Prediction: This Artificial Intelligence (AI) Memory Stock Will Go Parabolic on Oct. 30
As technology companies race to build data centers, demand for the memory chips that make artificial intelligence (AI) computing possible has skyrocketed. One of the leading manufacturers of memory chips for AI hyperscalers is Micron Technology (NASDAQ: MU).
So far this year, Micron stock has soared 225% — making it the third-highest performer in the Nasdaq-100. Nevertheless, Micron’s shares have experienced considerable volatility over the last couple of months and trade about 24% below their all-time high.
Missed AI’s “Act 1”? Act 2 Could Be 14x Bigger.Most investors think they missed the AI boat because they didn’t buy Nvidia in 2005. But according to our analysts, we’re only at the end of “Act 1″—the R&D phase. “Act 2” is the global rollout.Continue »
I think this disconnect is about to reverse. On Oct. 28 and 29, Alphabet(NASDAQ: GOOGL) (NASDAQ: GOOG) and Amazon(NASDAQ: AMZN) are scheduled to report quarterly earnings. While investors will undoubtedly focus on their respective AI-related capital expenditures (capex), I think another topic could emerge as a major discussion point: the global memory shortage. If my prediction is accurate, Micron could begin to rally just in time for Halloween.
Amazon already warned investors about rising memory costs
For most of the AI revolution, investors primarily associated infrastructure with graphics processing units (GPUs) designed by Nvidiaand application-specific integrated circuits (ASICs) designed by Broadcom. However, GPUs and custom silicon cannot operate efficiently without sufficient memory. Micron manufactures dynamic random access memory (DRAM) and high bandwidth memory (HBM), both of which are critical components of the AI chip stack.
Interestingly, Amazon CEO Andy Jassy already highlighted the growing importance of memory during the company’s last earnings call. Jassy explained that Amazon planned to increase its 2026 capex budget to $220 billion—up from its previous forecast of $200 billion — specifically because of higher memory costs.
Meanwhile, Alphabet raised its 2026 capex forecast to $195 billion to $205 billion during its second-quarter earnings call. Management attributed the increase to accelerating infrastructure investments and capacity supply constraints. Although Alphabet did not explicitly identify memory as the culprit, its comments reinforce the underlying idea that demand for AI compute is insatiable.
As both companies prepare to report earnings this week, investors should pay close attention to any additional commentary surrounding memory availability, pricing, and infrastructure spending.
