A Volatile Rebound
On July 30, the semiconductor market witnessed one of its most significant rebounds in recent history. Micron Technology saw its shares climb 18%, while SanDisk surged 26%. This sudden upward momentum stood in stark contrast to a broader monthly trend that saw many chip stocks suffering their worst performance since the 2008 financial crisis. For investors, the question remains: is this a temporary spike, or are we witnessing the beginning of a sustained structural shift in how the market values AI-related memory?
The Engines Behind the Growth
The rally can be traced back to a perfect storm of positive indicators for memory manufacturers. Primary drivers include:
- Unprecedented Azure growth of 43%, signaling massive demand for cloud computing capacity.
- Record-high memory pricing driven by the intensive requirements of AI training and inference.
- Systemic supply constraints that analysts suggest may persist through 2028.

The Long-Term Supply Crunch
While chipmakers are aggressively increasing their capital expenditure (capex) to expand manufacturing capacity, the reality is that new supply is slow to hit the market. Current projections suggest that major capacity expansion efforts may not fully come online until 2029 or 2030. Deloitte reports that costs for AI server dynamic random-access memory (DRAM) roughly doubled in the first quarter of 2026 alone, with the potential for a fourfold increase throughout the year.
The extraordinary capital investment cycle in AI infrastructure by hyperscale operators has driven server memory intensity to unprecedented levels.
— Dataintelo Market Research Report 2034
What This Means for the Future
The divergence between Wall Street’s high expectations and the physical limitations of chip production is creating a high-volatility environment. As hyperscale cloud providers lock in long-term supply agreements to secure their AI roadmaps, chipmakers like Micron and SanDisk find themselves in a powerful position. However, the market remains sensitive to any signals that the 'fire-hose' of AI capital spending might be throttled, leading to the rapid price fluctuations currently observed.
