Fueled by the global surge in computing power demand driven by artificial intelligence, technology stocks in the A-share market have reported substantial earnings growth, with their share prices continuing to climb.
Amid the global increase in demand for computing power sparked by AI, Chinese A-share technology stocks, particularly those focused on AI computing hardware, have maintained an upward trajectory. On April 17, domestic optical chip leader
Concurrently, A-share optical communication concept stocks, such as those related to "optical modules," "CPO (co-packaged optics)," and "optical chips," have continued their ascent. The phrase "you need to stand in the light" has become a hot topic among A-share market investors recently. Meanwhile, the ChiNext Index, heavily weighted by optical communication concept stocks like the "Yi Zhong Tian" trio—
In reality, as AI-led technology stocks have rallied, their prices have continued to rise, while consumer stocks, represented by baijiu, have underperformed in recent years. In August 2025, domestic computing power leader
Statistics show that as of the close on April 17, apart from
The direct driving force behind this bull market in A-share technology stocks is the explosive growth in global demand for AI-related computing power. Since ChatGPT went viral worldwide at the end of 2022, global cloud service providers have significantly increased their capital expenditures, boosting investments in AI computing infrastructure. It is understood that the four major North American cloud providers (Microsoft, Amazon, Google, Meta) have seen sustained substantial growth in capital expenditures since 2024. Their combined capital expenditure in 2024 was approximately $228 billion, a year-on-year increase of about 55%. In 2025, the combined capital expenditure of these four cloud providers continued to grow, reaching around $406 billion, a year-on-year increase of approximately 78%. Entering 2026, based on provided guidance, the total capital expenditure of the four major cloud service providers is expected to exceed $600 billion, a year-on-year growth of over 60%. Specifically, Google plans a total capital expenditure of $175-185 billion for 2026, a year-on-year increase of 91%-102%, nearly doubling. Amazon has guided for a total capital expenditure of $200 billion in 2026, a year-on-year increase of about 59%. Meta's capital expenditure guidance for 2026 is $115-135 billion, a year-on-year increase of 60.84%-88.81%, while Microsoft's guidance is approximately $140-150 billion.
Simultaneously, major domestic internet companies are also ramping up their AI computing infrastructure investments. According to public information, ByteDance's capital expenditure for 2025 was 150 billion yuan, with a planned capital expenditure of 160 billion yuan for 2026. Alibaba's (9988.HK) capital expenditure for fiscal year 2025 was 92.5 billion yuan, with a planned capital expenditure of 380 billion yuan for 2025-2027. Tencent's (0700.HK) capital expenditure for 2025 was 79.2 billion yuan, with plans to at least double its investment in AI new products in 2026.
The substantial increase in capital expenditure by global cloud providers is primarily used for building AI data centers, directly driving demand for AI computing hardware. From the perspective of the computing hardware industry chain, it mainly includes AI computing chips dominated by GPUs, memory chips dominated by HBM, and communication/interconnect sectors like optical modules and PCBs, corresponding to computing, storage, and communication segments, respectively.
Within the global AI industry chain division of labor, A-share listed companies hold a significant advantage in communication/interconnect segments like optical modules and PCBs, while also catching up rapidly in the GPU computing chip segment. Consequently, benefiting from the surge in global AI computing demand, especially A-share optical module and PCB companies embedded in the North American computing power supply chain, have seen sustained and substantial earnings growth.
The Q1 2026 report disclosed by optical module leader
The other two optical module companies,
As share prices of A-share AI computing hardware-related companies have surged significantly, market focus is gradually shifting to whether the growth trend in global computing power expenditure driven by this round of AI technological revolution can be sustained and for how long. This will determine whether the earnings growth of related companies can be maintained.
Regarding global AI computing power demand, NVIDIA's founder and CEO Jensen Huang previously provided a ten-year demand outlook. At the APEC CEO Summit in October 2025, he stated that global trillion-dollar computing infrastructure construction had just begun, with the new round of global computing infrastructure build-out only completing its "first year." He suggested a full cycle would take at least ten years. He mentioned that the rise of AI marks the beginning of a brand-new computing era. We are at the start of a new ten-year construction cycle. With the advent of the AI era, every layer of the entire computing architecture is being radically transformed. He also predicted that AI would reshape global industries worth up to $100 trillion in the future.
According to Goldman Sachs estimates, based on the continued investment in AI infrastructure by global tech giants and the widespread application demand for AI technology across various industries, cumulative global AI infrastructure investment is expected to reach $3-4 trillion by 2030, approximately equivalent to 20.48-27.3 trillion yuan.
However, as large-scale AI computing infrastructure build-out enters its fourth year, the market is increasingly concerned about whether such massive computing power investments can yield corresponding returns. This year, following the earnings releases of US-listed cloud providers like Google and Amazon, although their performance was strong, the simultaneous announcement of significant capital expenditure increases caused stock price volatility, indicating the market's "capital expenditure punishment" for tech giants (a shift from anticipating "future growth" to anxiety over "current costs," leading to short-term stock price declines). Domestically, after internet giants like Tencent indicated substantial increases in AI investment, their stock prices also experienced significant fluctuations.
From the demand side, as the global number of tokens accelerates growth, each token requires computing power or cloud computing support. These capital expenditures can achieve considerable returns on investment in cloud revenue and cloud profits, with relatively high visibility. Furthermore, at the application level, recalling the development of mobile internet, the initial phase also saw rising users and usage rates without immediate revenue generation. Once scale was achieved, monetization was eventually realized through models like subscriptions, advertising, and transaction commissions.
Meanwhile, although A-share AI computing-related company stocks have performed well, many A-share market investors, having missed out on the earlier rally, remain cautious about buying at high levels. A Beijing-based private equity investor mentioned that while the industry trend for optical modules is indeed positive, chasing highs is not advisable, as the previous price increases have already priced in future earnings. He stated that if stock prices later correct to a reasonable range, he would consider making some allocations. Completely missing out would be regrettable, but if no suitable buying opportunity arises, he would forgo it, noting that the market is never short of opportunities, but also never short of risks. Another Shanghai-based subjective private equity firm with billions under management, which also missed the optical module rally, bluntly stated that trees don't grow to the sky.
However, based on industry expectations from relevant A-share companies, AI computing-related demand is likely to remain high for the next year or two. The minutes from
Goldman Sachs' latest in-depth report on AI capital expenditure points out that AI has moved from pilot projects to scaled implementation, with Agentic AI becoming the core evolution direction. The global technology supply chain is experiencing the largest capital expenditure cycle in history, benefiting computing power, chips, semiconductor equipment, and storage across the board, with clear long-term growth logic for the industry.
Morgan Stanley predicts that future computing power demand growth will be three times the compound annual supply growth forecast by NVIDIA. The shortage of computing power will persist and intensify. With the launch of new-generation chips, AI computing costs will decrease significantly, leading to a further explosion in demand. This implies that computing power suppliers, including chip manufacturers, optical communication companies, and data center equipment providers, will enjoy long-term structural benefits.