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市場調查報告書
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1725056

2032 年人工智慧儲存市場預測：按產品、解決方案類型、儲存系統、儲存架構、部署模型、儲存媒體、最終用戶和地區進行的全球分析

AI Powered Storage Market Forecasts to 2032 - Global Analysis By Offering, Solution Type, Storage System, Storage Architecture, Deployment Model, Storage Medium, End User and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 200+ Pages | 商品交期: 2-3個工作天內

價格

根據 Stratistics MRC 的預測，全球人工智慧儲存市場規模預計在 2025 年達到 347.1 億美元，到 2032 年將達到 1,495.1 億美元，預測期內的複合年成長率為 23.2%。使用人工智慧來改善管理、效能和效率的系統稱為人工智慧儲存。這些智慧型系統使用機器學習演算法和預測分析來自動化產能預測、異常檢測、資料分層和效能調整等流程。支援人工智慧 (AI) 的儲存不斷評估使用趨勢和應用需求，以提高資料安全性、減少延遲並動態分配資源。這意味著一種響應更快、更經濟的儲存解決方案，特別是對於處理大量非結構化資料的企業而言。此外，隨著數位轉型的加速，人工智慧儲存對於尋求有效擴展並做出更明智的數據主導決策的企業來說變得至關重要。

根據國際數據公司 (IDC) 的數據，受人工智慧、物聯網和邊緣運算日益普及的推動，全球數據領域預計到 2025 年將成長到 175 Zetta位元組。這種成長需要先進的儲存解決方案，包括人工智慧存儲，以有效地管理和分析數據。

對高速資料存取的需求

快速資料存取對於人工智慧和機器學習應用中的高頻分析、即時推理和模型訓練至關重要。由於 IOPS（每秒輸入/輸出操作）有限且延遲問題，傳統儲存基礎設施可能會成為瓶頸。人工智慧儲存解決方案利用 NVMe、全快閃陣列和智慧快取演算法等技術，實現超低延遲和高吞吐量。此外，它還確保數據順利傳輸到AI引擎，從而顯著加快工作負載的執行速度，並提高金融建模、醫療診斷和無人駕駛汽車等行業的整體應用效能。

營運和實施成本高

人工智慧儲存系統需要在專門的軟體、硬體和訓練有素的人員方面進行大量的前期投資。儘管效能很高，但儲存層級記憶體、NVMe 和全快閃陣列等技術比傳統的基於 HDD 的系統更昂貴。將AI演算法整合到儲存工作流程中需要GPU、高效能CPU等先進的運算資源，進一步增加了成本。這些成本對於許多小型企業來說過高，限制了其採用。此外，由於需要頻繁更新、模型訓練和維護以確保儲存系統以最佳狀態運行，因此營運成本也會上升。

企業對智慧數據管理的需求日益成長

隨著各行各業數位轉型不斷加速，企業正以前所未有的規模產生和收集數據。人們對不僅能儲存數據，還能幫助管理、分析和提取數據見解的系統的需求日益成長。人工智慧儲存提供智慧分層、預測分析、自動資料分類和自我修復機制等功能，以提高業務連續性並實現更智慧的決策。此外，隨著越來越多的企業意識到資料的戰略價值，對能夠最佳化資料效用的智慧儲存解決方案的需求將不斷增加。

技術快速淘汰

人工智慧和儲存技術的快速進步可能很快就會使現有的解決方案過時。目前由人工智慧驅動的儲存系統可能很快就會被新的架構、儲存通訊協定或人工智慧硬體（如量子運算和神經型態晶片）的進步所取代。此外，如果更新、更有效的替代方案迅速出現，那麼在當今解決方案上投入大量資金的公司就有可能落後。這種不斷變化的環境導致潛在採用者產生猶豫，尤其是那些關心系統壽命和長期投資回報率的人。

