Investors are turning their attention to Asia, seeking the next breakthrough in the global equity rally.

Driven by the artificial intelligence wave, South Korea’s stock market has led global gains this month, attracting massive capital inflows. Implied volatility in options markets has surged to extreme levels, prompting derivatives strategists to aggressively recommend long structures.

All these signals point to one conclusion: the Asian upcycle may have only just begun.

According to Chasing the Wind Trading Desk, Morgan Stanley’s Asia-Pacific team has repeatedly emphasized that the underlying drivers of the Asian industrial cycle are shifting from traditional real estate and general manufacturing inventory rebuilding toward AI and its infrastructure, energy security and energy transition, defense, and supply chain resilience investments.

Morgan Stanley forecasts that fixed asset investment in Asia could rise from approximately $1.1 trillion in 2025 to $1.6 trillion by 2030, with a nominal annual compound growth rate of around 7% between 2026 and 2030—significantly higher than recent trends.

The Underlying Logic of the “Super Cycle”: Accelerated Capital Expenditure in Asia

The most distinctive feature of this Asian industrial cycle is that AI has once again brought capital expenditure to center stage.

Over the past two years, market discussions on AI have largely focused on models, applications, and the U.S. “Magnificent Seven.” From an Asian perspective, however, AI truly signifies the comprehensive expansion of chipsets, memory, servers, optical modules, data centers, power systems, and cloud infrastructure.

Morgan Stanley notes that the share of global CIOs ranking AI as their top priority has risen to 39%. Correspondingly, global AI data center investment is projected to reach approximately $280 billion between 2026 and 2028, growing at an annual rate of around 33%.

Asia sits at the heart of the AI hardware supply chain: from TSMC, Samsung, SK Hynix, to Chinese semiconductor, server, optical communications, and cloud infrastructure firms—all stand to benefit from this investment cycle.

The report further projects that capital expenditure at major chip companies could rise from about $105 billion in 2025 to roughly $250 billion annually by 2028—indicating that AI is becoming a capital-intensive race.

China’s role deserves particular attention.

Morgan Stanley views China’s AI development as a full-system capability competition: computing power determines speed, cloud platforms determine scale, token usage determines economic viability, and application scenarios determine value capture.

Despite ongoing external chip restrictions, the synergy among domestic AI chips, local cloud platforms, and large-scale model ecosystems is emerging as the new core theme in Chinese tech investment.

The analysis suggests China’s AI chip market could reach $67 billion by 2030, with domestic self-sufficiency potentially rising to 86%.

Whether this forecast fully materializes remains to be seen, but the direction is clear: domestic computing power localization has evolved from a policy imperative into a commercial reality.

The Export Story of Made-in-China Is Expanding from “New Three” to Robotics

Over the past few years, the most prominent segment of China’s export structure has been the “New Three”—electric vehicles, lithium batteries, and photovoltaics.

The report suggests that the next phase of China’s manufacturing growth may come from robotics, particularly industrial and humanoid robots.

Morgan Stanley points out that China already accounts for about half of the global incremental demand for industrial robots. Global humanoid robot shipments in 2025 are expected to range between 13,000 and 16,000 units, with approximately 90% originating from Chinese manufacturers. In contrast, markets in the U.S. and Japan remain largely in prototype or early validation stages.

More intriguingly, the report draws a parallel between current Chinese robot exports and electric vehicle exports around 2019: back then, EV exports had not yet entered a breakout phase, but the supply chain, policy support, and manufacturing capacity were already well-prepared.

Today’s robotics industry exhibits similar characteristics—market size is still modest, but supply chain expansion is rapid.

Data shows that China’s humanoid robot and related robot exports reached a rolling 12-month scale of approximately $1.5 billion by March 2026—comparable to the level of China’s EV exports in early 2020.

Subsequently, EV exports expanded rapidly; by 2025, annual exports reached around $70 billion, with quarterly year-on-year run rates climbing further to approximately $86 billion.

