Asia is experiencing an industrial supercycle, with a surge in China’s robot exports.

Overview

This research report is the second installment in Morgan Stanley’s “Asia’s Next Supercycle” series. At its core, the report argues that, driven by rising global and regional capital expenditures (Capex), Asia is on the cusp of its strongest industrial supercycle since the mid-2000s. Against this backdrop, China—bolstered by a robust supply-chain infrastructure and strong government support—has demonstrated formidable export competitiveness across key sectors, including electric vehicles, batteries, solar energy, and the emerging field of humanoid robotics. Meanwhile, the report delves into how AI technology is reshaping the labor market, highlighting that while AI significantly boosts productivity, it also exerts substantial pressure on employment structures, necessitating careful policy responses.

Core views

China’s New Engine for Manufacturing: Robotics and High-End Equipment The research report underscores that China’s next wave of exports could be driven by humanoid robots and industrial robots. Data indicate that China already accounts for roughly 50% of the global incremental demand for industrial robots. Even more striking, by 2025, an estimated 13,000 to 16,000 humanoid robots are expected to ship worldwide, with approximately 90% manufactured in China. By contrast, other major economies such as the United States and Japan remain largely at the prototype‑development stage. This scale advantage positions China to capture a larger share of global capital‑goods demand. Earlier projections suggest that, by 2030, China’s export market share could rise from its current 15% to 16.5%, with advanced manufacturing serving as the primary growth driver. The Double-Edged Sword of AI: Productivity Gains and Labor Market Restructuring Another key focus of the report is AI’s impact on employment. Morgan Stanley’s “Future of Work” study finds that 90% of occupations will be affected—either through automation or augmentation—by AI, creating substantial demand for reskilling and upskilling. Among early adopters, sample companies have reported double-digit productivity gains (exceeding 11%). However, this progress has been accompanied by significant labor-market disruptions: globally, these firms have recorded a net 4% reduction in employment. Notably, this figure masks regional disparities: while the U.S. has seen net hiring, Japan and the U.K. have experienced more pronounced job losses, highlighting uneven distribution of AI’s effects across countries and sectors. Market Outlook and Risk Warnings Despite favorable long-term trends, the report cautions against near-term risks. Geopolitical tensions may dampen short-term momentum but could also accelerate investment in AI, energy, defense, and resilient supply chains. Meanwhile, profitability challenges and overcapacity in China’s manufacturing sector remain potential downside risks. At the market level, institutions anticipate persistently elevated volatility and underscore widening divergences between bullish and bearish views within regions.

Analysis framework

Supply–Demand and Industry Cycle Framework The report adopts the “industrial supercycle” as its core analytical framework, assessing macroeconomic and sectoral conditions by tracking trends in capital expenditures (Capex). This is a quintessential cyclical analysis approach, positing that substantial capital investment typically signals prolonged industry expansion and rising demand. Horizontal Comparison and Historical Mapping In analyzing China’s robotics industry, the report employs a historical mapping methodology, juxtaposing current humanoid robot export performance with the 2019 electric vehicle (EV) export landscape. Such analogies help readers gauge the life-cycle stage of emerging industries—specifically, the pre‑boom phase—and leverage the EV sector’s success story to project potential growth trajectories for the robotics industry. Micro‑Data Validation of Macro Logic The report substantiates its macro-level conclusions with granular micro‑data, including the share of humanoid robot shipments, productivity changes among AI‑enabled firms, and net employment figures. This data‑driven approach sidesteps speculative rhetoric, using concrete enterprise‑level operational metrics to demonstrate the tangible economic impact of AI and automation technologies.

Methodology notes

• Cyclical and Economic Cycle FrameworkCapacity/Equipment Cycle (Kuznets)

  Industrial Super-Cycle

  The research report views the current uptick in capital expenditures as the starting point of a long cycle. In economics, equipment replacement and capacity expansion typically follow Kuznets cycles, which span roughly 7 to 11 years. The report suggests that we are at the onset of a new cycle, driven by artificial intelligence, the energy transition, and supply-chain restructuring.

• Industry/ Sector Analysis FrameworkPenetration Rate S-Curve

  Analogy of Emerging Industry Development Stages

  The research report implicitly applies S-curve theory by comparing the current export scale of humanoid robots to that of electric vehicles in 2019. As 2019 marked a pivotal transition point from the introduction phase to the growth phase for EVs, the report posits that humanoid robots may likewise be on the cusp of a similar breakout, thereby helping investors pinpoint the industry’s current stage of development.

• Macroeconomic frameworkOthers

  Technological Unemployment and the Productivity Paradox

  The research report analyzes the coexistence of productivity gains—exceeding 11%—and net job losses—around 4%—driven by AI. This phenomenon aligns with the macroeconomic concept of “technological unemployment,” whereby technological progress, while boosting efficiency, may temporarily displace certain segments of the workforce in the short term. Accordingly, attention should be focused on structural adjustments rather than merely aggregate-level changes.

Key data

• China’s Export Market Share Forecast (2030)16.5%The increase from the current 15% is primarily driven by electric vehicles, batteries, solar energy, and robotics.
• China accounts for the global incremental demand for industrial robots.~50%It demonstrates China’s scale advantages in supply chain development.
• Global humanoid robot shipments in 202513,000–16,000 unitsApproximately 90% of them are manufactured by Chinese producers.
• AI-Driven Productivity Gains in Corporate Production>11%Data from sample companies in highly exposed industries
• Global Net Job Losses Caused by AI4%The United States posted net hiring, while Japan and the United Kingdom experienced significant job losses.

Impact & implications

For China, this signifies the continued success of its manufacturing‑industry upgrade. Shifting from traditional low‑cost production to high‑technology robotics and AI hardware not only enhances the value added of its exports but also reinforces its central position in the global supply chain. For global investors, this underscores the opportunity to focus on China’s high‑end equipment‑manufacturing sector, particularly companies that hold pivotal roles in the humanoid robot supply chain. On the labor front, businesses and policymakers must prioritize “reskilling.” Given that 90% of occupations will be affected—and that the extent of impact varies across countries—education systems and vocational training programs tailored to the AI era will become key social and economic priorities. From an investment perspective, firms offering AI‑powered tools, automation solutions, and workforce reskilling services are likely to stand to benefit from this trend.

Risks

• Geopolitical tensions may dampen short-term market momentum.
• China’s manufacturing sector is grappling with profitability pressures and the risk of overcapacity.
• Market volatility is expected to remain elevated.
• The impact of AI on employment is unevenly distributed across countries and regions, potentially giving rise to social or policy-related resistance.

What to watch

• The sustained growth of China’s humanoid robot exports and the progress of their commercial deployment.
• Productivity Changes and Employment Data Following the Widespread Adoption of AI Technologies Across Industries
• Specific allocation of global capital expenditures (Capex) across the AI, energy, and defense sectors