Analysis

How China Forgot Karl Marx: The Chinese Economy Runs on Labor Exploitation

Published

3 months ago

March 26, 2026

In the early 1980s, something extraordinary was happening in rural China. Incomes were surging. Families who had known only collective poverty under Mao Zedong’s commune system were suddenly trading at market prices, leasing land, and tasting prosperity for the first time in a generation. To most observers — Western economists, development agencies, awed foreign correspondents — this was an unambiguous miracle. But inside the halls of the Chinese Communist Party, one senior official was deeply unsettled by what he saw.

His name was Deng Liqun — no relation to Deng Xiaoping, China’s paramount leader who had initiated these reforms — and he was alarmed not by poverty, but by its opposite: the emergence of rural businesses hiring large numbers of workers. Citing Das Kapital directly, Deng Liqun invoked Marx’s analysis of surplus extraction and warned his colleagues that China was breeding a new exploiter class from within the revolutionary state itself. His warnings were dismissed, sidelined, or quietly buried. Forty years later, as Chinese factory workers report daily wages collapsing to less than 100 yuan amid a record export boom, the uncomfortable question is: was Deng Liqun right all along?

The Seven-Worker Loophole: When Marx Became a Management Consultant

To understand the ideological contortion at the heart of modern China, one must revisit a peculiar episode in the history of economic thought. As Deng Xiaoping’s reformers sought to legalize private enterprise in the early 1980s, they faced a Marxist problem: how could a Communist Party permit capitalist employers? Their solution was as creative as it was absurd.

Party theorists dug into Volume IV of Das Kapital and located a passage in which Marx cited the example of an employer with eight workers as the threshold at which genuine capitalist exploitation begins. The inference was swift and convenient: hire no more than seven workers, and you are not a capitalist. The “seven-worker rule” became, briefly, the ideological boundary between socialism and sin. As one analyst of the period put it, the Party had transformed Marx into a management consultant — and a lenient one at that.

The rule did not last. Entrepreneurs like Nian Guangjiu, the Shazi Guazi (“Fool’s Sunflower Seeds”) magnate, hired hundreds of workers and dared Beijing to intervene. Deng Xiaoping, pragmatist to the bone, let it pass. The seven-worker rule was quietly abandoned. China’s private sector began its long, relentless ascent.

But Deng Liqun continued to press his case. Throughout the 1980s, as China’s reformist faction consolidated power, he remained one of the party’s most vocal critics of market liberalization, warning that unchecked private capital would reproduce exactly the exploitative dynamics Marx had described. He was repeatedly outmaneuvered. He died in 2015, at age 99, largely forgotten — a curio of ideological defeat.

What he could not have known is that the data would eventually vindicate him.

The Numbers Behind the Narrative

China’s economic rise remains one of history’s most astonishing chapters. Hundreds of millions lifted from poverty. A GDP that expanded from a fraction of the United States’ to roughly 70 percent of it in nominal terms. The construction of entire cities from bare earth. No serious analyst dismisses this achievement.

But growth and fairness are different metrics. And on the metrics that matter most to a self-proclaimed workers’ state, the picture is quietly damning.

According to estimates by the International Labour Organization, China’s output per hour worked in 2025 stood at just $20 in constant international dollars — behind the global average of $23, and roughly on par with Brazil and Mexico. The United States, by comparison, registers $82 per hour. China does not achieve its manufacturing dominance through efficiency or technological leverage. It achieves it through sheer volume of hours — the kind of raw labor extraction that, as a recent analysis in Foreign Affairs argued, is precisely the dynamic Deng Liqun warned about four decades ago.

Income inequality tells an equally uncomfortable story. China’s official Gini coefficient stands at 0.47 — already above the internationally recognized warning threshold of 0.40, beyond which social instability becomes a material risk. But economists at Cornell University and Peking University, working with alternative datasets, place the true figure closer to 0.52, putting China in the company of some of the world’s most unequal societies. Meanwhile, data from Peking University’s China Development Report reveals that the top 1 percent of Chinese households own roughly one-third of the country’s property — a concentration of wealth that would have struck the founders of the People’s Republic as counterrevolutionary.

