Oil prices have surged past $79 per barrel for Brent crude in the wake of US-Israel strikes on Iran on February 28, 2026, that killed Supreme Leader Ali Khamenei, sending shockwaves through global markets and spotlighting Asia oil import risks 2026. This Iran conflict energy crisis Asia underscores how the region’s heavy reliance on Middle Eastern crude—over 80% of Hormuz flows destined for Asia—exposes economies to severe disruptions. Drawing on Morgan Stanley Asia oil exposure analysis, this article examines why nations like India, South Korea, and Japan face outsized threats despite China’s dominance in volumes.

The Escalating Iran Conflict: A Timeline

The strikes marked a dramatic escalation, with President Donald Trump signaling prolonged action until US objectives are met, halting tanker traffic through the Strait of Hormuz. Iranian retaliation targeted US and Israeli assets, raising fears of a full blockade in this chokepoint handling 20% of global oil.

By March 2, 2026, Brent traded at $79.41, up 9%, while WTI hit $72.79, with analysts warning of $90-100 if disruptions persist. Iran strikes oil prices impact has been immediate, but the real test lies in sustained supply cuts from OPEC+ producers like Saudi Arabia and Iraq.

Imagine factory lights flickering in Mumbai or Seoul as tankers idle— a vivid reminder of Strait of Hormuz closure Asia economy perils.[chinadailyhk]​

Asia’s Oil Import Dependency: By the Numbers

Asia consumes over four-fifths of Middle Eastern crude, with 84% of Hormuz oil flows heading east, per recent data. Asia oil dependence Middle East stands at 66% of total imports, making Middle East oil disruption effects on Asian GDP a looming specter.

China imported 1.38 million bpd from Iran alone last year, but its vast stockpiles buffer short-term shocks. In contrast, India South Korea oil dependence Iran heightens vulnerabilities, with manufacturing hubs sensitive to every $10/barrel hike.

Morgan Stanley Asia oil exposure notes pegged Asia’s imports at levels far exceeding Europe or the US, amplifying Asia oil import risks 2026.[scmp]​

Oil tankers queue in the Strait of Hormuz, a vital artery now under threat amid rising tensions.[eia]​

Morgan Stanley’s Warning: Who Faces the Greatest Risks?

Morgan Stanley’s Warning on Asia oil vulnerability Iran strikes is stark: manufacturing powerhouses like India, South Korea, and Japan are “more sensitive” than China due to thinner reserves and higher import ratios. Chief Asia economist Chetan Ahya warns sustained tensions could shave 0.2-0.3% off regional GDP per $10 oil spike, fueling inflation in export-driven economies.

Why India and South Korea? Their 80-90% Gulf reliance dwarfs China’s 50%, with limited diversification to Russia or Africa. Japan, despite stockpiles, faces yen pressures from energy costs, potentially dimming Tokyo’s neon glow.

Rhetorically, if Hormuz clogs for weeks, could Seoul’s shipyards grind to a halt? Iran conflict energy crisis Asia analysts say yes, projecting 1-2% GDP hits for exposed nations.[chinadailyhk]​

Economic Forecasts: GDP Hits and Inflation Pressures

A $20 sustained oil surge could trim Asia’s 2026 growth by 0.5-1%, per implied models, with Middle East oil disruption effects on Asian GDP hitting exporters hardest. India’s refiners, slashing Russian buys, now lean 55% on the Gulf, risking 2-3% inflation jumps.

South Korea’s auto sector, Japan’s electronics—both oil-thirsty—face margin squeezes, while China’s stimulus cushions blow. Morgan Stanley flags “macro stability risks,” echoing IEA warnings on Hormuz flows.

These Asia oil import risks 2026 could cascade into currency woes, with rupee and won under siege.[chinadailyhk]​

Mitigation Strategies: Stockpiles, Diversification, and Beyond

Asian giants hoard reserves—Japan at 200 days, India building to 74—but gaps persist for South Korea. China pivots to floating storage (42 million Iranian barrels afloat) and FSU supplies.

Diversification beckons: India eyes Africa, Vietnam Latin America, but logistics lag. Short-term, LNG swaps from Qatar aid, yet Strait of Hormuz closure Asia economy threats loom large.

