AI-Powered Storage Market Forecast 2024-2033: Growth Rate, Drivers, And Trends

The AI-Powered Storage Global Market Report 2024 by The Business Research Company provides market overview across 60+ geographies in the seven regions – Asia-Pacific, Western Europe, Eastern Europe, North America, South America, the Middle East, and Africa, encompassing 27 major global industries. The report presents a comprehensive analysis over a ten-year historic period (2010-2021) and extends its insights into a ten-year forecast period (2023-2033).

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According to The Business Research Company’s AI-Powered Storage Global Market Report 2024, The ai-powered storage market size has grown exponentially in recent years. It will grow from $25.99 billion in 2023 to $32.52 billion in 2024 at a compound annual growth rate (CAGR) of 25.1%. The growth in the historic period can be attributed to rise of cloud computing, increasing complexity of data, data security concerns, demand for real-time analytics, growing iot ecosystem.

The ai-powered storage market size is expected to see exponential growth in the next few years. It will grow to $80.36 billion in 2028 at a compound annual growth rate (CAGR) of 25.4%. The growth in the forecast period can be attributed to data-driven decision-making, increasing data privacy regulations, autonomous storage management, quantum computing impact, continuous learning storage systems. Major trends in the forecast period include technological advancements in neural networks, ai in data lifecycle management, ai for predictive storage maintenance, ai-optimized storage hardware, ai-powered disaster recovery, green ai storage solutions.

Growing numbers of data centers are expected to propel the growth of the AI-powered storage market going forward. Data centers refer to facilities that offer shared access to applications and data through a sophisticated network, computing, and storage infrastructure. AI-powered storage analyses vast amounts of real-time data in data centers using machine learning algorithms and predictive analytics that allows data center operators to identify patterns and make informed decisions to optimize resource allocation, capacity planning, and workload management. For instance, in February 2021, according to the Korea Data Center Council (KDCC), the overall capacity of colocation data centers information technology (IT) load reached 430MW at the end of 2020, accounting for 11% of the total APAC IT load. Following Savills Korea projections, the total commercial data center IT load in Korea is expected to expand by 700MW between 2021 and 2023, accounting for 15% of overall Asia-Pacific capacity. Therefore, growing numbers of data centers are driving the growth of the AI-powered storage market.

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The ai-powered storage market covered in this report is segmented –

1) By Offering: Software, Hardware

2) By Storage System: Direct-attached Storage, Network-attached Storage, Storage Area Network

3) By Storage Medium: Hard Disk Drive (HDD), Solid State Drive (SSD)

4) By Storage Architecture: File and Object-Based Storage, Block Storage

5) By End-User: Enterprises, Government Bodies, Cloud Service Providers, Telecom Companies, Other End-users

Product innovation is a key trend gaining popularity in the AI-powered storage market. Major companies operating in the AI-powered storage market are working on product innovations to sustain their position in the market. For instance, in October 2023, Huawei Technologies Co. Ltd., a China-based multinational technology corporation, launched the OceanStor A310, a new AI storage model designed for the era of large AI models. In order to release new AI capabilities, the system offers the optimal storage capacity for training industry models, basic model training, and inference in segmented scenario models. OceanStor A310 is a deep learning data lake storage solution with unlimited horizontal scalability and high performance for mixed workloads in the context of industry large model scenarios and basic models. It makes it possible to manage huge data storage for AI processes, such as data collection, pre-processing, training, and inference, end-to-end. It can analyze data from similar sources and has data analysis skills that are compatible with big data and HPC (high-performance computing).

The ai-powered storage market report table of contents includes: