Author: Long Yue
Source: Hard AI
The wave of artificial intelligence is not only about algorithms and computing power; it also hides a competition regarding energy and physical infrastructure. In addition to chips and servers, the power systems that provide energy for AI data centers, the cooling technologies that ensure their stable operation, and the metal materials needed for construction are collectively 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 &#34;non-IT&#34; infrastructure capital expenditure is expected to reach 800 billion yuan.
The report predicts that by 2030, global AI-related capital expenditure will exceed 1.2 trillion USD. Among them, the Chinese market will play a key role, with total AI capital expenditure expected to grow from 600 to 700 billion yuan in 2025 to 2 to 2.5 trillion yuan by 2030, at a compound annual growth rate of 25-30%.
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Energy supply is seen as the cornerstone of AI development. About one-third of these investments, amounting to as much as 800 billion yuan, will be used to support the non-IT infrastructure for AI data centers. This includes power generation and transmission (38%), metals needed for data center construction (12%), advanced cooling systems (10%), and other engineering construction.
This trend brings clear investment opportunities in fields such as nuclear power, grid equipment, energy storage, backup power sources, and advanced cooling technologies, and has already transmitted to upstream metal markets like copper, aluminum, and uranium.
With the explosive growth in AI computing power demand, the focus of the global AI competition is shifting from computing power itself to energy. According to the International Energy Agency (IEA), it is expected that by 2030, the electricity consumption of data centers in China will increase from 102 terawatt-hours (TWh) in 2024 to 277 TWh, with an average compound annual growth rate of 18%.
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<h2>Powering AI: Five Major Opportunities Emerge</h2>
&#34;Without electricity, there is no AI.&#34;
The training and inference processes of AI models require enormous computing power, which in turn leads to equally enormous energy consumption.
The report states that the surge in electricity demand is mainly driven by three factors: first, the accelerated replacement of traditional data centers by AI data centers; second, the sharp increase in power consumption of high-performance computing chips represented by NVIDIA's Blackwell architecture, with its GB200 chip consuming as much as 2.7 kilowatts, far exceeding previous generations; and finally, the power density of server cabinets continues to rise, with the report predicting that the thermal design power (TDP) of NVIDIA's next-generation Rubin Ultra NVL576 architecture cabinet could reach as high as 600 kilowatts
The report believes that compared to Europe and the United States, China has advantages in power reserves, costs, renewable energy supply chains, and grid facilities and equipment supply.
It is estimated that by 2025, China's effective backup margin for the power grid will be about 30%, higher than the less than 25% in the United States and about 15% in the European Union. In addition, China's industrial electricity prices are 30-60% lower than those in the United States and the European Union, and the grid facilities are younger, with an average service life of less than 20 years, while in Europe and the United States, it generally exceeds 40 years.
China's power advantages pave the way for the development of AI data centers, bringing five major investment opportunities.
<blockquote>
<ul>
<li>Nuclear Power and Uranium: Nuclear power, due to its stability, efficiency, and low carbon characteristics, has become an ideal baseload power source for AI data centers. The report predicts that by 2030, China's nuclear power installed capacity will increase from 60 gigawatts (GW) in 2025 to 100 GW, accounting for 60% of the global nuclear power capacity under construction. This will directly lead to a shortage of uranium resources and price increases.</li>
<li>Grid Equipment: The global upgrade of power grids and the additional load brought by AI are driving a surge in demand for key equipment such as transformers. Chinese suppliers, with their strong supply chain and capacity advantages, are expected to fill the gap in the global market.</li>
<li>Energy Storage Systems (ESS): Energy storage systems are essential to ensure power stability. The report predicts that from 2024 to 2030, the global new installed capacity of ESS will grow at a compound annual growth rate of 21%, while the order growth rate for Chinese companies is expected to exceed 30%.</li>
<li>Diesel Generators: As the last line of defense during power outages at data centers, the market demand for diesel generators is strong. The report estimates that from 2024 to 2027, the compound annual growth rate of this market will reach 28%.</li>
<li>Special Power Supplies: The value and technical requirements of special power supply systems such as high-voltage direct current (HVDC) and power supply units (PSU) inside AI servers are rising sharply with the exponential increase in chip power consumption.</li>
</ul>
</blockquote>
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<h2>Cooling AI: The Surge in Demand for Liquid Cooling Technology and Key Metals</h2>
High-performance chips generate significant heat while providing powerful computing capabilities. The report points out that for every 10°C increase in server temperature, equipment reliability may decrease by 50%. Therefore, efficient heat dissipation has become the lifeline of AI data centers.
