Key takeaways
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- Micron’s revenue nearly tripled to $23.86 billion, driven by tight memory supply and surging AI demand.
- DRAM and NAND pricing rose far more than expected, sharply boosting margins.
- Micron says memory shortages will remain tight beyond 2026, signaling a longer AI infrastructure constraint.
- The company is ramping capex aggressively, treating memory as a strategic asset in the AI era.
What Happened?
Micron reported a massive earnings beat, with second-quarter revenue rising to $23.86 billion from $8.05 billion a year earlier. Profit and margins also surged as AI demand for memory continued to overwhelm available supply.
The company said prices for DRAM rose in the mid-60% range and NAND prices rose in the high-70% range, both well above earlier expectations. Gross margin doubled year over year to 75%, showing just how much pricing power memory suppliers now have.
Micron also raised its capex outlook, saying it expects to spend more than $25 billion this year and significantly more on clean-room capacity in fiscal 2027.
Why It Matters
This matters because the AI trade is no longer just about GPUs. Memory has become a core bottleneck.
As models and agents grow more complex, they need far more high-performance memory to store, retrieve, and process data efficiently. That means DRAM and NAND are no longer secondary semiconductor categories — they are now critical enablers of AI infrastructure.
For investors, Micron’s results confirm two things. First, AI demand is still cascading through the supply chain with real pricing power. Second, this cycle may last longer than many expected, because supply is not catching up quickly. If memory stays constrained through 2026 and beyond, companies exposed to this layer of the stack could keep seeing outsized earnings leverage.
What’s Next?
The next key issue is whether Micron and peers can add capacity fast enough without overshooting. Investors should watch continued pricing trends in DRAM and NAND, updates to industry supply timelines, and whether hyperscalers and AI infrastructure buyers begin locking in memory supply more aggressively.
The broader takeaway is that in the AI era, compute alone is not enough. Memory is becoming one of the most strategic — and scarce — assets in the entire semiconductor ecosystem.