COVID-19的影響：

COVID-19 疫情對人工智慧儲存市場產生了多種影響。一方面，由於供應鏈中斷和 IT 投資推遲，早期疫情發展和硬體可用性暫時放緩。但這場危機也加速了許多行業的數位轉型，企業迅速轉向雲端服務、人工智慧主導的分析和遠端操作，以處理不斷成長的數據量並確保業務永續營運連續性。此外，不斷成長的資料量凸顯了對能夠支援人工智慧工作負載的高度擴充性、智慧儲存系統的需求。因此，人工智慧儲存解決方案正受到越來越多的關注和資金籌措，尤其是來自醫療保健、電子商務和金融等行業。

預計人工智慧整合軟體領域將成為預測期內最大的市場

預計預測期內，AI整合軟體部分將佔據最大的市場佔有率。該領域的目標是透過將人工智慧融入儲存系統來提高資料管理和營運效率。透過實現智慧數據搜尋、即時分析、預測性維護和自動數據分類，人工智慧整合可以提高儲存效率並降低營運費用。此外，它還能實現儲存系統與其他業務應用程式的平滑整合，從而實現更智慧、靈活的基礎架構。對人工智慧增強技術的需求不斷成長，以及對更智慧、更有效率的儲存系統的需求正在推動各行各業這一領域的成長。

預計在預測期內，儲存區域網路(SAN) 部分將以最高的複合年成長率成長。

預計儲存區域網路（SAN）部分將在預測期內實現最高的成長率。 SAN 系統提供高速、低延遲的資料訪問，使其非常適合災難復原和巨量資料分析等企業級應用。它的靈活性和擴充性使企業能夠增加儲存容量，而不會中斷正在進行的業務。由於其強大的效能和改進的資料安全性，SAN 解決方案在醫療保健和 BFSI 等領域尤其受到青睞。此外，SAN 在人工智慧儲存市場的快速崛起是其廣泛使用的結果，反映了其管理繁重工作負載和複雜資料環境的能力。

比最大的地區

預計預測期內歐洲地區將佔據最大的市場佔有率。隨著製造業、醫療保健和金融等各個領域的人工智慧技術應用日益廣泛，該地區正在經歷快速擴張。法國、德國和英國等國家正在透過投資雲端基礎的儲存和人工智慧基礎設施樹立標準。此外，歐盟 (EU) 對數位轉型的重視以及《一般資料保護規範 (GDPR)》等法律體制的建立也增加了對安全有效的人工智慧儲存解決方案的需求。此外，歐洲在人工智慧儲存市場的佔有率受到數據分析日益成長的需求以及雲端運算和人工智慧的發展的推動。

複合年成長率最高的地區：

預計亞太地區在預測期內的複合年成長率最高。機器人技術在許多行業的廣泛應用、對雲端基礎的服務的需求不斷成長以及對即時數據處理的要求不斷增加是這種快速擴張的主要因素。而且，此次擴張的重點國家是中國、日本和印度。印度尤其在人工智慧基礎設施方面投入了大量資金，亞馬遜和微軟等科技巨頭在雲端服務和資料中心建設方面投資了數十億美元，使該國成為亞太地區人工智慧儲存市場的主要參與者。

提供免費客製化：

訂閱此報告的客戶可享有以下免費自訂選項之一：

  • 公司簡介
    • 全面分析其他市場參與者（最多 3 家公司）
    • 主要企業的SWOT分析（最多3家公司）
  • 地理細分
    • 根據客戶興趣對主要國家市場進行估計、預測和複合年成長率（註：基於可行性檢查）
  • 競爭基準化分析
    • 根據產品系列、地理分佈和策略聯盟對主要企業基準化分析

目錄

第1章執行摘要

第2章 前言

  • 概述
  • 相關利益者
  • 研究範圍
  • 調查方法
    • 資料探勘
    • 數據分析
    • 數據檢驗
    • 研究途徑
  • 研究材料
    • 主要研究資料
    • 次級研究資訊來源
    • 先決條件

