智通财经网·2026-03-30 02:05Core Viewpoint - The report from CITIC Securities indicates that the Agent AI era is driving a paradigm shift in the storage industry, with supply and demand dynamics leading to a long-term shortage expected to last until 2027, alongside price increases throughout 2026 [1][2][3]. Supply and Demand Dynamics - AI inference is causing a surge in storage demand, with server shipments expected to increase by 15% year-on-year in 2026, and AI servers projected to account for over 20% of total server shipments [2]. - The demand for KV Cache is expected to explode, with its usage increasing from 0.5GB to 64GB as sequence lengths rise from 1k to 128k tokens, leading to a linear increase in storage demand [2]. - Supply constraints are exacerbated by manufacturers prioritizing high-margin AI storage products, with advanced DRAM capacity expected to rise from under 50% in 2024 to over 85% by 2026 [3]. Market Trends and Innovations - The 2026 China Flash Memory Summit will focus on storage innovations and opportunities in the AI era, featuring participation from major global companies [1]. - The storage industry is undergoing a value reconstruction, with a shift from cost competition to securing product availability, as highlighted by the "Token Factory Economics" presented by NVIDIA [4]. - The emergence of high-capacity QLC products is becoming critical, with companies like Kioxia and SanDisk showcasing solutions exceeding 200TB, optimizing space efficiency and total cost of ownership (TCO) [6]. Technological Advancements - The role of eSSD is evolving from a passive data container to a core computing engine, significantly enhancing GPU efficiency during training and inference phases [5]. - Innovations in interface technology, such as the introduction of PCIe 6.0 SSDs, are set to dramatically improve input/output performance, addressing the challenges posed by large-scale GPU clusters [6]. - The trend towards "storage-compute integration" is crucial for overcoming memory bottlenecks in edge computing and AI applications, with advancements in hybrid technologies reducing DRAM requirements significantly [7][8].