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Micron, SK Hynix, and Sandisk Poised to Lead $100B AI Memory Supercycle, Analysts Say

Micron, SK Hynix, and Sandisk are set to dominate a $100 billion AI memory market by 2028, with Micron’s stock soaring 240% in a rapidly evolving landscape.

The AI industry is undergoing a significant shift, with the focus moving from the chips that process data to the hardware necessary for storage. Analyst Gil Luria from DA Davidson highlighted this transition during an interview with Yahoo Finance, stating, “Right now, we are very early in the memory cycle. The progress that we’ve made in AI models has made it so memory is the next frontier.” This demand for enhanced memory capabilities is evident across chips, installations, servers, and data centers.

Companies like Micron, SK Hynix, and the memory division of Samsung are increasingly becoming essential players in this evolving landscape. Micron, in particular, has seen its stock rise approximately 240% over the past year, although its valuation remains strikingly low, trading at just 9.9 times forward earnings. This is a notable discount compared to the S&P 500 and Nvidia, which are trading at 22 times and 25 times, respectively.

As the memory supercycle gains momentum, analysts have pinpointed key stocks for investors to watch. Micron has transformed from a cyclical laggard into a crucial component of the AI server ecosystem, with its high-bandwidth memory (HBM) products taking center stage. The company has projected that the total addressable market for HBM could reach $100 billion by 2028, reflecting a remarkable compounded annual growth rate of 40%.

Wedbush analyst Dan Ives likened Micron’s current pricing to “getting a Mickey Mantle signed card at a garage sale.” The complexity of HBM production allows Micron to command higher margins and pricing power, as much of its capacity is now allocated to HBM rather than traditional products like smartphones and flash storage.

While Micron has emerged as a domestic leader, many on Wall Street view South Korea’s SK Hynix as the epicenter of the memory boom. Currently, SK Hynix is the principal supplier of HBM to Nvidia, holding approximately 60% market share as of late 2025. However, this dominance may also pose risks; Luria noted that SK Hynix faces severe capacity constraints. If the company is unable to meet the surging demand for HBM4—the next generation of AI memory—it risks ceding ground to competitors in 2026. Nevertheless, UBS forecasts that SK Hynix’s HBM4 market share could increase to 70% by 2026, bolstered by its integral role in Nvidia’s upcoming Rubin platform.

Another noteworthy player in this memory landscape is Sandisk, which has seen its shares soar over 800% since its spin-off from Western Digital. While discussions around AI typically emphasize DRAM, or short-term memory, Sandisk specializes in NAND flash, a critical solution for long-term storage. This technology is essential for “AI at the edge,” where devices like robots and autonomous vehicles require local data processing and storage capabilities.

Despite the excitement surrounding the memory sector, Luria cautioned that memory remains a commodity. Unlike Nvidia’s proprietary software ecosystem, memory chips tend to be interchangeable, which could undermine pricing power once supply constraints loosen. Luria remarked, “Nvidia can decide to order more from SK Hynix one year and more from Micron the next year,” indicating a potential lack of sustainability in this model.

Currently, the market appears to be prioritizing short-term supply issues over long-term commodity risks. As Luria noted, “From a trading perspective, from a shorter-term investment perspective, that doesn’t matter when you’re in a bottleneck.” The memory sector is poised for continued growth, but investors will need to remain vigilant about the underlying dynamics that could affect profitability as the landscape evolves.

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Marcus Chen
Written By

At AIPressa, my work focuses on analyzing how artificial intelligence is redefining business strategies and traditional business models. I've covered everything from AI adoption in Fortune 500 companies to disruptive startups that are changing the rules of the game. My approach: understanding the real impact of AI on profitability, operational efficiency, and competitive advantage, beyond corporate hype. When I'm not writing about digital transformation, I'm probably analyzing financial reports or studying AI implementation cases that truly moved the needle in business.

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