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市場調查報告書
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1470702

人工智慧驅動的儲存市場：依產品類型、最終用戶、地區 - 全球產業分析、規模、佔有率、成長、趨勢、預測，2024-2031 年

AI-Powered Storage Market by Product Type, End-Users, and Geography (North America, Europe, Asia Pacific, Latin America, and the Middle East and Africa): Global Industry Analysis, Size, Share, Growth, Trends, and Forecast, 2024-2031
出版日期: | 出版商: Persistence Market Research | 英文 310 Pages | 商品交期: 2-5個工作天內

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簡介目錄

本研究報告是Persistence Market Research的市場研究報告，詳細分析並預測了全球配備AI的儲存市場。 這份綜合報告提供了關鍵市場動態、市場成長驅動因素、課題和新興趨勢的寶貴見解。 它詳細概述了資訊科技產業中人工智慧驅動的儲存領域，並提供了獨家數據和統計數據來預測 2024 年至 2031 年的市場成長軌跡。

關鍵見解

  • 人工智慧驅動的儲存市場規模（2024 年）：233 億美元
  • 預測市場規模（2031 年）：1,100 億美元
  • 全球市場成長率（複合年增長率，2024-2031 年）：18.9%

人工智慧驅動的儲存市場 - 報告範圍：

人工智慧驅動的儲存市場涵蓋各種硬體、軟體和服務，它們利用人工智慧 (AI) 和機器學習 (ML) 技術來優化儲存基礎設施、資料管理和分析功能。 該市場為企業、雲端服務供應商、資料中心和託管服務供應商提供人工智慧驅動的儲存解決方案，用於資料處理、分析和洞察生成。 人工智慧驅動的儲存平台使企業能夠提高資料可存取性、可擴充性和效能，同時降低儲存成本、複雜性和管理開銷。 市場成長的驅動力是資料量的增加、對即時分析的需求以及採用人工智慧驅動的自動化進行儲存最佳化和預測性維護。

推動市場成長的因素：

全球人工智慧驅動的儲存市場正受益於幾個關鍵的成長動力。 數位轉型計畫、物聯網設備和多媒體內容產生的數據呈指數級增長，推動了對能夠處理不同數據類型和工作負載的人工智慧儲存解決方案的需求。 此外，人工智慧演算法、深度學習模型和神經網路的進步支援預測分析、異常檢測和資料分類，以實現儲存優化和資料治理。 此外，向混合和多雲環境、邊緣運算和容器化儲存架構的轉變正在推動對人工智慧驅動的儲存平台的需求，這些平台可以實現跨分散式IT 基礎設施的無縫資料移動性、安全性和合規性。 此外，金融、醫療保健和零售等行業對即時洞察和決策能力的需求日益增長，從而加速了數據分析和商業智慧應用程式採用人工智慧驅動的儲存。

市場限制因素：

儘管成長前景廣闊，但人工智慧驅動的儲存市場面臨技術整合、資料隱私和人才短缺等課題。 將人工智慧驅動的儲存解決方案與現有 IT 基礎設施和遺留儲存系統整合可能需要在硬體、軟體和專業服務方面進行大量投資，這可能會影響採用率和投資回報率。 此外，對資料安全、隱私和監管合規性的擔憂成為採用人工智慧驅動的儲存平台的障礙，特別是在具有嚴格資料保護要求的高度監管行業。 此外，缺乏能夠設計、實施和管理人工智慧驅動的儲存解決方案的熟練人工智慧和數據科學專業人員也限制了市場的成長和創新。 解決這些障礙需要技術供應商、網路安全專家和監管機構共同努力，開發強大、可擴展且安全的人工智慧驅動的儲存解決方案，以滿足企業需求和監管標準。