第3章市場走勢分析

  • 驅動程式
  • 限制因素
  • 機會
  • 威脅
  • 最終用戶分析
  • 新興市場
  • COVID-19的影響

第4章 波特五力分析

  • 供應商的議價能力
  • 買家的議價能力
  • 替代品的威脅
  • 新進入者的威脅
  • 競爭對手之間的競爭

第5章 全球人工智慧儲存市場（依產品分類）

  • 硬體
  • 軟體

第6章 全球人工智慧儲存市場（按解決方案類型）

  • 人工智慧整合軟體
  • 資料保護軟體
  • 儲存管理軟體

第7章 全球人工智慧儲存市場（按儲存系統）

  • 直接連接儲存 (DAS)
  • 網路附加儲存 (NAS)
  • 儲存區域網路(SAN)

第8章 全球人工智慧儲存市場：儲存架構

  • 檔案式的存儲
  • 物件儲存
  • 區塊儲存

第9章 全球人工智慧儲存市場（按部署模式）

  • 混合雲端
  • 私有雲端
  • 公共雲端
  • 邊緣運算
  • 本地

第 10 章全球AI 儲存市場（按儲存媒體）

  • 硬碟機（HDD）
  • 固態硬碟 (SSD)

第 11 章全球AI 儲存市場（依最終用戶分類）

  • BFSI
  • 公司
  • 政府
  • 雲端服務供應商(CSP)
  • 電信業者
  • 其他最終用戶

第12章 全球人工智慧儲存市場（按地區）

  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 德國
    • 英國
    • 義大利
    • 法國
    • 西班牙
    • 其他歐洲國家
  • 亞太地區
    • 日本
    • 中國
    • 印度
    • 澳洲
    • 紐西蘭
    • 韓國
    • 其他亞太地區
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 南美洲其他地區
  • 中東和非洲
    • 沙烏地阿拉伯
    • 阿拉伯聯合大公國
    • 卡達
    • 南非
    • 其他中東和非洲地區

第13章 重大進展

  • 協議、夥伴關係、合作和合資企業
  • 收購與合併
  • 新產品發布
  • 業務擴展
  • 其他關鍵策略

第14章 公司概況

  • Alphabet（Google Inc.）
  • Dell Technologies Inc.
  • Huawei Technologies Co., Ltd.
  • Cisco Systems, Inc.
  • Intel Corporation
  • Flextronics International Ltd.
  • Toshiba Corporation
  • Lenovo Group Limited
  • Amazon Web Services
  • Hewlett Packard Enterprise Company（HPE）
  • Fujitsu Limited
  • NVIDIA Corporation
  • IBM Corporation
  • Hitachi Ltd.
  • Samsung Electronics Co. Ltd.
Product Code: SMRC29362

According to Stratistics MRC, the Global AI Powered Storage Market is accounted for $34.71 billion in 2025 and is expected to reach $149.51 billion by 2032 growing at a CAGR of 23.2% during the forecast period. Systems that use artificial intelligence to improve management, performance, and efficiency are referred to as AI-powered storage. These smart systems automate processes like capacity forecasting, anomaly detection, data tiering, and performance tuning through the use of machine learning algorithms and predictive analytics. Artificial intelligence (AI)-powered storage can improve data security, lower latency, and dynamically allocate resources by continuously evaluating usage trends and application demands. This leads to storage solutions that are more responsive and economical, particularly for businesses handling substantial amounts of unstructured data. Moreover, AI-powered storage is becoming indispensable for companies looking to scale effectively and make more informed, data-driven decisions as digital transformation picks up speed.

According to the International Data Corporation (IDC), the global datasphere is expected to grow to 175 zettabytes by 2025, driven by the increasing adoption of AI, IoT, and edge computing. This growth necessitates advanced storage solutions, including AI-powered storage, to manage and analyze data efficiently.

Market Dynamics:

Driver:

Demand for fast data access

Rapid data access is essential for high-frequency analytics, real-time inference, and model training in AI and machine learning applications. Because of limited IOPS (input/output operations per second) and latency problems, traditional storage infrastructure can lead to bottlenecks. AI-powered storage solutions provide ultra-low latency and high throughput by utilizing technologies such as NVMe, all-flash arrays, and intelligent caching algorithms. Additionally, this guarantees smooth data transfer to AI engines, greatly speeding up workload execution and enhancing overall application performance in industries like financial modeling, healthcare diagnostics, and driverless cars.

Restraint:

High operational and implementation costs

AI-powered storage systems demand a large initial outlay of funds for specialized software, hardware, and trained staff. Despite their high performance, technologies like storage-class memory, NVMe, and all-flash arrays are pricier than conventional HDD-based systems. Costs are further increased by the requirement for sophisticated computing resources like GPUs and high-performance CPUs to integrate AI algorithms into storage workflows. These costs can be prohibitive for many small and mid-sized businesses, which restricts adoption. Furthermore, the requirement for frequent updates, model training, and maintenance to guarantee the storage system operates at its best raises operational costs as well.

Opportunity:

Growing enterprise need for intelligent data management

The speed at which digital transformation is occurring across industries is causing organizations to generate and collect data at a never-before-seen scale. Demand is rising for systems that help manage, analyze, and extract insights from data in addition to storing it. AI-powered storage provides features like intelligent tiering, predictive analytics, automated data classification, and self-healing mechanisms that enhance business continuity and allow for more intelligent decision-making. Moreover, intelligent storage solutions that can optimize data utility will become more and more in demand as more businesses realize the strategic value of data.

Threat:

Quick obsolescence of technology

Existing solutions may soon become outdated due to the rapid advancements in AI and storage technologies. Current AI-powered storage systems might be swiftly surpassed by new architectures, storage protocols, or advances in AI hardware (like quantum computing or neuromorphic chips). Additionally, businesses that make significant investments in today's solutions run the risk of lagging behind if more effective, newer alternatives appear soon after. Potential adopters are hesitant because of this changing environment, particularly those who are worried about system longevity and long-term ROI.

Covid-19 Impact:

The COVID-19 pandemic affected the market for AI-powered storage in different ways. On the one hand, early pandemic deployments and hardware availability were momentarily slowed down by supply chain interruptions and postponed IT investments. But the crisis also sped up digital transformation in many industries, with businesses quickly turning to cloud services, AI-driven analytics, and remote operations to handle growing data volumes and ensure business continuity. Additionally, this increase in data production brought attention to the need for scalable, intelligent storage systems that could handle AI workloads. As a result, there is now more interest in and funding for AI-powered storage solutions, particularly in industries like healthcare, e-commerce, and finance.

The AI integration software segment is expected to be the largest during the forecast period

The AI integration software segment is expected to account for the largest market share during the forecast period. The goal of this section is to improve data management and operational efficiency by incorporating artificial intelligence into storage systems. By enabling intelligent data retrieval, real-time analytics, predictive maintenance, and automated data classification, AI integration enhances storage efficiency and lowers operating expenses. Additionally, it enables the smooth integration of storage systems with other business applications, resulting in a more intelligent and flexible infrastructure. The growing demand for AI-enhanced technologies and the need for more intelligent, efficient storage systems across industries are driving the segment's growth.

The storage area network (SAN) segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the storage area network (SAN) segment is predicted to witness the highest growth rate. SAN systems are appropriate for enterprise-grade applications like disaster recovery and big data analytics because they offer fast, low-latency data access. Because of their flexibility and scalability, companies can increase storage capacity without interfering with ongoing operations. Because of their strong performance and improved data security, SAN solutions are especially preferred by sectors like healthcare and BFSI. Furthermore, SAN's quick rise in the market for AI-powered storage is a result of its widespread use, which reflects its ability to manage demanding workloads and intricate data environments.

Region with largest share:

During the forecast period, the Europe region is expected to hold the largest market share. The region is expanding rapidly as a result of the growing use of AI technologies in a variety of sectors, including manufacturing, healthcare, and finance. With their investments in cloud-based storage and AI infrastructure, nations like France, Germany, and the UK are setting the standard. The need for safe and effective AI-powered storage solutions has also increased as a result of the European Union's emphasis on digital transformation and its legislative frameworks, such as the General Data Protection Regulation (GDPR). Moreover, Europe's share of the AI-powered storage market is being driven by the growing demand for data analytics as well as developments in cloud computing and artificial intelligence.

