Driven by the AI wave, Asian stock markets are experiencing a new round of upward momentum. Morgan Stanley forecasts that fixed asset investment in Asia will rise from $11 trillion in 2025 to $16 trillion by 2030. Key growth drivers encompass AI infrastructure, energy security, and defense spending. China holds significant advantages in domestic AI chip production, robotics exports, and the new energy sector.
Investors are shifting their focus to Asia, seeking the next major catalyst for global equity market growth. South Korea's stock market, propelled by the artificial intelligence trend, has led global gains this month, attracting substantial capital inflows. Implied volatility in the options market has climbed to extreme levels, prompting derivatives strategists to recommend bullish structures.
These signals collectively point to a single conclusion: the Asian rally may just be beginning. According to market analysis, Morgan Stanley's Asia-Pacific team has recently emphasized that the fundamental drivers of Asia's industrial cycle are shifting from traditional real estate and general manufacturing inventory replenishment to AI and its infrastructure, energy security and transition, and investments in defense and supply chain resilience.
Morgan Stanley estimates that Asia's fixed asset investment scale could increase from approximately $11 trillion in 2025 to $16 trillion by 2030. From 2026 to 2030, the nominal investment is projected to grow at a compound annual growth rate of about 7%, significantly higher than recent levels.
The core logic of this "supercycle": Asia's capital expenditure is set to accelerate markedly. The most crucial difference in this Asian industrial cycle is that AI has brought capital expenditure back to the forefront. Over the past two years, market discussions on AI largely centered on models, applications, and the U.S. "Magnificent Seven." However, from an Asian perspective, the true meaning of AI is the comprehensive expansion of chips, memory, servers, optical modules, data centers, power systems, and cloud infrastructure.
Morgan Stanley notes that the proportion of global CIOs listing AI as their top priority has risen to 39%. Correspondingly, global AI data center investment is expected to reach about $2.8 trillion from 2026 to 2028, with an annual growth rate of approximately 33%. Asia is at the center of the AI hardware supply chain: from TSMC, Samsung, SK Hynix to mainland China's semiconductor, server, optical communication, and cloud infrastructure companies, all are poised to benefit from this investment cycle.
The report further anticipates that major chip companies' capital expenditure could rise from around $105 billion in 2025 to about $250 billion annually by 2028. This indicates that AI is a capital-intensive race. China's role is particularly noteworthy. Morgan Stanley believes competition in Chinese AI revolves around complete system capabilities: computing power determines speed, cloud platforms determine scale, token usage determines economics, and application scenarios determine value attribution.
Against the backdrop of ongoing external chip restrictions, the synergy between domestic AI chips, local cloud platforms, and the large model ecosystem is becoming a new main theme for China's technology investment. Their analysis suggests China's AI chip market could reach $67 billion by 2030, with the domestic self-sufficiency rate potentially rising to 86%. Whether this prediction fully materializes remains to be seen, but the direction is clear: the localization of computing power is gradually shifting from a policy imperative to a commercial proposition.
China's manufacturing export story is expanding from the "electric vehicle trio" to robotics. In recent years, the most prominent features of China's export structure have been electric vehicles, lithium batteries, and solar panels—the "new three." The report suggests that the next phase of new growth for Chinese manufacturing may come from robotics, particularly industrial robots and humanoid robots.
Morgan Stanley points out that China already captures about half of the incremental global demand for industrial robots. Global humanoid robot shipments are projected to be around 13,000 to 16,000 units in 2025, with approximately 90% coming from Chinese manufacturers. In contrast, markets like the U.S. and Japan remain more in the prototype or early validation stages. More interestingly, the report draws a parallel between current Chinese robotics exports and electric vehicle exports around 2019: at that time, EV exports had not yet entered an explosive growth phase, but the supply chain, policy support, and manufacturing capabilities were largely in place.
Today, the robotics industry exhibits similar characteristics—the market size is not yet large, but the supply chain is expanding rapidly. Data shows that China's humanoid robot and robotics-related exports reached a 12-month rolling sum of about $1.5 billion as of March 2026, a level similar to China's electric vehicle exports in early 2020. In the following years, EV exports expanded rapidly, reaching about $70 billion for the full year 2025, with a quarterly annualized run rate further increasing to approximately $86 billion.