The public-private wage gap compounds the picture. According to data from China Briefing, the average annual urban wage in China’s public sector reached RMB 120,698 in 2023, while the average in the private sector — where the vast majority of Chinese workers are employed — was just RMB 68,340. Those who work for the state earn nearly twice those who do not. In a country that officially represents the proletariat, the proletariat is still on the outside looking in.

The Factory Floor in 2026

Abstract statistics find their most vivid expression on the ground. A Bloomberg investigation from March 2026 documented day laborers in Guangzhou waiting in winter cold for factory agents to offer work. One worker, Sheng, 55, described his income having more than halved to less than 100 yuan — roughly $14 — per day. Some workers cannot find employment for months at a time, he said. This is occurring while China posts record export numbers, defying the Trump administration’s escalating tariffs with a manufacturing juggernaut that continues to flood global markets.

The paradox is complete: the export machine hums, profits accumulate, trade surpluses swell — and the workers who power all of it are left behind. It is not incidental. It is structural. As China Labor Watch’s executive director Li Qiang argued in January 2026, China’s decisive competitive advantage lies in its weak labor protections, and it is now exporting this low-rights model globally — a race to the bottom dressed in the language of development.

Nowhere is this more starkly illustrated than in the platform economy. According to the All-China Federation of Trade Unions, the number of workers in “new forms of employment” — overwhelmingly gig-economy roles with minimal protections — surpassed 84 million in 2024, representing 21 percent of the total workforce. Among food-delivery riders on Meituan alone, nearly half worked fewer than 30 days per year, pointing to an army of precarious, intermittent laborers with no benefits, no unions, and no recourse. As of 2022, at least 70,000 of these riders held master’s degrees.

996, Involution, and the Vocabulary of Exhaustion

China’s young workers have developed their own lexicon for what Marxist theory would call surplus extraction. The “996” schedule — work from 9 a.m. to 9 p.m., six days a week — became the defining norm of China’s tech industry, a practice that a joint study by Chinese and Australian universities, published in October 2025, described as “modern labour slavery,” directly linking it to chronic burnout, mental health decline, and fertility postponement. Officially illegal under China’s Labor Law, 996 persists through what labor researchers describe as “informal-flexible despotism” — the unspoken threat of unemployment for those who refuse to comply.

The cultural response has been the phenomenon of neijuan, or “involution” — the sense of being trapped in relentless, self-defeating competition that produces no advancement. As youth unemployment reached 17.8% in July 2025 — six times the official urban headline rate — and this year’s graduating class of 12.22 million enters a trade-war-disrupted economy also disrupted by artificial intelligence, neijuan has metastasized from internet slang into political critique. Its counterpart, tangping — “lie flat” — is the passive resistance of those who have concluded that the system is designed not to reward their labor but to extract it.

These are not marginal, youth-culture curiosities. They are symptoms of a structural contradiction at the heart of the Chinese political economy: a party that claims to represent workers presiding over conditions that would have warranted a chapter in Volume I of Das Kapital.

Xi Jinping’s Marxist Revival: Signal or Noise?

Against this backdrop, Xi Jinping’s periodic invocations of Marxist rhetoric acquire a particular ambiguity. His “common prosperity” campaign, elevated in August 2021 as “an essential requirement of socialism,” set targets to reduce the Gini coefficient from 0.47 toward 0.40 by 2025 and 0.35 by 2035. The crackdown on tech giants — Alibaba, DiDi, Meituan — was framed in language recognizable to any student of Marx: reining in monopoly capital, redistributing to the people.

Yet the common prosperity campaign has conspicuously failed to deliver on its core promise. The Gini has not meaningfully declined. Minimum wages, while rising nominally, remain well below levels that would allow Chinese households to become the robust consumers the economy urgently needs. The crackdown on tech billionaires proved more politically convenient than structurally transformative: it punished visible wealth without redistributing it, and it chilled private investment without replacing it with workers’ power.

As CSIS’s Interpret: China project has noted, the common prosperity campaign’s success will ultimately be judged not by economics but by whether it can “maintain social harmony and stability” — which is to say, by whether the CCP can suppress the political consequences of inequality without addressing its material causes. That is not Marxism. That is its managed inverse.

The Overproduction Trap: What Karl Marx Got Right, and What China Ignored

Marx’s central warning in Capital was not simply about exploitation in isolation. It was about the systemic consequences of treating workers purely as inputs: overproduction crises, demand collapse, competitive race-to-the-bottom dynamics that ultimately undermine the capitalist system itself. He called it “the epidemic of overproduction.”

