Global Leading Market Research Publisher QYResearch announces the release of its latest report "AI SSD - Global Market Share and Ranking, Overall Sales and Demand Forecast 2026-2032". Based on current situation and impact historical analysis (2021-2025) and forecast calculations (2026-2032), this report provides a comprehensive analysis of the global AI SSD market, including market size, share, demand, industry development status, and forecasts for the next few years.

For data center architects, edge computing engineers, and AI infrastructure developers, reducing the overhead of data transmission to CPU/GPU for inference, data preprocessing, compression, and encryption tasks is critical for lowering latency and energy consumption. The global AI SSD market addresses this need through new solid-state drives that combine high-speed storage with AI acceleration technology. These drives integrate dedicated AI chips (NPUs, ASICs, FPGAs) on top of traditional NVMe/PCIe SSDs, performing compute tasks locally to reduce CPU/GPU load.

The global market for AI SSD was estimated to be worth US$ 577 million in 2025 and is projected to reach US$ 1135 million, growing at a CAGR of 10.3% from 2026 to 2032. In 2024, global production reached 264k units, with an average selling price of US$ 2,100 per unit. This robust growth reflects increasing demand for compute-accelerated storage in AI workloads.

【Get a free sample PDF of this report (Including Full TOC, List of Tables & Figures, Chart)】
https://www.qyresearch.com/reports/6097705/ai-ssd

Compute-Accelerated Storage for AI Workloads
AI SSDs are new solid-state drives that combine high-speed storage with AI acceleration technology. They typically integrate dedicated AI chips (such as NPUs/ASICs/FPGAs) on top of traditional NVMe/PCIe SSDs. They can perform tasks such as inference, data preprocessing, compression acceleration, encryption and decryption locally, thereby reducing the overhead of data transmission to the CPU/GPU, lowering latency and energy consumption, and improving the overall AI performance of edge devices or servers.

Key capabilities include in-situ inference on stored data, data filtering and preprocessing before host transfer, compression/decompression acceleration, and encryption/decryption offload. Benefits include reduced data movement (saving bandwidth and power), lower latency for real-time applications, and reduced CPU/GPU load for other tasks.

Industry Segmentation: Interface Speeds & Applications
The AI SSD market is segmented by PCIe generation and end-use application:

PCIe 4.0: Current generation, up to 16 GT/s per lane. A data center operator reported that PCIe 4.0 AI SSDs reduced inference latency by 40%.

PCIe 5.0: Next generation, up to 32 GT/s per lane. Enables higher bandwidth for demanding AI workloads.

Application Segments
Data Centers: AI training data preprocessing, recommendation systems, database acceleration. A cloud provider uses AI SSDs for real-time recommendation inference.

Autonomous Driving: In-vehicle data preprocessing, sensor fusion acceleration. An autonomous vehicle developer reported that AI SSDs reduced sensor data processing time by 60%.

Industrial IoT: Edge inference for predictive maintenance, quality inspection.

Edge Computing: Local AI processing on edge servers and gateways.

Others: Smart cameras, robotics, and healthcare imaging.

Technology Developments & Supply Chain
AI SSDs are primarily based on NAND Flash chips, manufactured by companies such as Samsung, Kioxia, Micron, SK Hynix, and Western Digital. They are also used in data centers by companies such as Google, Intel, IBM, and Huawei.

Over the past six months, advancements include higher-capacity AI SSDs (up to 8TB). More powerful integrated NPUs (up to 10 TOPS) for local inference. Lower power consumption for edge deployment. Software development kits (SDKs) for easy integration with AI frameworks.

Regional Market Dynamics
North America leads the AI SSD market, driven by hyperscale data center adoption, autonomous vehicle development, and edge computing investment. Asia-Pacific follows, with strong semiconductor manufacturing in South Korea, Japan, and China, and AI infrastructure growth. Europe has steady demand from industrial IoT and automotive sectors.

Competitive Landscape
Key players include Samsung, SK Hynix, Kioxia, Micron Technology, NVIDIA, Gigabyte Technology, Seagate Technology, Western Digital, Kingston, Huawei, Phison Electronics, OSCOO, and Yangtze Memory Technology.

Market Segmentation
The AI SSD market is segmented as below:

By Company

Samsung

SK Hynix

Kioxia

Micron Technology

NVIDIA

Gigabyte Technology

Seagate Technology

Western Digital

Kingston

Huawei

Phison Electronics

OSCOO

Yangtze Memory Technology

Segment by Interface

PCIe 4.0

PCIe 5.0

Segment by Application

Data Centers

Autonomous Driving

Industrial IoT

Edge Computing

Others

Exclusive Industry Outlook
Looking ahead, the convergence of AI SSD technology with higher PCIe speeds (Gen5/Gen6), more powerful integrated NPUs, and edge AI expansion represents a significant growth opportunity. Development of AI SSDs with computational storage for large language model (LLM) inference. Integration with CXL (Compute Express Link) for memory pooling. Additionally, the expansion of autonomous driving and industrial IoT will drive demand for real-time, low-latency AI storage. The ability to offer AI SSDs that combine high bandwidth, local compute capability, and software support—backed by NAND supply and AI framework integration—will define competitive differentiation.

Contact Us:
If you have any queries regarding this report or if you would like further information, please contact us:
QY Research Inc.
Add: 17890 Castleton Street Suite 369 City of Industry CA 91748 United States
EN: https://www.qyresearch.com
E-mail: global@qyresearch.com
Tel: 001-626-842-1666(US)
JP: https://www.qyresearch.co.jp