Over coffee with traders, one quips: “Stockpiles buy time, but not eternity.” Renewables ramp-up offers long-term salve.[thestar.com]​

Forward-Looking: Energy Transition Amid Geopolitical Storms

The Iran strikes oil prices impact accelerates Asia’s green shift, with Japan and Korea targeting net-zero by 2050. Yet fossil dependence endures—87% for Japan, 81% Korea—amid slow EV adoption.

Morgan Stanley Asia oil exposure urges hedging via futures, biofuels, while OPEC+ spare capacity (5 million bpd) tempers doomsday scenarios. Geopolitics reshapes maps: expect more CPEC-like corridors bypassing Hormuz.[scmp]​

In this volatile era, Asia’s lesson is clear—diversify or dim. As Trump’s strikes echo, India South Korea oil dependence Iran demands urgent action, lest energy crises eclipse economic miracles.

The KSE-100 index collapsed 9.57% on March 2, 2026 — its worst-ever single-day absolute loss — as US-Israel strikes on Iran triggered a PSX bloodbath, oil shock, and global market panic. Here’s the full breakdown.

Key Facts at a Glance

It began not with the opening bell, but with silence — the particular, loaded silence of traders staring at screens as the world they priced for had, overnight, become a different one entirely. By 9:22 on a Monday morning in Karachi, the Pakistan Stock Exchange had effectively declared an emergency, triggering a mandatory trading halt after the benchmark KSE-100 index plummeted 15,071 points — nearly 9% — in less than half an hour of trading. When markets finally closed, the KSE-100 had shed 16,089 points to settle at 151,972.99, a decline of 9.57% that constitutes the worst absolute single-day loss in the exchange’s history.

This was no ordinary correction. This was the market’s verdict on a new and dangerous world.

The Trigger: When Washington and Tel Aviv Changed the Calculus

The proximate cause was a seismic geopolitical event that investors had feared but hoped would remain theoretical. Over the weekend of February 28–March 1, 2026, the United States and Israel launched what the White House described as “major combat operations” in Iran, reportedly killing Supreme Leader Ayatollah Ali Khamenei in the opening strikes. Tehran’s response was swift and broad: retaliatory missile barrages targeting US military installations across the Gulf, with blasts reported in the UAE, Qatar, Bahrain, Kuwait, Jordan, and Saudi Arabia.

Dubai International Airport was briefly engulfed in chaos, with footage showing people fleeing a smoke-filled passageway as Iran’s missile salvos — mostly intercepted — sent shockwaves through Gulf infrastructure. President Trump, characteristically blunt, suggested the campaign could last another four weeks.

For energy markets, the threat to the Strait of Hormuz was the true horror. Roughly 15 million barrels of crude oil per day — approximately 20% of the world’s total oil supply — transit the Strait daily, making it the planet’s most consequential energy chokepoint. Marine tracking sites showed tankers piling up on either side, unable to obtain insurance for the voyage. Brent crude surged 9% to $79.41 a barrel in early Monday trading, while West Texas Intermediate climbed 8.6% to $72.79 — the steepest single-day energy price spike since the brief Israel-Iran war of 2025.

The PSX Collapse: Anatomy of a Historic KSE-100 Plunge

Pakistan, as a major net oil importer and a nation whose western border already simmers with Afghan tensions, sits at an especially exposed node in this crisis network. The market did not wait for analysis.

The benchmark index closed at 151,972.99, plunging 16,089.17 points or 9.57% in a single session. It traded within a wild intraday range of 7,580 points, recording a high of 159,328.59 and a low of 151,747.96, reflecting extreme volatility throughout the session. Total trading volume surged to 479.70 million shares.

Monday’s decline marks the KSE-100’s highest-ever single-day fall in absolute terms. Historically, the largest percentage decline was on June 1, 1998 at 12.4%, but due to the lower base of the index at that time, it does not rank in the top ten for absolute point drops. Today’s crash, in sheer numerical magnitude, stands alone.

The circuit breaker fired at 9:22 AM after the KSE-30 fell 5% from its previous close. Following the resumption of trading around 10:22 AM, strong recovery momentum briefly emerged, pushing the index more than 6,000 points higher from its intraday floor — before selling pressure re-emerged and erased those gains.

Market breadth told a brutal story: of the 100 index companies, only one closed higher, 98 declined, and one remained unchanged. The heaviest individual drags were Fauji Fertilizer Company (-1,595 pts), UBL (-1,301 pts), Engro Holdings (-886 pts), Hub Power (-718 pts), and Meezan Bank (-681 pts).

