Power, cooling, metals, and engineering construction: the “non-IT infrastructure” of China’s AI data centers will be a huge 800 billion yuan market.

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Author: Long Yue

Source: Hard AI

The wave of artificial intelligence is not only about algorithms and computing power, but also hides a competition revolving around energy and physical infrastructure. In addition to chips and servers, the power systems that drive AI data centers, the cooling technologies that ensure stable operation, and the metal materials required for construction are together forming a brand new investment field.

According to a recent report released by Bank of America Global Research, by 2030, the market size of China’s AI-related “non-IT” infrastructure capital expenditures is expected to reach 800 billion yuan.

The report predicts that by 2030, global AI-related capital expenditures will exceed $1.2 trillion. Among them, the Chinese market will play a key role, with total AI capital expenditures rising from 600 billion to 700 billion yuan in 2025 at a compound annual growth rate of 25-30%, reaching 2 trillion to 2.5 trillion yuan by 2030.

Among these, energy supply is seen as the cornerstone of AI development. About one third of these investments—up to 800 billion yuan—will be used to support non-IT infrastructure for AI data center operations. This includes electricity production and transmission (38%), metals required for data center construction (12%), advanced cooling systems (10%), and other engineering and construction.

This trend has brought clear investment opportunities to areas such as nuclear power, power grid equipment, energy storage, backup power, and advanced cooling technology, and has already transmitted impacts upstream to metal markets for copper, aluminum, uranium, and more.

With the explosive growth in demand for AI computing power, the focus of the global AI race is shifting from computing power itself to energy. According to data from the International Energy Agency (IEA), by 2030, the electricity consumption of Chinese data centers is expected to increase from 102 terawatt-hours (TWh) in 2024 to 277 TWh, with a compound annual growth rate as high as 18%.

Powering AI: Five Major Opportunities Emerge

“Without electricity, there is no AI.”

The training and inference processes of AI models require massive computational power, and behind that is equally massive energy consumption.

The report states that the surge in electricity demand is mainly driven by three factors: First, AI data centers are rapidly replacing traditional data centers; second, power consumption of high-performance computing chips, exemplified by Nvidia's Blackwell architecture, has risen sharply, with the GB200 chip consuming as much as 2.7 kilowatts, far exceeding previous generations; finally, the power density of server cabinets continues to rise, with the report predicting the thermal design power (TDP) of Nvidia's next-generation Rubin Ultra NVL576 cabinet could reach as high as 600 kilowatts.

The report believes that compared to Europe and the US, China has advantages in electricity reserves, costs, renewable energy supply chains, grid facilities, and equipment supply.

It is estimated that in 2025, the effective reserve margin of China’s power grid will be about 30%, higher than less than 25% in the US and about 15% in the EU. In addition, China's industrial electricity prices are 30-60% lower than those in the US and EU, and the grid facilities are newer, with an average service life of less than 20 years, compared to over 40 years in the West.

China’s power advantages pave the way for the development of AI data centers, bringing five major investment opportunities.

Nuclear Power and Uranium: Due to its stable, efficient, and low-carbon characteristics, nuclear power is becoming the ideal base-load power for AI data centers. The report foresees that by 2030, China’s installed nuclear power capacity will increase from 60 gigawatts (GW) in 2025 to 100 GW, accounting for 60% of the world’s nuclear power capacity under construction. This will directly lead to shortages and price increases of uranium resources.Power Grid Equipment: Grid upgrades worldwide and incremental loads brought by AI are driving surging demand for key equipment such as transformers. Chinese suppliers, with robust supply chains and production capacity, are expected to fill the global market gap.Energy Storage Systems (ESS): To ensure power stability, energy storage systems are indispensable. The report predicts that between 2024 and 2030, the global newly installed capacity of ESS will grow at a compound annual rate of 21%, while order growth of Chinese companies is expected to exceed 30%.Diesel Generators: As the last line of defense for data centers during power outages, the diesel generator market is in strong demand. The report forecasts a compound annual growth rate of 28% in this market from 2024 to 2027.Specialized Power Supplies: High-voltage direct current (HVDC), power supply units (PSU), and other specialized power systems inside AI servers are increasing in value and technical requirements, as chip power consumption grows exponentially.

Cooling AI: Soaring Demand for Liquid Cooling Technology and Key Metals

High-performance chips deliver tremendous computing power while also generating massive amounts of heat. The report states that for every 10°C increase in server temperature, device reliability may decrease by as much as 50%. Therefore, efficient cooling is the lifeblood of AI data centers.

The report emphasizes that as the power density of AI servers soars, traditional air cooling is no longer sufficient, and liquid cooling is becoming inevitable.

Bank of America predicts that between 2025 and 2030, China’s liquid cooling market will expand at a compound annual growth rate of 42%, reaching a market penetration rate of 45% by 2030. Compared with traditional air cooling, liquid cooling has 20-50 times higher heat transfer efficiency and can save up to 30% in electricity. Analysts point out that emerging technologies such as immersion cooling are also gaining more attention.

At the same time, the construction of AI data centers cannot proceed without basic metals such as copper and aluminum. For example, copper plays a crucial role in power transmission, signal transmission, and thermal management.

Copper: As a core material for power transmission and cooling systems, copper demand will rise sharply. Bank of America predicts that by 2030, copper demand directly driven by China’s AI data centers will reach nearly 1 million tons, accounting for 5-6% of China’s total copper demand at that time. Furthermore, indirect demand from grids and power equipment will further amplify copper consumption.

Aluminum: Also critical in data center structural parts and cooling equipment. The report forecasts that by 2030, data centers will drive demand for 695,000 tons of aluminum, with a compound annual growth rate of 16% from 2025.Tungsten, Tin, Gallium and other rare metals are also indispensable in chip manufacturing.

Engineering and Construction: Building the Physical Foundation for the AI Era

Within the 800-billion-yuan non-IT infrastructure market, engineering and construction (E&C) is also an indispensable part. Report data shows that in the non-IT cost structure of data centers, engineering and construction and other related expenses account for as much as 40%, making it the largest expenditure except for power systems.

This part of investment is mainly driven by national-level strategic projects. The report specifically mentions China’s “Eastern Data Western Calculation” project. The rollout of these large-scale projects directly translates into huge demand for civil engineering, construction and installation, project management, and more. The construction of these data center clusters involves not only the buildings themselves but also supporting projects such as grid access, optical fiber network laying, and a series of complex engineering tasks.

Bank of America’s report reveals a new map under the AI boom for investors. Besides the well-known semiconductor and software companies, a massive ecosystem including power, industry, and materials companies is becoming an indispensable cornerstone of the AI era. The report believes that leading enterprises in these related fields will significantly benefit.

This article is from WeChat public account “Hard AI”. For more cutting-edge AI news, please visit here

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