China in 2026 is exhibiting textbook symptoms. The electric vehicle sector’s median net profit margin collapsed to just 0.83% in 2024, down from 2.7% in 2019, as brutal price wars among BYD, Tesla, and dozens of domestic brands hollowed out margins. The solar manufacturing industry lost $40 billion to overcapacity. Steel, cement, food delivery — sector after sector is caught in the deflationary spiral that Chinese policymakers euphemistically call “involution” but that economists recognize as classic overproduction: too much supply chasing too little domestic demand, because workers who make the goods cannot afford to buy them.

The CCP’s own theorists have identified the root: household consumption remains stubbornly low as a share of GDP — hovering near 37-38 percent, compared with 68 percent in the United States and over 50 percent in most developed economies. The Foreign Affairs analysis draws the Henry Ford parallel with precision: Ford famously raised his workers’ wages so they could afford his cars. China’s economy does the reverse — it suppresses wages to make exports price-competitive, and then wonders why domestic demand refuses to ignite.

The Global Stakes: What China’s Labor Model Exports

The implications extend well beyond China’s borders. As China Labor Watch has documented, Beijing’s manufacturing dominance is now being actively exported through Belt and Road projects, industrial parks across Africa and Southeast Asia, and Chinese-owned factories in countries from Ethiopia to Cambodia. The labor conditions travel with the capital. A race to the bottom in labor rights is a deliberate feature, not an accident, of China’s industrial model — and it sets the competitive benchmark to which other manufacturing nations must respond or decline.

For Western policymakers, this reframes the trade debate. Tariffs address the symptom — price-competitive imports — without touching the cause, which is systematic wage compression underwritten by a state that suppresses independent unions, restricts collective bargaining, and classifies labor organizing as a political threat. The US-China trade war’s escalating tariff regime, which has seen duties on Chinese goods reach 145 percent, is economically disruptive for both sides. But it does not change the structural reality that China’s manufacturing advantage is built on a foundation that would have been recognizable to Friedrich Engels touring Manchester in 1845.

Conclusion: The Haunting of Deng Liqun

History’s ironies rarely arrive cleanly. Deng Liqun was, in many respects, a problematic figure — a hardliner who helped orchestrate ideological campaigns that silenced liberal reformers and contributed to the atmosphere of repression that culminated in Tiananmen. His Marxism was often a political instrument as much as a philosophical commitment.

But on this one point, his analysis was structurally sound: a Communist Party that permits unlimited private capital accumulation without empowering workers to claim a proportionate share of the value they create is not transcending Marx. It is fulfilling him. The exploitation he predicted has arrived — not in the form of Victorian factory owners with top hats, but in the form of platform algorithms calculating delivery routes to the nearest yuan, 996 schedules enforced through the threat of precarity, and a gig economy that has absorbed 84 million workers without offering a single one a union card.

Xi Jinping’s “common prosperity” rhetorical architecture is vast and elaborate. The material delivery, forty years after Deng Liqun’s warnings, remains insufficient. China’s economy runs on labor exploitation. Marx would have recognized it immediately. He would have found it almost unremarkable. What would have astonished him — what should astonish us — is that the party invoking his name is the one enforcing it.

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AI

AI Infrastructure Debt Bubble 2026: $570 Billion in Global Debt Issuance Raises Systemic Risk Alarm

Published

15 hours ago

June 28, 2026

Abdul Rahman

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.

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Analysis

Global Economic Growth 2026: World Bank Cuts Forecast to 2.5%

Published

16 hours ago

June 28, 2026

Abdul Rahman

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.

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Analysis

China Economy 2026: 87% Semiconductor Surge, Property Crisis

Published

19 hours ago

June 28, 2026

Abdul Rahman

China’s May 2026 data shows high-tech manufacturing up 15.1% while property investment fell 16.2%. How Beijing’s export-led gamble is reshaping global supply chains.

The National Bureau of Statistics’ May 2026 release confirmed what economists had begun calling China’s “industrial divergence.” Scale-above industrial value-added output grew 4.5% year-on-year in May, accelerating 0.4 percentage points from April, with high-tech manufacturing surging 15.1%. The semiconductor sector was the standout: domestic output jumped 87% from the prior year, while China’s exports of semiconductors were up 110% from a year earlier, exports of mobile phones climbed 44%, and automatic data-processing machines rose 66%.