Naturally, whether robotics can replicate the EV trajectory depends on cost reduction, expanded use cases, and evolving overseas regulatory environments. However, China’s advantages in components, system integration, supply chain coordination, and rapid iteration are already becoming evident.

Energy Security and Defense Spending Are Providing Second and Third Growth Engines

The expansion of AI data centers comes with massive demand for power and energy infrastructure. The denser the computing power, the more critical electricity, cooling, grid stability, and energy storage become.

Morgan Stanley argues that energy shocks will accelerate investment in energy security across Asia, where renewable energy still accounts for a relatively small share of primary energy consumption—indicating substantial room for future investment.

China holds industrial advantages in photovoltaics, electric vehicles, and lithium batteries, with related exports reaching a rolling 12-month scale close to $200 billion—making it a key beneficiary of this energy transition capital expenditure cycle.

Meanwhile, defense spending is also showing structural increases across multiple Asian economies.

Defense expenditures as a share of GDP have risen in Japan, South Korea, and India. China and South Korea remain among the world’s top ten defense exporters.

For capital markets, this implies stronger long-term demand for high-end manufacturing, materials, electronic components, and precision equipment supply chains.

In other words, AI drives compute demand, energy secures infrastructure constraints, and defense plus supply chain resilience provide the geopolitical backdrop for “resilience investing.” Together, these three forces form the foundation of the Asian super cycle.

Who Benefits Most? China, South Korea, and Japan Stand at the Core of the Supply Chain

From a regional benefit perspective, Morgan Stanley highlights China, South Korea, and Japan as key beneficiaries.

Mainland China excels in supply chain completeness, manufacturing scale, engineering execution capabilities, and emerging export categories such as new energy and robotics.

South Korea holds advantages in memory, HBM, batteries, and certain equipment materials. Japan maintains deep expertise in semiconductor equipment, materials, precision manufacturing, and industrial automation.

Capital goods export shares reveal further insight: Thailand at ~38%, China at ~36%, Japan at ~35%, and South Korea at ~30%. This indicates that when the world enters a new equipment investment cycle, these economies will exhibit greater external demand elasticity.

Finally, from a capital market structure standpoint, these markets feature higher weightings in industrial, tech hardware, and materials sectors—meaning macro-level capital expenditure cycles are more readily reflected in equity performance.

This suggests that the pricing logic in Asian markets may shift over the coming years, with investors increasingly focusing on which companies along the capital expenditure chain possess orders, technological moats, and profit elasticity.

Risks Not to Be Ignored: Overcapacity, Margins, and Geopolitical Frictions

The narrative of a super cycle is compelling—but does not imply all industries and firms will benefit in lockstep.

First, expanding capital expenditure may lead to temporary supply pressures.

China’s new energy sector has demonstrated how scale advantages can quickly open global markets, but also bring price competition and margin volatility. Robotics, AI hardware, photovoltaics, and energy storage industries may face similar challenges in the future.

Second, technological limitations and export controls remain key variables.

While there is significant room for domestic AI chip development, gaps persist in advanced process nodes, HBM, EDA tools, and equipment materials. The report acknowledges that domestic chips still lag behind U.S. top-tier chips, but competitiveness can be enhanced through system optimization, advanced packaging, and software adaptation.

Third, employment structures will be impacted by AI.

In Morgan Stanley’s “Future of Work” research, it is estimated that around 90% of occupations will be affected to varying degrees by AI-driven automation and augmentation. Among its sample companies, early AI adoption has already driven productivity gains exceeding 11%, though accompanied by an average net job reduction of about 4%, with notable differences across countries and sectors.

For China, how to advance retraining and job transitions while boosting efficiency will remain a critical long-term policy and corporate management challenge.

Fourth, market volatility may intensify. The report warns that the divergence between bull and bear scenarios across regions is widening, meaning investor disagreements on AI capital expenditure, export orders, and profit realization will persist.

Author: Bao Yilong | Source: DeepTide Techflow