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR. The broad use of robotics in many industries, the growing demand for cloud-based services, and the growing requirement for real-time data processing are the main drivers of this quick expansion. Additionally, the leading nations in this expansion are China, Japan, and India. India, in particular, is seeing large investments in AI infrastructure, with tech behemoths like Amazon and Microsoft investing billions to construct cloud services and data centers, making the nation a major player in the APAC region's AI-powered storage market.

Key players in the market

Some of the key players in AI Powered Storage Market include Alphabet (Google Inc.), Dell Technologies Inc., Huawei Technologies Co., Ltd., Cisco Systems, Inc., Intel Corporation, Flextronics International Ltd., Toshiba Corporation, Lenovo Group Limited, Amazon Web Services, Hewlett Packard Enterprise Company (HPE), Fujitsu Limited, NVIDIA Corporation, IBM Corporation, Hitachi Ltd. and Samsung Electronics Co. Ltd.

Key Developments:

In March 2025, Google's parent company, Alphabet Inc., has agreed to acquire Israeli-founded cybersecurity startup Wiz for at least $32 billion, marking the largest acquisition in the tech giant's history. The deal, announced Tuesday morning, underscores Google's intensified efforts to bolster its cloud security capabilities and compete with Microsoft and Amazon in the highly competitive enterprise cloud market.

In November 2024, Cisco and MGM Resorts International announce that the companies have signed a Whole Portfolio Agreement (WPA), empowering MGM Resorts with the majority of Cisco's software portfolio. This includes cyber security, software defined networking, software defined-WAN, digital experience assurance, full-stack observability, data center and services. This agreement spans 5.5 years, benefiting guests and employees across all of MGM Resorts' properties.

In July 2023, Dell Technologies announced it has signed a definitive agreement to acquire Moogsoft, an AI-driven provider of intelligent monitoring solutions that support DevOps and ITOps. This transaction will further enhance Dell's AIOps capabilities, as part of its longstanding approach of embedding AI functionality within its product portfolio and as a critical component of its "multicloud by design" strategy.

Offerings Covered:

  • Hardware
  • Software

Solution Types Covered:

  • AI Integration Software
  • Data Protection Software
  • Storage Management Software

Storage Systems Covered:

  • Direct-attached Storage (DAS)
  • Network-attached Storage (NAS)
  • Storage Area Network (SAN)

Storage Architectures Covered:

  • File-Based Storage
  • Object Storage
  • Block Storage

Deployment Models Covered:

  • Hybrid Cloud
  • Private Cloud
  • Public Cloud
  • Edge Computing
  • On-Premises

Storage Mediums Covered:

  • Hard Disk Drive (HDD)
  • Solid State Drive (SSD)

End Users Covered:

  • BFSI
  • Enterprises
  • Government Bodies
  • Cloud Service Providers (CSP)
  • Telecom Companies
  • Other End Users

Regions Covered:

  • North America
    • US
    • Canada
    • Mexico
  • Europe
    • Germany
    • UK
    • Italy
    • France
    • Spain
    • Rest of Europe
  • Asia Pacific
    • Japan
    • China
    • India
    • Australia
    • New Zealand
    • South Korea
    • Rest of Asia Pacific
  • South America
    • Argentina
    • Brazil
    • Chile
    • Rest of South America
  • Middle East & Africa
    • Saudi Arabia
    • UAE
    • Qatar
    • South Africa
    • Rest of Middle East & Africa

What our report offers:

  • Market share assessments for the regional and country-level segments
  • Strategic recommendations for the new entrants
  • Covers Market data for the years 2024, 2025, 2026, 2028, and 2032
  • Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
  • Strategic recommendations in key business segments based on the market estimations
  • Competitive landscaping mapping the key common trends
  • Company profiling with detailed strategies, financials, and recent developments
  • Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

  • Company Profiling
    • Comprehensive profiling of additional market players (up to 3)
    • SWOT Analysis of key players (up to 3)
  • Regional Segmentation
    • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
  • Competitive Benchmarking
    • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