The Export Engine Running at Full Throttle

China‘s May exports (denominated in US dollars) were up 19.6% from a year earlier — the second biggest monthly increase since January 2022. The first two months of 2026 had registered an extraordinary 39.6% gain. Over all of 2025, China recorded a trade surplus exceeding $1.2 trillion — the largest ever posted by any country — as manufactured goods, particularly in advanced technology categories, poured into global markets.

The strength carries a double driver. First, the global AI boom has generated extraordinary demand for semiconductors and related hardware, where China‘s manufacturing base has rapidly scaled. Second, as domestic demand softened, manufacturers redirected capacity toward export markets. Gary Ng, senior Asia Pacific economist at Natixis, characterised this as the operative dynamic: “China’s exports have decelerated as the Iran war starts to affect global demand and supply chains,” though he noted the moderation was from record levels.

China’s economy in mid-2026 resembles a dual exposure photograph — one frame showing a technology powerhouse outpacing global rivals, the other depicting a property market in structural retreat that is slowly draining household wealth.

Goldman Sachs had projected 5–6% annual growth in China’s exports and raised its 2026 real GDP forecast to 4.8% — above both IMF projections and Bloomberg consensus. That upgrade rested on the observation that Chinese exports demonstrated resilience even against elevated US tariffs that hit 100% in April 2025 before settling at 30% in May following a bilateral agreement. Chinese exports of chips, semiconductors, autos, and auto parts continued to expand despite the tariff headwinds.

The Property Hole That Will Not Close

The other side of the ledger is less encouraging. In the first five months of 2026, fixed-asset investment fell 4.1% year-on-year — the steepest decline since May 2020. Within that, property investment dropped 16.2%. Given that roughly two-thirds of Chinese household wealth is held in real estate, the wealth destruction is persistent and consequential. Consumers saving to restore depleted balance sheets rather than spending is the logical response — and it explains why domestic retail demand has been chronically soft despite headline economic growth of 5% in 2025.

The Economist Intelligence Unit’s Nick Marro captured the strategic bet underlying Beijing’s trajectory: “There’s a strong emphasis on doubling down on manufacturing and ensuring that China’s competitive positioning in global supply chains remains sticky.” China‘s 15th Five-Year Plan (2026–2030), approved in late 2025, explicitly prioritises advanced manufacturing, semiconductors, AI, renewable energy, and digital infrastructure — doubling down on supply-side transformation rather than demand-side stimulus.

The Global Spillover: China Shock 2.0

The US-China Economic and Security Review Commission flagged a “14 percent surge in China Shock 2.0,” noting that developing markets are bearing the brunt of an export deluge driven by China’s market distortions. Unlike the original China Shock of the 2000s — which displaced labour-intensive, low-value manufacturing in rich economies — China Shock 2.0 is crowding out high-tech, high-value manufacturing in Europe and Japan. Goldman Sachs estimates that for every 1 percentage point of export-driven boost to Chinese GDP, other economies may see a 0.1 to 0.3 percentage point drag, with tech-intensive producers facing acute pressure.

Meanwhile, China’s voracious appetite for advanced chips it cannot yet manufacture domestically has produced a paradox: China imported a record $135 billion in semiconductors in the most recent quarter as AI investment accelerates. The country remains dependent on foreign-made advanced logic chips dominated by ASML, creating a structural vulnerability that its Five-Year Plan is designed to remedy — but may not resolve within this decade.

The Endgame of the Xi Gamble

The Economist captured the existential dimension of Beijing‘s strategy by quoting Johns Hopkins University‘s Yuen Yuen: “At no time in modern history has a large country gone all in on investment in high-end technology while also navigating a slowing economy and a local-government debt crisis.” Xi Jinping’s wager is that the technology-driven growth model scales faster than the old property-and-construction model collapses. The data through mid-2026 suggest the race is closer than Beijing’s official narrative acknowledges.

China’s GDP growth target for 2026 is the lowest since 1991 at 4.5–5%. Meeting it will depend on whether AI and green technology exports can sustain momentum against an Iran-related global slowdown that is already beginning to weigh on overall demand. The outcome will shape global trade balances, supply chain geography, and the AI chip economy for the next decade.