Of course, whether robotics can replicate the EV growth curve depends on cost reductions, the opening of application scenarios, and overseas regulatory environments. However, China's advantages in components, complete machine manufacturing, supply chain coordination, and rapid iteration are already becoming apparent.
Energy security and defense spending are providing the second and third growth engines. The flip side of AI data center expansion is the enormous demand for power and energy infrastructure. The more intensive the computing power, the greater the importance of electricity, cooling, power grids, and energy storage.
Morgan Stanley believes energy shocks will catalyze investment in energy security across Asia. The share of renewable energy in Asia's primary energy consumption remains relatively low, indicating significant room for subsequent investment. China holds industrial advantages in solar PV, electric vehicles, lithium batteries, and related fields. Its relevant exports have reached a 12-month rolling scale close to the $200 billion level, making it a key beneficiary of this round of energy transition capital expenditure.
Simultaneously, defense spending is showing a structural upward trend in several Asian economies. The share of defense expenditure in GDP has increased in Japan, South Korea, India, and others. China and South Korea are also among the world's top ten defense exporters. For capital markets, this implies that demand across supply chains for advanced manufacturing, materials, electronic components, and precision equipment may receive longer-term support.
In other words, AI provides computing power demand, energy imposes infrastructure constraints, and defense and supply chain security provide "resilience investment" within a geopolitical context. The combination of these three factors forms the foundation of Asia's supercycle.
Who benefits most? China, South Korea, and Japan stand at the core of the supply chain. From a regional beneficiary perspective, Morgan Stanley highlights China, South Korea, and Japan. Mainland China excels in supply chain completeness, manufacturing scale, engineering capabilities, and emerging export categories like new energy and robotics. South Korea holds advantages in memory, HBM, batteries, and some equipment and materials segments. Japan retains deep expertise in semiconductor equipment, materials, precision manufacturing, and industrial automation.
The share of capital goods exports also illustrates the point. The report shows figures of approximately 38% for Thailand, 36% for China, 35% for Japan, and 30% for South Korea. This means these economies exhibit greater external demand elasticity when the global economy enters a new cycle of equipment investment. Finally, from a capital market structure perspective, these markets have relatively high weightings in industrial, technology hardware, and materials sectors. Therefore, the macro capital expenditure cycle is more easily reflected in stock market performance.
This also implies that the pricing logic in Asian markets may change in the coming years, focusing on which companies in the capital expenditure chain have orders, technological barriers, and profit elasticity.
Risks that cannot be ignored: overcapacity, profit margins, and geopolitical friction. The supercycle narrative is compelling but does not mean all industries and companies will benefit simultaneously. First, capital expenditure expansion may bring periodic supply pressures. China's new energy industry has demonstrated that scale advantages can quickly open global markets but may also be accompanied by price competition and profit margin fluctuations. Industries like robotics, AI hardware, solar PV, and energy storage may face similar challenges in the future.
Second, technological restrictions and export controls remain variables. There is significant potential for domestic AI chip production in China, but gaps persist in advanced process nodes, HBM, EDA, equipment, and materials. The report also notes that while domestic chips still lag behind top-tier U.S. chips, competitiveness can be enhanced through system optimization, advanced packaging, and software adaptation.
Third, employment structures will also be impacted by AI. Morgan Stanley's "Future of Work" research estimates that about 90% of occupations will be affected to varying degrees by AI automation and augmentation. Among its sample companies, early AI adoption has already led to productivity gains exceeding 11%, but this has been accompanied by a net average job reduction of about 4%, with significant variations across countries and industries. For China, how to promote efficiency while advancing retraining and job transitions will be a crucial medium- to long-term policy and corporate management challenge.
Fourth, market volatility may increase. The report also cautions that the widening gap between bull and bear scenarios in regional markets suggests persistent investor divergence in expectations regarding AI capital expenditure, export orders, and profit realization.
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