Sector Damage (Index Points Lost):

Pakistan’s Particular Vulnerability

Why did Karachi suffer so much more than London, Frankfurt, or New York? The answer is structural, not merely psychological.

Pakistan imports the vast majority of its energy needs. Every $10 rise in the per-barrel price of crude translates to roughly $2.5 billion in additional annual import costs — a meaningful sum for an economy currently navigating IMF-supervised stabilisation. Analysts were quick to connect the dots: “Elevated oil prices are highly detrimental to Pakistan’s external account, and persistently high commodity prices are likely to trigger a new wave of inflation,” said Waqas Ghani, Head of Research at JS Global.

The country was already navigating a dual-front stress test. Pakistan’s Defence Minister had described the situation with Afghanistan as tantamount to “open war,” and the KSE-100 has now fallen nearly 19% from its record high of 189,166.83 set in January 2026, edging dangerously close to the 20% threshold commonly associated with a formal bear market.

In the week before Monday’s collapse, the index had already shed 5,107 points — a 2.9% weekly decline. The PSX crash of March 2 was therefore not a surprise attack on a healthy market, but a breaking point on an already-fractured one.

The Global Picture: A Coordinated Rout

Pakistan’s pain was severe, but it was not isolated. Global markets opened the week sharply lower after the US-Israel strikes on Iran rattled investors across every time zone. In the US, S&P 500 futures were down 1.1%, Nasdaq 100 futures fell 1.5%, and the Dow Jones futures slid 1.1%. In Europe, the pan-European Stoxx 600 fell nearly 1.8% during Monday’s session.

Asian markets joined the rout: India’s Sensex fell 1.3%, Taiwan’s benchmark lost 0.9%, and Singapore’s dropped 2.3%. Bangkok’s SET fell 4%, while the UAE and Kuwait temporarily closed their own stock markets entirely, citing “exceptional circumstances.”

Gold surged to $5,408.10 per ounce — a 3.1% single-day gain — as the classic safe-haven flight took hold. The US dollar strengthened against most emerging-market currencies, adding a secondary pressure on Pakistan’s rupee and its debt-servicing capacity.

Standard Chartered’s Global Head of Research Eric Robertsen noted that investors had already been underpricing geopolitical risk, pointing to commodity-linked currencies outperforming as markets began pricing exposure to scarce resources and terms-of-trade winners.

What Analysts and Economists Are Saying

The bull case for containment: Quantum Strategy’s David Roche argued that the market impact depends almost entirely on duration. If the conflict remains short and contained, he noted, the risk-off move and oil spike could be brief — referencing the June 2025 pattern, when Israel struck Iranian nuclear sites and equities sold off sharply at the open before recovering once it became clear the Strait of Hormuz was not disrupted.

The bear case for escalation: Goldman Sachs estimated that oil prices could blow past $100 a barrel if there is an extended disruption to Strait of Hormuz flows — a scenario with severe implications for Pakistan’s current account and inflation trajectory.

The structural concern: Arif Habib Limited (AHL), in its latest note, highlighted that despite the near-term pressure, the tail-end of March typically marks the beginning of a seasonally bullish period for the KSE-100, and that following an almost 15% drawdown, the index appears poised for a rebound towards the 175,000 level, with sustained support above 165,000 likely to underpin such a move.

Recovery Scenarios: Three Possible Paths Forward

Scenario 1 — Swift De-escalation (30–45 days) If the US-Iran conflict remains largely aerial and does not close the Strait of Hormuz, global oil markets could retrace sharply. Pakistan would benefit from falling crude prices, a stabilizing rupee, and renewed risk appetite for frontier markets. KSE-100 recovery to 165,000–170,000 is plausible by April.

Scenario 2 — Prolonged Campaign (60–90 days) A sustained conflict, particularly one that throttles Strait of Hormuz traffic, would push Brent above $90–100, forcing Pakistan to burn through foreign exchange reserves at an accelerated pace and potentially triggering an emergency IMF review. The KSE-100 could test support at 140,000.

Scenario 3 — Regime Change and Uncertainty The death of Ayatollah Khamenei opens a power vacuum scenario in Iran that few analysts have priced. Ben Emons of FedWatch Advisors argued that leadership strikes in Tehran raise regime-change tail risks and leave an uncertain endgame — potentially the most destabilizing medium-term outcome for all regional markets, including PSX.