2 Preface

  • 2.1 Abstract
  • 2.2 Stake Holders
  • 2.3 Research Scope
  • 2.4 Research Methodology
    • 2.4.1 Data Mining
    • 2.4.2 Data Analysis
    • 2.4.3 Data Validation
    • 2.4.4 Research Approach
  • 2.5 Research Sources
    • 2.5.1 Primary Research Sources
    • 2.5.2 Secondary Research Sources
    • 2.5.3 Assumptions

3 Market Trend Analysis

  • 3.1 Introduction
  • 3.2 Drivers
  • 3.3 Restraints
  • 3.4 Opportunities
  • 3.5 Threats
  • 3.6 End User Analysis
  • 3.7 Emerging Markets
  • 3.8 Impact of Covid-19

4 Porters Five Force Analysis

  • 4.1 Bargaining power of suppliers
  • 4.2 Bargaining power of buyers
  • 4.3 Threat of substitutes
  • 4.4 Threat of new entrants
  • 4.5 Competitive rivalry

5 Global AI Powered Storage Market, By Offering

  • 5.1 Introduction
  • 5.2 Hardware
  • 5.3 Software

6 Global AI Powered Storage Market, By Solution Type

  • 6.1 Introduction
  • 6.2 AI Integration Software
  • 6.3 Data Protection Software
  • 6.4 Storage Management Software

7 Global AI Powered Storage Market, By Storage System

  • 7.1 Introduction
  • 7.2 Direct-attached Storage (DAS)
  • 7.3 Network-attached Storage (NAS)
  • 7.4 Storage Area Network (SAN)

8 Global AI Powered Storage Market, By Storage Architecture

  • 8.1 Introduction
  • 8.2 File-Based Storage
  • 8.3 Object Storage
  • 8.4 Block Storage

9 Global AI Powered Storage Market, By Deployment Model

  • 9.1 Introduction
  • 9.2 Hybrid Cloud
  • 9.3 Private Cloud
  • 9.4 Public Cloud
  • 9.5 Edge Computing
  • 9.6 On-Premises

10 Global AI Powered Storage Market, By Storage Medium

  • 10.1 Introduction
  • 10.2 Hard Disk Drive (HDD)
  • 10.3 Solid State Drive (SSD)

11 Global AI Powered Storage Market, By End User

  • 11.1 Introduction
  • 11.2 BFSI
  • 11.3 Enterprises
  • 11.4 Government Bodies
  • 11.5 Cloud Service Providers (CSP)
  • 11.6 Telecom Companies
  • 11.7 Other End Users

12 Global AI Powered Storage Market, By Geography

  • 12.1 Introduction
  • 12.2 North America
    • 12.2.1 US
    • 12.2.2 Canada
    • 12.2.3 Mexico
  • 12.3 Europe
    • 12.3.1 Germany
    • 12.3.2 UK
    • 12.3.3 Italy
    • 12.3.4 France
    • 12.3.5 Spain
    • 12.3.6 Rest of Europe
  • 12.4 Asia Pacific
    • 12.4.1 Japan
    • 12.4.2 China
    • 12.4.3 India
    • 12.4.4 Australia
    • 12.4.5 New Zealand
    • 12.4.6 South Korea
    • 12.4.7 Rest of Asia Pacific
  • 12.5 South America
    • 12.5.1 Argentina
    • 12.5.2 Brazil
    • 12.5.3 Chile
    • 12.5.4 Rest of South America
  • 12.6 Middle East & Africa
    • 12.6.1 Saudi Arabia
    • 12.6.2 UAE
    • 12.6.3 Qatar
    • 12.6.4 South Africa
    • 12.6.5 Rest of Middle East & Africa

13 Key Developments

  • 13.1 Agreements, Partnerships, Collaborations and Joint Ventures
  • 13.2 Acquisitions & Mergers
  • 13.3 New Product Launch
  • 13.4 Expansions
  • 13.5 Other Key Strategies

14 Company Profiling

  • 14.1 Alphabet (Google Inc.)
  • 14.2 Dell Technologies Inc.
  • 14.3 Huawei Technologies Co., Ltd.
  • 14.4 Cisco Systems, Inc.
  • 14.5 Intel Corporation
  • 14.6 Flextronics International Ltd.
  • 14.7 Toshiba Corporation
  • 14.8 Lenovo Group Limited
  • 14.9 Amazon Web Services
  • 14.10 Hewlett Packard Enterprise Company (HPE)
  • 14.11 Fujitsu Limited
  • 14.12 NVIDIA Corporation
  • 14.13 IBM Corporation
  • 14.14 Hitachi Ltd.
  • 14.15 Samsung Electronics Co. Ltd.

