China under the AI and Energy Super-Cycle: Strong Externally, Weak Internally

Overview

This report explores China's medium-to-long-term economic outlook driven by the dual forces of Artificial Intelligence (AI) and the Energy Super-Cycle. The core conclusion is that Asia is experiencing its strongest industrial super-cycle since the mid-2000s, with China set to expand its global export share further due to manufacturing dominance. However, the domestic economy shows 'two-speed' characteristics: internal demand recovery lags, the real estate sector continues adjusting, and rapid AI diffusion may exacerbate labor market frictions in the short term. The report posits that AI's impact on China's economy will be 'neutral in the short term and positive in the long term,' while unlocking growth potential hinges on releasing excess household savings through structural reforms like social security.

Core views

Macro Landscape: Hot Externals, Cool Internals, and Dual-Speed Economy The report notes that nominal investment in high-growth areas of Asia is projected to reach $9 trillion by 2030 (10% CAGR from 2025-2030). This extends beyond AI technology to represent a broad industrial super-cycle. China maintains a dominant position in global manufacturing value-added and is expected to raise its global export market share to 16.5% by 2030. However, this external strength does not fully transmit domestically; increasing capital intensity and automation in the industrial sector have weakened job creation, making labor market slack a critical bottleneck constraining domestic demand. Real Estate & Policy: Continued Adjustment and Fiscal Discipline The real estate market remains in deep adjustment. Although sales rebounded after the Spring Festival, the report suggests this reflects the release of pent-up demand rather than a trend reversal, with most fundamental indicators showing limited improvement. On the policy front, authorities maintain a 'cruise control' mode, with the general fiscal deficit ratio expected to remain around 11.7% of GDP in 2026; the likelihood of additional budgets in the second half is low. Geopolitical tensions have further reinforced the supply-side orientation of policies, meaning PPI recovery is driven more by supply factors than demand, resulting in a narrow base for reflation. AI Industry: From Infrastructure to Profitability and Application China's AI development has entered a 2.0 phase, shifting focus from infrastructure construction to corporate profitability and commercial implementation. Surveys indicate that 51% of enterprises have become AI enablers or adopters. In specific sectors: Power generation sees a shift in AI computing demand from training to inference, driving a surge in data center energy storage system (ESS) deployments; Humanoid robots see 2026 sales forecasts upgraded to 28,000 units with an 85% CAGR from 2025-2030; Autonomous driving sees L2+ penetration reaching 32% in 2026 and breaking 50% by 2030. Additionally, China's AI chip self-sufficiency rate is expected to reach 86% by 2030, though it still needs time to catch up in advanced process nodes and EDA tools. Structural Reform: Unlocking Savings and Managing AI Impact Addressing potential AI-driven job displacement risks, the report views these impacts as transitional but requiring policy mitigation. Chinese household savings rates remain high, and unlocking these funds requires a three-stage process: first, risk appetite restoration guiding fixed deposits toward equities; second, re-anchor inflation expectations to absorb cyclical excess savings; and finally, and crucially, comprehensive social security reform to reduce structural precautionary savings. Calculations show that raising rural pensions slightly above the subsistence level (to 1,000 RMB/month by 2030) would impose an extra fiscal burden of approximately 1% of GDP, which is financially sustainable.

Analysis framework

The report employs a three-tier progressive analytical framework: 'Macro-Industry-Structure.' First, by distinguishing between 'cyclical industrial investment' and 'structural AI trends,' it establishes the breadth of Asia's industrial super-cycle, anchoring China's external competitiveness using export share and manufacturing value-added data. Second, in analyzing the domestic economy, it utilizes an 'income-employment spillover effect' model to reveal the decoupling of industrial growth and employment, explaining why strong external demand has failed to effectively boost domestic demand. Third, in assessing AI impact, it draws on patterns from five historical innovation waves, combining enterprise survey data to deconstruct AI's economic effects into productivity gains (long-term) and labor substitution (short-term) for hedged analysis. Finally, in determining solutions, it adopts a 'savings-consumption' transformation model to quantify the specific fiscal costs and macro benefits of social security reform in lowering precautionary savings, giving the policy recommendations an executable quantitative basis.

Methodology notes

• Macroeconomic framework

  Two-Speed Economic Analysis Framework

  The report decomposes the Chinese economy into two subsystems operating at different speeds: 'External/Industrial' versus 'Internal/Consumption.' This approach helps investors understand why aggregate GDP remains stable while micro-level experiences vary significantly, avoiding misjudgment of the overall economy's temperature by relying on a single indicator.

