Micron, Qualcomm Show Strong AI Demand

2026-06-25 · Source: Bloomberg Tech · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Emerging Technologies & Innovation, Cloud Computing & IT Infrastructure · Depth: Intermediate, extended

Summary

Micron Technology issued a super bullish sales outlook, forecasting up to \$51 billion in fourth-quarter revenue, significantly exceeding Wall Street's \$43 billion estimates. The company anticipates AI-driven memory shortages will persist beyond 2027, sustaining high memory prices despite increased manufacturing capacity. In response, Apple is raising prices on various hardware, including iPads, Macs, and Vision Pro, citing the ongoing memory and storage crunch. Concurrently, Qualcomm projects over \$15 billion in annual AI data center revenue by fiscal 2029 and \$40 billion in non-smartphone sales by 2027, driven by custom ASICs and a new HBM-free memory solution for disaggregated AI compute. Separately, global AI revenue, excluding China, hit \$25 billion in Q1 2026, surpassing depreciation from infrastructure investments, with an annualized run rate of \$170 billion. Figma also launched an "intelligent canvas" platform overhaul, integrating code layers and AI agents for full-stack digital creation.

Key takeaway

For investors evaluating semiconductor and hardware portfolios, recognize that sustained AI demand is driving structural shifts, including prolonged memory shortages and rising component costs. You should factor in the potential for continued hardware price increases and the rapid, yet volatile, growth of AI revenue. Monitor public sentiment and emerging anti-AI policies, as these could introduce regulatory risks impacting future market performance and investment returns.

Key insights

Surging AI demand is reshaping semiconductor markets, driving memory price hikes and strategic tech diversification.

Principles

• AI demand creates sustained memory shortages.
• Power efficiency differentiates AI hardware.
• Diversifying into AI data centers is crucial.

In practice

• Sign longer-term memory contracts to secure supply.
• Prioritize power-efficient AI hardware designs.
• Integrate AI agents and code layers in design platforms.

Topics

• AI Demand
• Semiconductor Market
• Memory Pricing
• Data Center Infrastructure
• AI Hardware
• Tech Policy Risk

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Editorial summary, takeaway, and curation by AIssential. Original article published by Bloomberg Tech.