The report emphasizes that as the power density of AI servers rises sharply, traditional air cooling technology can no longer meet the cooling needs, and liquid cooling technology is becoming a necessary choice.
Bank of America predicts that China's liquid cooling market will expand at an average annual compound growth rate of 42% between 2025 and 2030, with market penetration reaching 45% by 2030. Compared to traditional air cooling, liquid cooling technology has a heat transfer efficiency that is 20-50 times higher and can save up to 30% of electricity. Bank of America analysts noted in the report that emerging technologies such as immersion cooling are also gaining more attention
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At the same time, the construction of AI data centers relies on basic metals such as copper and aluminum. For example, copper plays a crucial role in power transmission, signal transmission, and thermal management.
<blockquote>
<ul>
<li>Copper: As a core material in power transmission and heat dissipation systems, the demand for copper will increase significantly. Bank of America predicts that by 2030, the copper demand directly driven by AI data centers in China will grow to nearly 1 million tons, accounting for 5-6% of China's total copper demand at that time. In addition, indirect demand from power grids and electrical equipment will further amplify copper consumption.</li>
</ul>
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<ul>
<li>Aluminum: Also important in the structural components and heat dissipation equipment of data centers. The report predicts that by 2030, data centers will drive a demand for 695,000 tons of aluminum, achieving a compound annual growth rate of 16% compared to 2025.</li>
<li>Tungsten, tin, gallium and other rare metals also play an indispensable role in chip manufacturing.</li>
</ul>
</blockquote>
<h2>Engineering Construction: Building the Physical Foundation of the AI Era</h2>
In the 800 billion yuan non-IT infrastructure market, engineering and construction (E&amp;C) is also an essential part. Report data shows that in the non-IT cost structure of data centers, engineering construction and other related expenses account for as much as 40%, making it the largest expenditure after power systems.
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This portion of investment is mainly driven by national strategic projects. The report specifically mentions China's &#34;East Data West Computing&#34; project. The implementation of these large projects directly translates into a huge demand for civil engineering, construction installation, project management, and other services. The construction of these data center clusters involves not only the buildings themselves but also a series of complex engineering tasks such as grid access and fiber optic network deployment.
Bank of America's report reveals a new landscape for investors amid the AI boom. In addition to well-known semiconductor and software companies, a vast ecosystem composed of power, industrial, and materials companies is becoming an indispensable cornerstone of the AI era. The report believes that leading companies in related fields will benefit significantly.
This article is from the WeChat public account &#34;Hard AI&#34;. For more cutting-edge AI news, please click here
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Bank of America expects that by 2030, China's capital expenditure in non-IT fields such as power systems, cooling technology, and key metals will account for one-third of total AI investment, creating a massive market worth 800 billion yuan. By then, the copper demand directly used by AI data centers in China will reach approximately 1 million tons, accounting for 5-6% of China's total copper demand at that time

- The article discusses the emerging investment opportunities in the energy and physical infrastructure sectors driven by the growth of artificial intelligence (AI) in China.  
- A report predicts that by 2030, China's AI-related non-IT infrastructure capital expenditure will reach 800 billion RMB, with global AI capital spending exceeding 1.2 trillion USD.  
- Key areas for investment include nuclear power, energy storage systems, and advanced cooling technologies, highlighting the critical role of energy supply in supporting AI data centers.

Electricity, heat dissipation, metals, and engineering construction, China's AI data center's "non-IT infrastructure" will be an 800 billion market