Actionable Insights for Investors

This is not a moment for panic, but it is a moment for precision. Here is what the data suggests:

1. Energy-linked plays carry double risk. Pakistani oil marketing companies and refineries face margin compression from higher crude costs even as revenues appear to rise in PKR terms. The sector’s net impact is negative for most listed names.

2. Banks face a credit cycle test. Commercial banks, which bore the largest index-point losses today, face rising non-performing loan risk if a fresh inflation cycle materializes. However, their healthy net interest margins — built during the high-rate era — provide a buffer. Selectively accumulating quality names on dips remains a viable strategy.

3. Fertilizer stocks are caught in a vice. Higher natural gas costs (linked to LNG imports) and falling farm-gate prices from commodity pressure could squeeze margins. Fauji Fertilizer’s 1,595-point drag on the index today reflects this anxiety.

4. Technicals matter now. AHL’s observation that the KSE-100 remains 7% above its 200-day moving average is significant — it represents a long-term structural support that institutional investors will defend. Breach of 145,000 would mark genuine capitulation territory.

5. Watch the Strait, not just the headlines. The single most important variable for Pakistan’s macro outlook over the next 30–60 days is not battlefield developments, but whether marine traffic through the Strait of Hormuz normalizes. A functional strait = manageable oil shock. A blocked strait = crisis conditions.

The Bigger Picture

Pakistan’s PSX bloodbath today is, in one sense, a microcosm of a broader truth about the global economy in 2026: the world has underpriced geopolitical risk for years, and it is now receiving the bill. From Karachi to Frankfurt, from the Gulf tanker lanes to Wall Street’s futures desks, the US-Israel strikes on Iran have created a risk-repricing event of genuine historical significance.

The Pakistan Stock Exchange, with its volatile frontier-market character, tends to price these shocks faster and harder than more liquid peers. That same characteristic means it tends to recover faster when clarity returns. The question Pakistani investors — and the government — must answer urgently is: what decisions, made today, preserve the most options for that recovery?

Analysis | China’s AI Strategy | Global Technology Review

How China’s low-cost AI models—10 to 20 times cheaper than US equivalents—are quietly building global tech dependence, reshaping the AI race, and challenging American dominance.

In late February 2026, ByteDance unveiled Seedance 2.0, a video-generation model so capable—and so strikingly inexpensive—that it sent tremors through Silicon Valley boardrooms. The timing was no accident. Within days, Anthropic filed a legal complaint alleging that a Chinese national had systematically harvested outputs from Claude to train a rival model, a practice known in the industry as “distillation.” The accusation crystallized what many AI executives had quietly been saying for months: China is not simply competing in artificial intelligence. It is running a fundamentally different play.

The strategy is elegant in its ruthlessness. While American frontier labs—OpenAI, Google DeepMind, Anthropic—compete on the technological frontier, racing to build the most powerful and most expensive models imaginable, China’s leading AI developers are racing in the opposite direction. They are making AI astonishingly cheap, broadly accessible, and deeply entangled in the infrastructure of developing economies. Understanding how cheap AI tools from China compare to American frontier models is not merely a technology question. It is a question about who writes the rules of the next era of the global economy.

The Sputnik Moment That Changed Everything

When DeepSeek released its R1 reasoning model in January 2025, the reaction in Washington was somewhere between bewilderment and alarm. US officials, accustomed to treating American AI supremacy as a structural given, struggled to explain how a Chinese startup—operating under heavy export restrictions that denied it access to Nvidia’s most advanced chips—had produced a model that matched, or in certain benchmarks exceeded, OpenAI’s o1. Reuters (2025) described the release as “a wake-up call for the US tech industry.”

The label that stuck was borrowed from Cold War history. Investors, policymakers, and researchers began calling DeepSeek’s R1 “a Sputnik moment”—a demonstration that the adversary had capabilities that had been systematically underestimated. The reaction was visceral: Nvidia lost nearly $600 billion in market capitalization in a single trading session. But the deeper implication was not about one model or one company. It was about a method.

“The real disruption isn’t that China built a good model. It’s that China built a cheap model—and cheap changes everything about adoption curves, lock-in, and geopolitical leverage.”

