Memory stocks: Morgan Stanley explains how to play the new AI bottleneck [Yahoo! Finance]
Morgan Stanley (MS)
Last morgan stanley earnings: 4/16 07:15 am
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Source: Yahoo! Finance
Analyst Shawn Kim wrote that “memory sits in a capacity-constrained cycle with unusually long order visibility driven by AI inference,” adding that for 2026, “the risk is execution and transition, not demand.” The firm argues that inference workloads increasingly depend on memory access, not just processing power. According to Morgan Stanley, “memory access increasingly determines the performance of longer text, image/video and Agentic AI workflows,” requiring more advanced server DRAM and enterprise NAND to support context-heavy and continuously learning systems. Kim explained that the memory market is entering a rapid pricing upcycle, noting: “We expect a steeper upcycle with rapid gains in DRAM, HBM, NAND, and legacy memory.” The analyst estimates that text-only AI inference could consume “35% of 2026 global memory supply for DRAM and 92% for NAND.” Supply, rather than demand, is said to now be the central debate. Morgan Stanley's channel checks point to “potential upsid
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MS
Earnings
- 1/15/26 - Beat
MS
Sec Filings
- 1/16/26 - Form FWP
- 1/16/26 - Form 4
- 1/16/26 - Form 4
- MS's page on the SEC website