Markets have been experiencing wide-ranging fluctuations recently, and as the recovery from earlier oversold conditions continues, rotations within the technology sector and divergence among individual stocks have accelerated. Where will the industrial value of the AI supply chain be redistributed next, and what allocation strategy should be adopted from an investment perspective? We turn to Wang Li, senior macro strategy researcher at Great Wall Fund, for his analysis on these questions.
Wang Li notes that the distribution of value within the AI supply chain is evolving from a focus on core computing power to a broader spread across the entire industry chain. Over the past two years, the central challenge for AI industry growth was insufficient computing capacity, which meant that segments with high technical barriers, such as GPUs, advanced packaging, and high-speed interconnect, benefited first. As large-scale models continue to expand, the bottlenecks in AI infrastructure are shifting from single-chip performance to system-level capabilities like data transmission, energy supply, and cooling. Consequently, the importance of supporting components, including optical modules, PCBs, liquid cooling, and power equipment, is rising, and industrial value is beginning to flow to more segments.
From an industry cycle perspective, Wang believes AI is still in its infrastructure build-out phase, with capital expenditure serving as the primary driver. However, as large model capabilities improve and commercial applications gradually progress, the value chain is likely to extend further toward software and application layers. He suggests that the future of the AI industry is not a simple transfer of value; instead, as the industry expands, the value contribution of each segment will rise together. Investment opportunities will likewise broaden from the early focus on core computing power to include infrastructure, energy security, and application ecosystems.
From a fund investment standpoint, Wang argues that technology growth assets are still in a phase of long-term industrial trend development, but investment strategy needs to pay closer attention to structure and timing. The new technology cycle, led by AI, continues to advance, with strong industrial potential in areas like computing infrastructure, semiconductor self-innovation, and intelligent applications. Recent market volatility is more a result of valuation adjustments, crowded trading, and a repricing of earnings delivery timelines, rather than a sign that the industrial trend has changed.
"Therefore, investors in technology growth should neither exit simply due to short-term fluctuations nor chase rallies blindly, but instead return to industry fundamentals and earnings delivery," Wang emphasizes. He suggests focusing on sub-sectors with sustained demand growth, clear competitive landscapes, and solid earnings support, while seizing opportunities after pullbacks based on valuation levels and shifts in market sentiment. Tech growth is better suited as a medium-to-long-term focus, with phased positioning and dynamic adjustments helping to smooth out volatility.
Looking ahead, Wang believes technology growth will remain a key focus for the market, with strong industrial trends in areas such as the AI supply chain, robotics, high-end manufacturing, and self-sufficiency. In AI, as computing infrastructure continues to improve and applications gradually come online, investment opportunities will expand from early-stage computing construction into energy security, core components, and application ecosystems. Robotics is moving from technical validation toward industrialization, and as costs decline and use cases broaden, companies in the supply chain with core technology and mass-production capabilities are poised to benefit first. Additionally, semiconductor localization and high-end manufacturing upgrades hold long-term value, as global supply chain restructuring and the push for self-reliance will continue to drive these fields.
He also cautions that tech investment must ultimately be anchored in earnings delivery. The market is likely to shift from broad theme dispersion toward picking leaders, with greater attention on companies that possess technical barriers, competitive advantages, and earnings growth potential.