市場機會：

人工智慧驅動的儲存市場透過技術創新、產業聯盟和垂直市場擴張提供了巨大的成長機會。 人工智慧驅動的資料管理、聯合學習和邊緣人工智慧處理等新興趨勢為儲存供應商提供了新的途徑，使其產品脫穎而出並滿足不斷變化的客戶需求。 開發包含資料治理、加密和合規性功能的人工智慧驅動的儲存解決方案可以幫助企業滿足監管要求並降低資料密集型環境中的網路安全風險。 此外，與雲端服務供應商、人工智慧軟體供應商和行業特定解決方案提供商的策略合作夥伴關係加速了人工智慧驅動的儲存平台的市場滲透和客戶採用。 此外，對人工智慧人才開發、培訓計劃和認證計劃的投資將推動人工智慧驅動的儲存市場的創新和人才管道的成長。

本報告涵蓋的主要問題

  • 推動全球人工智慧儲存市場成長的因素有哪些？
  • 人工智慧演算法和機器學習技術的進步如何改變人工智慧驅動的儲存解決方案的競爭格局？
  • 儲存供應商和企業客戶在人工智慧驅動的儲存市場中面臨哪些主要課題和機會？
  • 哪些產業和用例在採用人工智慧驅動的儲存方面最具成長潛力？
  • 領先公司正在採取哪些策略來實現人工智慧驅動儲存的差異化並贏得市場佔有率？

競爭資訊與業務策略：

全球人工智慧驅動的儲存市場的主要參與者，包括儲存供應商、人工智慧軟體供應商和雲端服務供應商，正在專注於創新、合作夥伴關係和以客戶為中心的策略，以推動市場成長並保持競爭力。 這些公司正在投資研發，開發人工智慧驅動的儲存平台，該平台具有重複資料刪除、壓縮和分層等高級功能，以優化成本並提高效能。 此外，與人工智慧軟體供應商、系統整合商和產業合作夥伴的策略聯盟使企業能夠將人工智慧驅動的分析、資料管理和自動化功能整合到其儲存解決方案中，從而為客戶提供附加價值。 此外，我們對客戶參與、解決方案客製化和垂直市場專業化的關注提高了在人工智慧驅動的儲存市場競爭格局中的品牌認知度和客戶忠誠度。

公司主要簡介

  • Intel Corporation
  • NVIDIA Corporation
  • IBM
  • Samsung Electronics
  • Pure Storage
  • NetApp
  • Micron Technology
  • CISCO
  • Toshiba
  • Hitachi
  • Lenovo
  • Dell
  • HPE

人工智慧驅動的儲存市場研究細分：

透過提供

  • 軟體
  • 硬體

依儲存系統

  • 直接附加存儲
  • 網路附加存儲
  • 儲存區域網絡

依儲存架構劃分

  • 硬碟機 (HDD)
  • 固態硬碟 (SSD)。

最終使用者

  • 公司
  • 政府機構
  • 雲端服務供應商
  • 電信公司

依地區

  • 北美
  • 歐洲
  • 亞太地區
  • 行

目錄

第 1 章執行摘要

第二章市場概述

  • 市場範圍/分類
  • 市場定義/範圍/限制

第三章市場風險與趨勢評估

  • 風險評估
    • 新冠肺炎 (COVID-19) 危機及其對人工智慧驅動的儲存市場的影響
    • 與過去的危機相比，對新冠肺炎 (COVID-19) 的影響進行基準測試
    • 對市場價值的影響
    • 評估：依主要國家劃分
    • 評估：依主要細分市場
    • 針對供應商的行動要點和建議
  • 影響市場的主要趨勢
  • 配方和產品開發的趨勢

第四章市場背景

  • 人工智慧儲存市場：依主要國家劃分
  • 人工智慧驅動的儲存市場機會評估
  • 市場情境預測
  • 投資可行性分析
  • 預測因子 - 相關性和影響
  • 市場動態

