Why this round of memory tightness is a long-term structural issue rather than a market cycle fluctuation

Major chip manufacturers have recently sent an important signal: memory capacity shortages could persist for years. The puzzle is gradually coming together.

First, let's look at the billion-dollar investment in a super wafer fab in New York State — this is not a typical expansion cycle. The logic behind this investment is very clear: the demand for high-end memory for AI chips is undergoing a qualitative change. From decision-making to implementation and capacity release, the cycle often takes five to ten years. In other words, the industry is making long-term bets on the wave of AI applications over the next decade.

This change in the scale and time span of capital investment fundamentally reflects a shift in market supply and demand from cyclical fluctuations to structural imbalance. Previously, memory shortages were usually inventory cycle issues, which could be adjusted within a few quarters. But now, AI training, inference, and large model deployment are continuously expanding their appetite for computing power and storage, while capacity expansion cycles are far too slow to keep up. This is the core characteristic of structural shortages.