Soaring Memory Costs Reshape AI Chips and Cloud Spending
The rapid buildout of generative AI infrastructure has turned high-bandwidth memory, or HBM, and DRAM into major cost drivers for cloud service providers. Rising memory prices are lifting the cost of AI accelerators and servers while forcing operators to reconsider how computing capacity, memory and power are balanced. The shift matters because memory supply and pricing increasingly determine data-center investment returns and the competitiveness of AI hardware.
TrendForce expects memory to account for 68% of capital expenditure at major global cloud service providers by 2027 as they accelerate AI infrastructure deployments. The research firm said persistently rising HBM and DRAM contract prices are feeding into higher AI chip prices. Those costs are also prompting operators to redesign AI system memory architectures and step up development of custom AI ASICs to improve efficiency and curb infrastructure expenses.
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The history behind this eventCapital Spending by Eight Global CSPs to Top $710 Billion in 2026, Accelerating AI and ASIC Expansion
Cloud service providers (CSPs) are expanding data centers to support demand for generative AI and cloud computing. TrendForce said providers are purchasing GPUs from NVIDIA and AMD while accelerating adoption of custom ASICs such as Google’s TPUs to reduce computing costs and energy consumption. Capital spending has therefore become a key gauge of the AI infrastructure cycle.
TrendForce had initially forecast that combined capital spending by the world’s eight largest CSPs would exceed $710 billion in 2026, with Google’s TPUs leading the ASIC expansion. After adding more North American providers to its latest survey, it raised its 2026 capital-spending forecast for the world’s nine largest CSPs to $830 billion, more than $120 billion above its previous estimate, reflecting continued growth in AI data center investment.
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