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Thailand 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)  

 

Thailand AI Memory Chip Market Outlook

  • In 2024, the sector in Thailand was valued at USD 105.3 million.
  • The Thailand AI Memory Chip Market is expected to expand to USD 861.5 million by 2033, recording a CAGR of 26.3% over the forecast window.
  • 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: Regional data infrastructure planning and national digital roadmaps changed how buyers specify memory for AI systems. A high-profile non-vendor milestone was the publication of a Digital Data Infrastructure Roadmap in Jun-2025 that clarifies data-sharing corridors, testbed access, and incentives for local compute capacity. That guidance led enterprises and public agencies to favour memory architectures that simplify cross-site validation and permit staged dataset caching close to edge compute nodes. As a result, procurement teams prioritise memory modules with clear qualification paths and manageable thermal envelopes to support rapid rollouts across manufacturing and logistics clusters.

Industry Player Insights: Players operating in the Thailand industry are Samsung Electronics, Western Digital, Seagate Technology, and Micron Technology etc. Western Digital secured Board of Investment approval for a THB23.5 billion expansion in Aug-2024 to scale HDD manufacturing and adjacent assembly capabilities, which tightened local availability of persistent storage options for AI dataset staging. Separately, Seagate documented ongoing regional manufacturing and sustainability investments across Thailand in 2024–2025 that improved local supply resilience for storage and hybrid memory+storage stacks. These vendor moves lowered procurement risk and gave Thai cloud and telco operators more reliable options for hybrid memory architectures.
*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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