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Saudi Arabia AI Memory Chip Market Size and Forecast by Memory Types, Packaging Architectures, and End User: 2019-2033

  Dec 2025   | Format: PDF DataSheet |   Pages: 110+ | Type: Niche Industry Report |    Authors: Surender Khera (Asst. Manager)  

 

Saudi Arabia AI Memory Chip Market Outlook

  • As per our findings, the Saudi Arabia market revenue stood at USD 87.5 million in 2024.
  • Market projections show the Saudi Arabia AI Memory Chip Market is forecast to reach USD 1.04 billion by 2033, achieving a CAGR of 30.3% during the projection horizon.
  • DataCube Research Report (Dec 2025): This analysis uses 2024 as the actual year, 2025 as the estimated year, and calculates CAGR for the 2025-2033 period.

Industry Assessment Overview

Industry Findings: National industrial strategy and large cloud-region commitments altered procurement risk models and memory sourcing preferences. A clear policy and capacity inflection occurred in Mar-2024 when major cloud providers publicly announced plans to establish onshore cloud regions, prompting government agencies and large enterprises to require localised data-handling and lower-latency compute. Procurement teams shifted toward memory architectures that prioritise on-node capacity, verified endurance for persistent tiers, and clear qualification pathways to meet sovereignty and performance requirements for AI deployments.

Industry Player Insights: Companies shaping sector outcomes in UAE include Samsung Electronics, Micron Technology, SK hynix, and Kioxia etc. Amazon Web Services declared plans to open a Saudi cloud region in Mar-2024 and to invest in local data-centre capacity, accelerating demand for high-bandwidth HBM and enterprise SSD sampling among local integrators. Separately, Saudi government agencies and national AI authorities continued to refine national data-and-AI strategy guidance through 2024–2025 to accelerate domestic compute projects, which in turn prompted vendors to offer targeted validation programmes for memory and storage stacks. Those vendor developments compressed qualification timelines and expanded the set of locally available, validated memory options.
*Research Methodology: This report is based on DataCube’s proprietary 3-stage forecasting model, combining primary research, secondary data triangulation, and expert validation. [Learn more]

Market Scope Framework

Memory Types

  • Compute-in-Memory (CiM)
  • Near-Memory / On-Package DRAM
  • In-Memory Processing SRAM Blocks

Packaging Architectures

  • 2.5D Co-Packaged AI Memory
  • 3D-Stacked AI Memory
  • AI-Focused Fan-Out Memory Tiles

End User

  • Hyperscalers & Cloud Providers
  • OEMs / System Integrators
  • Accelerator / ASIC Vendors
  • Enterprises / Research Institutions
  • Edge Device Makers
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