The AI memory squeeze may not ease before 2028

The AI memory crunch stems not from transient supply-demand gaps but from the convergence of generational tech shifts and fragmented global capacity. High-bandwidth memory like HBM3E and LPDDR5X—essential for AI training—relies on advanced packaging and 1β/1γ DRAM nodes, producible only by Samsung, SK Hynix, and Micron, creating a de facto oligopoly. Cloud hyperscalers locking in multi-year contracts are engaging in defensive stockpiling, inflating costs for smaller players and delaying edge AI adoption. U.S. export controls on semiconductor equipment further delay Chinese capacity ramp-up, worsening global misallocation. Over the next 12–24 months, a structural imbalance—tight high-end, glutted low-end—will accelerate architectural pivots toward CXL-based memory pooling or near-memory computing. No new fab will meaningfully alleviate supply before 2027, making memory the most fragile choke point in the AI arms race.