China Galaxy Securities has released a research report indicating that the large-scale advancement of artificial intelligence is driving a rapid restructuring of infrastructure systems, with the synergy between energy and computing power emerging as a critical pillar for fostering new quality productive forces. A stable, low-cost, and green energy supply capability is set to become a decisive factor influencing the layout and competitiveness of the AI industry. China is currently expediting the construction of its "Six Networks" initiative, promoting the coordinated development of energy, computing, and communication infrastructure to provide systematic support for industrial upgrades and economic growth in the AI era.

Looking ahead, the large-scale construction of computing infrastructure such as data centers and intelligent computing hubs will not only drive demand for servers, chips, and other computing equipment but also spur concurrent investment expansion in power supplies, power grids, energy storage, and power distribution systems. For the capital markets, AI computing investment is gradually shifting from a pure "chip and server rally" toward an extension into "power infrastructure momentum." The key viewpoints from China Galaxy Securities are outlined below.

Artificial intelligence is systematically reshaping the structure of energy demand and the global landscape of energy competition. As computing demand transitions from phase-based model training to large-scale inference services, data centers are evolving from peak-demand profiles to sustained, stable high-base-load requirements, placing greater demands on the reliability, flexibility, and carrying capacity of power systems. AI data centers exhibit new characteristics such as high power density, high reliability, and strong spatial clustering, and energy constraints have expanded beyond merely meeting incremental electricity demand to encompass system-level capabilities including grid integration, energy storage, cooling, and infrastructure coordination. Going forward, global AI competition will accelerate its shift from resource endowment rivalry to competition in energy-computing synergy capabilities, where a stable, low-cost, and green energy supply system becomes essential for supporting computing growth and shaping industrial advantage.

In the AI era, competition between China and the United States is transitioning from energy resource competition to energy system capability competition, with energy security, resource allocation efficiency, and cost control emerging as decisive factors for AI industry development. The U.S. benefits from flexible market mechanisms and strong short-term supply response capabilities, while China leverages its comprehensive infrastructure system and notable advantages in long-term planning; however, both nations need to further modernize their energy systems. The future of AI competition hinges on the ability to efficiently coordinate energy, electricity, computing power, and industrial applications. The U.S., relying on mature energy markets, abundant natural gas resources, and nuclear power deployments, can quickly establish reliable capacity and use market mechanisms and long-term power purchase agreements to dynamically match energy with computing demand, offering short-term advantages in supply security and cost, yet it faces challenges such as slow grid expansion, insufficient cross-regional transmission capacity, and pressure from low-carbon energy transition. China, leveraging the world's largest unified power grid, an ultra-large-scale power system, and major infrastructure projects like the "East Data, West Computing" initiative, continues to enhance reliable power supply capabilities and energy-computing coordination efficiency, providing systemic support for the large-scale build-out of AI infrastructure. Nevertheless, the rising share of renewable energy generation in China brings challenges including insufficient flexible regulation capacity in the power system and the need to strengthen energy storage and cross-regional consumption capabilities, meaning that advantages in renewable resources have not yet been fully converted into stable, low-cost computing advantages.

For the AI era, the energy system must shift from merely satisfying incremental power demand to building system capabilities that support long-term computing development. Relying solely on expanding installed power capacity cannot sustainably meet AI's demands for large-scale, stable, low-cost, and low-carbon electricity. It is imperative to promote coordinated planning between energy and computing, optimizing the spatial distribution of computing capacity based on energy resources, grid carrying capacity, and industrial layout, thereby improving the efficiency of converting energy resources into computing capabilities. Concurrently, to address computing security needs under high-penetration renewable energy conditions, efforts should accelerate the development of energy storage, grid regulation, and intelligent dispatch capabilities to enhance power system flexibility, while also leveraging AI's reverse-enabling role in renewable forecasting, grid operations, and load regulation. On this basis, integrating energy-computing synergy into the "Six Networks" construction, alongside coordinated planning with communication and logistics infrastructure, will drive the joint development of infrastructure networks with advanced manufacturing, strategic emerging industries, and future industries, forming a conversion chain from energy resources and infrastructure to computing capability and industrial competitiveness.

Risk warnings: 1. Risks related to inadequate understanding of policies; 2. Risks of policy implementation falling short of expectations; 3. Risks arising from uncertainties in technological development.