第 5 章關鍵成功因素

  • 製造商專注於滲透率低但成長率高的市場
  • 押注該細分市場的高增量機會
  • 同業基準

第六章全球人工智慧儲存市場需求分析（2019-2023）及預測（2024-2031）

  • 過去的市場分析，2019-2023 年
  • 2024-2031 年當前與未來市場預測
  • 年成長趨勢分析

第七章全球人工智慧儲存市場貨幣分析（2019-2023）與預測（2024-2031）

  • 過去的市場價值分析，2019-2023 年
  • 2024-2031 年當前與未來市場價值預測
    • 年成長趨勢分析
    • 絕對數量機會分析

第 8 章全球人工智慧儲存市場分析（2019-2023 年）與預測（2024-2031 年）：依產品劃分

  • 簡介/主要發現
  • 2019-2023 年歷史市場價值與依產品分析
  • 2024-2031 年當前和未來的市場價值以及依產品分類的分析和預測
    • 硬體
    • 軟體
  • 市場吸引力分析：依產品分類

第9章全球人工智慧儲存市場分析（2019-2023）與預測（2024-2031）：依儲存系統劃分

  • 簡介/主要發現
  • 過去的市場價值與分析：依儲存系統劃分，2019-2023 年
  • 當前和未來的市場價值、分析和預測：依儲存系統劃分，2024 年至 2031 年
    • 直接附加儲存 (DAS)
    • 網路附加儲存 (NAS)
    • 儲存區域網路 (SAN)
  • 市場吸引力分析：依儲存系統分類

第 10 章全球人工智慧驅動的儲存市場分析（2019-2023 年）與預測（2024-2031 年）：依儲存架構劃分

  • 簡介/主鍵調查結果
  • 歷史市場價值與分析：依儲存架構劃分，2019-2023 年
  • 2024-2031 年儲存架構當前與未來的市場價值、分析與預測
    • 基於檔案/基於物件的存儲
    • 物件存儲
  • 市場吸引力分析：依儲存架構

第11章全球人工智慧儲存市場分析（2019-2023）與預測（2024-2031）：依儲存媒體劃分

  • 簡介/主要發現
  • 過去的市場價值與分析：依儲存媒體劃分，2019-2023 年
  • 當前和未來的市場價值、分析和預測：依儲存媒體劃分，2024-2031 年
    • 硬碟機 (HDD)
    • 固態硬碟 (SSD)
  • 市場吸引力分析：依儲存媒體

第 12 章全球人工智慧儲存市場分析（2019-2023 年）和預測（2024-2031 年）：依最終用戶劃分

  • 簡介/主要發現
  • 歷史市場價值與分析：依最終用戶劃分，2019-2023 年
  • 當前和未來的市場價值、分析和預測：依最終用戶劃分，2024 年至 2031 年
    • 公司
    • 政府機構
    • 雲端服務供應商
    • 電信公司
  • 市場吸引力分析：依最終用戶分類

第 13 章全球人工智慧儲存市場分析（2019-2023 年）與預測（2024-2031 年）：依地區劃分

  • 簡介
  • 市場價值與分析：依地區劃分，2019-2023 年
  • 目前市場規模、分析與預測：依地區劃分，2024-2031 年
    • 北美
    • 亞太地區
    • 歐洲
    • 行
  • 市場吸引力分析：依地區劃分

