bank’s forward guidance is that a recovery should materialise in 2027–28, driven by an assumed decline in energy prices as supply adjusts and the conflict’s acute phase passes, and a rebound in global trade activity. That recovery is explicitly conditional on the ceasefire holding and conflict not escalating to involve Gulf oil infrastructure more directly. Recoveries are projected across all EMDE regions in 2027–28, but the pace will depend heavily on policy buffers — many of which were depleted fighting the post-pandemic inflation.

The upside scenario, acknowledged in the World Bank report, involves broader AI adoption lifting productivity and economic activity. Estimates of the productivity impact of AI vary “widely,” and the report notes that different scenarios “could lead to markedly different growth paths.” The AI tailwind is real but front-loaded in advanced economies, and access to the technology in lower-income countries remains constrained by infrastructure gaps and digital divides.