— Senior analyst, Brookings Institution Center for Technology Innovation

DeepSeek’s R1 was trained at an estimated cost of under $6 million, a fraction of what OpenAI reportedly spent on GPT-4. The model was open-sourced, triggering an avalanche of derivative models across Southeast Asia, Latin America, and sub-Saharan Africa. The impact of low-cost Chinese AI on US dominance had moved from hypothetical to measurable. By the fourth quarter of 2025, Chinese AI models had captured approximately 15% of global market share, up from roughly 1% just two years earlier, according to estimates cited by CNBC (2025).

Five Models and Counting: The Pace Accelerates

DeepSeek was only the opening act. Within weeks, five additional significant Chinese AI models had shipped—a pace that surprised even close observers of China’s technology sector. ByteDance’s Doubao and the Seedance family of multimodal models, Alibaba’s Qwen series, Baidu’s ERNIE updates, and Tencent’s Hunyuan collectively constitute what The Economist (2025) termed China’s “AI tigers.”

American labs have pushed back hard. Anthropic’s legal complaint over distillation practices reflects a broader industry concern: that Chinese developers are not merely competing on engineering talent but systematically harvesting the intellectual output of Western models to accelerate their own. The accusation is significant because distillation—training a smaller, cheaper model on the outputs of a larger one—is not illegal in most jurisdictions, but it sits in a legal and ethical gray zone that could reshape how frontier AI outputs are licensed and protected. Chatham House (2025) has observed that the practice “blurs the line between legitimate benchmarking and intellectual property extraction at scale.”

UBS Picks Its Winners

Not all Chinese models are created equal, and sophisticated institutional actors are drawing distinctions. Analysts at UBS, in a widely circulated note from early 2026, indicated a preference for several Chinese models—specifically Alibaba’s Qwen and ByteDance’s Doubao—over DeepSeek for enterprise deployments, citing more consistent performance on structured reasoning tasks and better compliance tooling for regulated industries. The note was striking precisely because it came from a global financial institution with every incentive to avoid geopolitical controversy. The risks of dependence on Chinese AI platforms, apparently, are acceptable to some of the world’s most sophisticated institutional investors when the price differential is this large.

Key Strategic Insights

• China’s cost advantage is structural, not temporary. Priced 10 to 20 times cheaper per API call, the gap reflects architectural innovation, lower energy costs, and in some cases state subsidy—making it durable over time.
• Emerging markets are the primary battleground. In Indonesia, Nigeria, Brazil, and Vietnam, Chinese AI tools have penetrated developer ecosystems faster than US equivalents because local startups and governments simply cannot afford American pricing.
• Open-sourcing is a deliberate geopolitical instrument. By releasing models under permissive licenses, Chinese developers seed global ecosystems with their architectures, creating dependency on Chinese tooling, Chinese fine-tuning expertise, and Chinese cloud infrastructure.
• The distillation controversy signals a new phase. As US labs tighten access and output monitoring, the cat-and-mouse dynamics of knowledge extraction will intensify, potentially reshaping how AI models are licensed globally.
• Hardware self-reliance is advancing faster than anticipated. Cambricon’s revenue surged over 200% in 2025 as domestic chip demand spiked, while Baidu’s Kunlun AI chips are now deployed across major Chinese data centers at scale.

The Comparison Table: US vs. Chinese AI

Winning the Hardware War From Behind

No analysis of how China’s cheap AI is creating global tech dependence is complete without confronting the chip question. The Biden and Trump administrations’ export controls—restricting Nvidia’s H100, A100, and subsequent architectures from reaching Chinese buyers—were designed to create a permanent computational ceiling. The assumption was that frontier AI requires frontier silicon, and frontier silicon would remain American. That assumption is under sustained pressure.

Huawei’s Atlas 950 AI training cluster, unveiled in late 2025, represents the most credible challenge yet to Nvidia’s dominance in the Chinese market. Built around Huawei’s Ascend 910C processor, the cluster offers training performance that analysts at the Financial Times (2025) described as “approaching, though not yet matching, Nvidia’s H100 at scale.” More telling is the trajectory. Cambricon Technologies, China’s leading AI chip specialist, reported revenue growth exceeding 200% in fiscal 2025 as domestic AI developers pivoted aggressively to domestic silicon under regulatory pressure and patriotic procurement directives.