List of Tables

  • Table 1 Global AI Powered Storage Market Outlook, By Region (2024-2032) ($MN)
  • Table 2 Global AI Powered Storage Market Outlook, By Offering (2024-2032) ($MN)
  • Table 3 Global AI Powered Storage Market Outlook, By Hardware (2024-2032) ($MN)
  • Table 4 Global AI Powered Storage Market Outlook, By Software (2024-2032) ($MN)
  • Table 5 Global AI Powered Storage Market Outlook, By Solution Type (2024-2032) ($MN)
  • Table 6 Global AI Powered Storage Market Outlook, By AI Integration Software (2024-2032) ($MN)
  • Table 7 Global AI Powered Storage Market Outlook, By Data Protection Software (2024-2032) ($MN)
  • Table 8 Global AI Powered Storage Market Outlook, By Storage Management Software (2024-2032) ($MN)
  • Table 9 Global AI Powered Storage Market Outlook, By Storage System (2024-2032) ($MN)
  • Table 10 Global AI Powered Storage Market Outlook, By Direct-attached Storage (DAS) (2024-2032) ($MN)
  • Table 11 Global AI Powered Storage Market Outlook, By Network-attached Storage (NAS) (2024-2032) ($MN)
  • Table 12 Global AI Powered Storage Market Outlook, By Storage Area Network (SAN) (2024-2032) ($MN)
  • Table 13 Global AI Powered Storage Market Outlook, By Storage Architecture (2024-2032) ($MN)
  • Table 14 Global AI Powered Storage Market Outlook, By File-Based Storage (2024-2032) ($MN)
  • Table 15 Global AI Powered Storage Market Outlook, By Object Storage (2024-2032) ($MN)
  • Table 16 Global AI Powered Storage Market Outlook, By Block Storage (2024-2032) ($MN)
  • Table 17 Global AI Powered Storage Market Outlook, By Deployment Model (2024-2032) ($MN)
  • Table 18 Global AI Powered Storage Market Outlook, By Hybrid Cloud (2024-2032) ($MN)
  • Table 19 Global AI Powered Storage Market Outlook, By Private Cloud (2024-2032) ($MN)
  • Table 20 Global AI Powered Storage Market Outlook, By Public Cloud (2024-2032) ($MN)
  • Table 21 Global AI Powered Storage Market Outlook, By Edge Computing (2024-2032) ($MN)
  • Table 22 Global AI Powered Storage Market Outlook, By On-Premises (2024-2032) ($MN)
  • Table 23 Global AI Powered Storage Market Outlook, By Storage Medium (2024-2032) ($MN)
  • Table 24 Global AI Powered Storage Market Outlook, By Hard Disk Drive (HDD) (2024-2032) ($MN)
  • Table 25 Global AI Powered Storage Market Outlook, By Solid State Drive (SSD) (2024-2032) ($MN)
  • Table 26 Global AI Powered Storage Market Outlook, By End User (2024-2032) ($MN)
  • Table 27 Global AI Powered Storage Market Outlook, By BFSI (2024-2032) ($MN)
  • Table 28 Global AI Powered Storage Market Outlook, By Enterprises (2024-2032) ($MN)
  • Table 29 Global AI Powered Storage Market Outlook, By Government Bodies (2024-2032) ($MN)
  • Table 30 Global AI Powered Storage Market Outlook, By Cloud Service Providers (CSP) (2024-2032) ($MN)
  • Table 31 Global AI Powered Storage Market Outlook, By Telecom Companies (2024-2032) ($MN)
  • Table 32 Global AI Powered Storage Market Outlook, By Other End Users (2024-2032) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.