Micron's AI-Fueled Forecast: What Sales Teams Should Do Now
Micron just signaled a demand wave that hasn't peaked yet. The company forecast fiscal Q2 revenue of US$18.3B to US$19.1B, well above the US$14.4B analysts expected. Excluding some items, profit is projected at US$8.22 to US$8.62 per share versus a US$4.71 estimate.
Investors took note. The stock jumped about 10% in pre-market trading after the outlook and is up 168% this year, closing at US$225.52 on Wednesday. That kind of move is a signal: pricing power and scarcity are back in memory.
Demand for AI infrastructure is outrunning supply, and Micron is benefitting. The company called itself an "essential AI enabler," with memory and storage as the bottleneck for training and inference systems. High-bandwidth memory is already sold out for next year, according to leadership.
There's spillover too. Even mainstream PC memory is tight because manufacturers shifted capacity to AI-grade parts. One executive called this the most significant demand-supply disconnect in 25 years-by both size and duration.
The company's last quarter backs it up: sales rose 57% to US$13.6B, with profit (ex-items) at US$4.78 per share. Analysts had expected US$13B and US$3.95 respectively.
Shortages aren't going away soon. Management expects tight conditions to persist beyond 2026. They're only meeting about 50% to two-thirds of demand from several key customers and plan to spend US$20B on capex this fiscal year (up from a prior US$18B forecast; last year was US$13.8B).
Why this matters for sales
- Scarcity sells: Limited supply creates urgency. Use credible lead-time data and delivery windows to move deals forward.
- Pricing power returns: When demand outruns supply, value-based pricing lands. Anchor on outcomes (throughput, training time saved, energy efficiency), not parts and SKUs.
- Multi-year planning: Buyers building AI stacks need multi-quarter commitments. Push capacity reservations and longer terms to lock priority allocation.
- CFO-ready ROI: AI budgets are big and scrutinized. Tie your solution to revenue drivers-faster model cycles, lower run costs, higher utilization-backed by numbers.
Customer conversation starters
- Lead times and allocation: "What's your AI capacity plan for the next 12-24 months, and which workloads will face risk if memory stays tight?"
- Capacity reservations: "Would guaranteed delivery slots justify a deposit or multi-year agreement to de-risk your roadmap?"
- Workload prioritization: "Which models or apps need HBM-level performance, and what can shift to standard DRAM without delaying outcomes?"
- TCO clarity: "If we cut training time by X% or raise utilization by Y%, what's the revenue impact this quarter?"
Pipeline moves you can make this week
- Re-score accounts by AI intensity (data center buildouts, LLM initiatives, inference at scale). Prioritize those with clear model roadmaps.
- Bundle for outcomes: Offer configurations that reduce time-to-deploy and guarantee performance SLAs, not just parts lists.
- Offer phased ramps: Stage deliveries tied to milestones. It reduces risk for buyers and secures your book of business.
- Co-sell with partners: Align with GPU vendors, integrators, and cloud credits to remove purchasing friction.
- Use credible scarcity: Share realistic delivery dates and allocation constraints. False urgency kills trust-real constraints close deals.
Key numbers to keep in your back pocket
- Q2 revenue outlook: US$18.3B-US$19.1B (vs. US$14.4B consensus)
- EPS (ex-items): US$8.22-US$8.62 (vs. US$4.71 estimate)
- HBM: Sold out for next year
- Shortages: Likely beyond 2026
- Capex: US$20B this year (prior US$18B; last year US$13.8B)
Helpful links
For official updates and financials, check Micron Investor Relations.
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