Baidu’s Kunlun chip line, meanwhile, is now powering a significant share of the company’s own inference workloads—reducing dependence on imported hardware at the exact moment when US export restrictions are tightening. China’s AI strategy for becoming an economic superpower is not predicated on surpassing American chip technology in the near term. It is predicated on becoming self-sufficient enough to sustain its cost advantage while US competitors remain anchored to expensive, constrained silicon supply chains. Brookings (2025) has noted that “China’s domestic chip ecosystem has advanced by at least two to three years relative to projections made in 2022.”

The Emerging Market Gambit

Silicon Valley’s pricing model was always implicitly designed for Silicon Valley’s clients: well-capitalized Western enterprises with robust cloud budgets and tolerance for compliance complexity. The rest of the world—which is to say, most of the world—was an afterthought. Chinese AI developers recognized this gap and moved into it with precision.

In Vietnam, government agencies have begun piloting Alibaba’s Qwen models for document processing and citizen services, drawn by price points that make comparable US offerings economically untenable for a developing-economy public sector. In Nigeria, startup accelerators report that the majority of AI-native companies in their cohorts are building on Chinese model APIs—not out of ideological preference but because the economics are simply not comparable. Indonesian developers have contributed tens of thousands of fine-tuned model variants to open-source repositories built on DeepSeek and Qwen foundations, creating exactly the kind of community lock-in that platform companies spend billions trying to manufacture.

The implications for tech sovereignty are profound and troubling. As Chatham House (2025) argues, when a country’s critical AI infrastructure is built on a foreign model’s weights, architecture, and increasingly its cloud services, the notion of digital sovereignty becomes largely theoretical. Data flows toward Chinese servers. Fine-tuning expertise clusters around Chinese tooling ecosystems. Regulatory leverage accrues to Beijing.

“Ubiquity is more powerful than superiority. The question is not which AI is best—it is which AI is everywhere.”

— Stanford HAI, AI Index Report 2025

Alibaba’s $53 Billion Signal

If there was any residual doubt about the strategic ambition behind China’s AI push, Alibaba’s announcement of a $53 billion AI investment commitment through 2027 should have resolved it. The scale dwarfs most national AI strategies and rivals the combined R&D budgets of several major US technology companies. Critically, the investment is not concentrated in a single prestige project. It is spread across cloud infrastructure, model development, developer tooling, international data centers, and—pointedly—subsidized access programs for emerging-market customers.

This is the architecture of dependency, built deliberately. Offer cheap access. Embed your tools in critical workflows. Build the developer community on your frameworks. Then, when the switching costs are high enough and the alternatives have atrophied from neglect, the pricing conversation changes. It is the playbook that Amazon ran with AWS, that Google ran with Search, and that Microsoft ran with Office—now being executed at geopolitical scale by a state-aligned corporate champion with essentially unlimited political backing. Forbes (2025) characterized the investment as “less a corporate bet than a national infrastructure program wearing a corporate uniform.”

Is China Winning the AI Race?

The question is, in one sense, the wrong question. “Winning” implies a finish line, a moment when one competitor’s supremacy is declared and ratified. Technological competition does not work that way, and the AI race least of all. What China is doing is more subtle and, in the long run, potentially more consequential: it is restructuring the terms of global AI participation in ways that favor Chinese platforms, Chinese architectures, and Chinese geopolitical interests.

On pure technical capability, American frontier labs retain meaningful advantages at the absolute cutting edge. OpenAI’s reasoning models, Google’s multimodal systems, and Anthropic’s safety-focused architectures represent genuine innovations that Chinese competitors are still working to match. The New York Times (2025) noted that US models continue to lead on complex multi-step reasoning and long-context tasks by measurable margins. But capability at the frontier matters far less than capability at the median—at the price point, integration depth, and ecosystem richness that determine what the world actually uses.

China is winning that race. Not through theft or brute force, though allegations of distillation practices suggest the competitive lines are not always clean, but through a coherent, patient, and strategically sophisticated campaign to make Chinese AI the default choice for a world that cannot afford American alternatives. The risks of dependence on Chinese AI platforms—data sovereignty concerns, potential for access interruption under geopolitical pressure, embedded architectural assumptions that may encode specific values—are real and documented. They are also, increasingly, being accepted as the price of access by a world that Western AI pricing has effectively priced out.

History suggests that the technology that becomes ubiquitous becomes infrastructure, and infrastructure becomes power. China’s AI developers have understood this clearly. The rest of the world is just beginning to reckon with what it means.