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The Impact of the Storage Shortage on AI Data Center Build-Out

Price: Starting at USD 1,950
Publish Date: 10 Jun 2026
Code: PT-6045
Research Type: Presentation
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Actionable Benefits

Actionable Benefits

  • Prioritize storage procurement, supplier diversification, and inventory strategies to reduce Artificial Intelligence (AI) infrastructure deployment risk.
  • Identify where shortages in High-Bandwidth Memory (HBM), Dynamic Random-Access Memory (DRAM), NAND, and packaging are delaying commissioning, reducing Graphics Processing Unit (GPU) utilization, and increasing costs.
  • Support infrastructure planning and sourcing decisions with scenario-based insight into storage-driven risks across the AI data center ecosystem.
  • Benchmark mitigation strategies across architecture, procurement, and operations to improve resilience.
Research Highlights

Research Highlights

  • Analysis of how shortages in HBM, DRAM, NAND, and advanced packaging are constraining AI data center build-out.
  • Scenario-based outlook covering optimistic, neutral, and pessimistic market developments.
  • Assessment of key bottlenecks, including commissioning delays, GPU underutilization, checkpointing risks, and rising workaround costs.
  • Stakeholder-level analysis of deployment, utilization, commercial, and competitive impacts.
  • Practical mitigation strategies across architecture, procurement, and supply security.
Critical Questions Answered

Critical Questions Answered

  • Why has storage become a key constraint on AI data center build-out?
  • How do storage shortages affect deployment timelines, utilization, and economics across the AI infrastructure stack?
  • Which stakeholders are most exposed, and how do impacts differ across hyperscalers, emerging cloud providers, colocation providers, and server Original Equipment Manufacturers (OEMs)?
  • What is the most likely outlook for the storage shortage in 2026 and through 2027?
  • Which mitigation strategies can operators use to reduce storage-related risk?
Who Should Read This?

Who Should Read This?

  • Chief Technology Officers (CTOs), infrastructure leaders, and data center strategists at hyperscalers and AI cloud providers: to assess how storage shortages affect AI deployment, utilization, and Service-Level Agreements (SLAs).
  • Supply chain, procurement, and operations executives at cloud providers, OEMs, and AI infrastructure operators: to prioritize sourcing, qualification, and inventory strategies.
  • Executives at colocation providers and digital infrastructure firms: to understand how storage constraints are reshaping AI campus competitiveness.
  • Investors, Mergers and Acquisitions (M&A) teams, and industry analysts: to evaluate competitive positioning, margin risk, and long-term resilience across the AI infrastructure market.

Table of Contents

Key Takeaways

Key Forecasts

Nature of the Storage Shortage

Key Bottlenecks Created by the Storage Shortage

Impact Across the AI Data Center Stack

Impact by Stakeholder

Outlook on the AI Data Center Build-Out: Scenario-Based Approach 

Neutral Scenario: Impact by Stakeholder 

Mitigation Strategies & Risks