第14章北美人工智慧儲存市場分析（2019-2023）與預測（2024-2031）

第十五章拉丁美洲人工智慧儲存市場分析（2019-2023）與預測（2024-2031）

第16章歐洲人工智慧儲存市場分析（2019-2023年）與預測（2024-2031年）

第十七章亞太地區人工智慧儲存市場分析（2019-2023）與預測（2024-2031）

第十八章中東與非洲人工智慧儲存市場分析（2019-2023）與預測（2024-2031）

第十九章主要國家人工智慧儲存市場分析（2019-2023）及預測（2024-2031）

  • 簡介
    • 市值比分析：依主要國家分類
    • 世界與各國的成長比較
  • 美國人工智慧儲存市場分析
    • 價值比率分析：依市場分類
    • 價值、分析與預測：依市場分類，2024-2031 年
      • 依儲存架構
      • 透過提供
      • 依儲存系統
      • 依儲存媒體
      • 依最終用戶
  • 加拿大人工智慧儲存市場分析
    • 價值比率分析：依市場分類
    • 價值、分析與預測：依市場分類，2024-2031 年
      • 依儲存架構
      • 透過提供
      • 依儲存系統
      • 依儲存媒體
      • 依最終用戶
  • 墨西哥人工智慧儲存市場分析
    • 價值比率分析：依市場分類
    • 價值、分析與預測：依市場分類，2024-2031 年
      • 依儲存架構
      • 透過提供
      • 依儲存系統
      • 依儲存媒體
      • 依最終用戶
  • 巴西人工智慧儲存市場分析
    • 價值比率分析：依市場分類
    • 價值、分析與預測：依市場分類，2024-2031 年
      • 依儲存架構
      • 透過提供
      • 依儲存系統
      • 依儲存媒體
      • 依最終用戶
  • 德國人工智慧儲存市場分析
    • 價值比率分析：依市場分類
    • 價值、分析與預測：依市場分類，2024-2031 年
      • 依儲存架構
      • 透過提供
      • 依儲存系統
      • 依儲存媒體
      • 依最終用戶
  • 法國人工智慧儲存市場分析
    • 價值比率分析：依市場分類
    • 價值、分析與預測：依市場分類，2024-2031 年
      • 依儲存架構
      • 透過提供
      • 依儲存系統
      • 依儲存媒體
      • 依最終用戶
  • 義大利人工智慧儲存市場分析
    • 價值比率分析：依市場分類
    • 價值、分析與預測：依市場分類，2024-2031 年
      • 依儲存架構
      • 透過提供
      • 依儲存系統
      • 依儲存媒體
      • 依最終用戶
  • 俄羅斯人工智慧儲存市場分析
    • 價值比率分析：依市場分類
    • 價值、分析與預測：依市場分類，2024-2031 年
      • 依儲存架構
      • 透過提供
      • 依儲存系統
      • 依儲存媒體
      • 依最終用戶
  • 英國人工智慧儲存市場分析
    • 價值比率分析：依市場分類
    • 價值、分析與預測：依市場分類，2024-2031 年
      • 依儲存架構
      • 透過提供
      • 依儲存系統
      • 依儲存媒體
      • 依最終用戶
  • 中國人工智慧儲存市場分析
    • 價值比率分析：依市場分類
    • 價值、分析與預測：依市場分類，2024-2031 年
      • 依儲存架構
      • 透過提供
      • 依儲存系統
      • 依儲存媒體
      • 依最終用戶
  • 日本人工智慧儲存市場分析
    • 價值比率分析：依市場分類
    • 價值、分析與預測：依市場分類，2024-2031 年
      • 依儲存架構
      • 透過提供
      • 依儲存系統
      • 依儲存媒體
      • 依最終用戶
  • 韓國人工智慧儲存市場分析
    • 價值比率分析：依市場分類
    • 價值、分析與預測：依市場分類，2024-2031 年
      • 依儲存架構
      • 透過提供
      • 依儲存系統
      • 依儲存媒體
      • 依最終用戶
  • 海灣合作委員會國家配備人工智慧的儲存市場分析
    • 價值比率分析：依市場分類
    • 價值、分析與預測：依市場分類，2024-2031 年
      • 依儲存架構
      • 透過提供
      • 依儲存系統
      • 依儲存媒體
      • 依最終用戶
  • 南非人工智慧儲存市場分析
    • 價值比率分析：依市場分類
    • 價值、分析與預測：依市場分類，2024-2031 年
      • 依儲存架構
      • 透過提供
      • 依儲存系統
      • 依儲存媒體
      • 依最終用戶
  • 土耳其人工智慧儲存市場分析
    • 價值比率分析：依市場分類
    • 價值、分析與預測：依市場分類，2024-2031 年
      • 依儲存架構
      • 透過提供
      • 依儲存系統
      • 依儲存媒體
      • 依最終用戶
    • 國內競爭情勢及企業集中度

第20章市場結構分析

  • 市場分析：依公司層級
  • 市場集中度
  • 主要公司市佔率分析
  • 市場現況分析

第21章競爭分析

  • 競爭對手儀表板
  • 競爭基準
  • 衝突詳情
    • Intel Corporation
    • NVIDIA Corporation
    • IBM
    • