Australia 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)  

 

Australia AI Memory Chip Market Outlook

  • In 2024, the sector in Australia reached a value of USD 272.4 million.
  • Our market projections estimate the Australia AI Memory Chip Market size is expected to achieve USD 2.15 billion by 2033, supported by a CAGR of 25.5% for the forecast period.
  • 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: Public infrastructure and national AI planning are reorienting memory procurement toward shorter data-paths and larger on-node capacities to serve domestic and regional workloads. A concrete non-vendor milestone occurred when the federal government published its National AI Plan in Dec-2025 to accelerate domestic AI capability and infrastructure investment, which increased focus on local data-centre build-out and governance-ready architectures. That policy direction pushed enterprises to favour memory and storage configurations that support sovereign data-handling, reduce cross-border latency, and lower the total cost of ownership for AI services deployed within Australia.

Industry Player Insights: Australia’s structural shifts are influenced by Western Digital, Micron Technology, Samsung Electronics, and SK hynix etc. Western Digital updated corporate structuring and strategic plans in Mar-2024, which affected product roadmaps for enterprise flash and influenced procurement discussions among Australian cloud and telco operators. Separately, Micron’s ramp of HBM3E volume production in Feb-2024 increased the global supply of ultra-high-bandwidth parts, giving Australian HPC integrators improved options when specifying memory-dense training racks shipped into the region. These vendor developments strengthened local procurement choices and reduced lead-time uncertainty for memory-intensive AI projects.

*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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