• Cycle and Business Environment FrameworkCapacity/Equipment Cycle (Juglar)

  Asian Industrial Super-Cycle

  The report identifies Asia as being in a robust capital expenditure cycle similar to the mid-2000s, encompassing not only AI but also extensive industrial and intellectual property investments. This represents a typical Juglar cycle (equipment investment cycle) analysis used to judge medium-to-long-term capacity expansion and economic growth momentum.

• Industry/Vertical Analysis FrameworkPenetration S-curve

  AI and New Energy Vehicle Penetration Forecasting

  The report uses S-curve penetration models to forecast metrics such as humanoid robot adoption, L2+ autonomous driving penetration, and AI chip self-sufficiency rates (e.g., L2+ rising from 25% to 50%). This is a core method for identifying the industrialization stage of new technologies, helping to distinguish between conceptual hype phases and performance realization phases.

• Company Fundamentals and Financial Framework

  Revenue-Employment Spillover Elasticity

  By analyzing changes in the slope of corporate revenue growth versus employment growth, the report finds that the industrial sector's ability to drive employment via revenue growth is weakening. This micro-elasticity metric serves as key evidence for the phenomenon of 'growth without jobs,' offering greater foresight than simply looking at unemployment rates.

• Macroeconomic framework

  Savings-Consumption Three-Stage Transformation Model

  The report structures the process of releasing household excess savings into three stages: risk appetite restoration, re-anchoring of inflation expectations, and social security reform. This provides a clear roadmap for understanding the rhythm of consumption recovery, avoiding linear extrapolation of consumption stimulus effects.

Key data

• Forecast of China's Global Export Share by 203016.5%In the baseline scenario, expected to rise continuously from current levels, reflecting expanded manufacturing competitive advantages
• Forecast of General Fiscal Deficit Ratio for 202611.7%Flat compared to 2025; no additional budget expected for H2, maintaining policy resolve
• Forecast of China's Humanoid Robot Sales Volume for 202628,000 unitsCAGR of 85% expected from 2025-2030; commercialization accelerating
• Forecast of L2+ Intelligent Driving Penetration Rate for 202632%Expected to exceed 50% by 2030; intelligent driving entering a period of rapid popularization
• Forecast of China's AI Chip Self-Sufficiency Rate by 203086%Process of domestic substitution accelerating, though advanced process nodes remain a短板 (weak link)
• Extra Fiscal Cost of Rural Pension Reform~1% GDP/yearFiscal burden remains manageable if rural pensions are raised to 1,000 RMB/month by 2030

Impact & implications

For the China market, this implies highly structured investment opportunities. Segments benefiting from the global industrial super-cycle and AI implementation (such as energy storage, humanoid robot value chains, intelligent driving, and semiconductor equipment) possess clear incremental logic. Conversely, segments related to traditional domestic demand and the real estate chain must await substantive landing of structural policies like social security reform. The 'Chips-Rare Earths' mutual dependence formed between China and the US provides a temporary stabilizer for bilateral relations, reducing the risk of extreme decoupling and supporting foreign investors' baseline allocation to Chinese assets. Simultaneously, AI-induced employment friction highlights the need to monitor policy developments regarding vocational skills training and flexible employment protection, which are both necessary for social stability and prerequisites for restoring consumer confidence.

Risks

• Rapid AI diffusion causing unforeseen short-term job displacement, dampening household income and consumption confidence
• Real estate market adjustment lasting longer than expected, dragging down local fiscal health and financial system stability
• Escalation of geopolitical tensions disrupting the 'chips-rare earths' balance, triggering supply chain interruptions
• Slow progress in social security reform preventing effective conversion of precautionary savings into consumption
• Intensification of global trade protectionism hindering the rise of China's export share

What to watch

• Profit realization and margin improvement情况的 reflected in AI corporate earnings reports
• Actual shipment volumes and penetration rate data for humanoid robots and L2+ intelligent driving
• High-frequency real estate sales data and changes in inventory destocking cycles
• Policy details of social security reform and signals of fiscal expenditure structure adjustment
• Progress of China-US trade negotiations and dynamics regarding tariffs/export controls
• Household savings rates and risk appetite indicators (e.g., deposit migration, fund subscriptions)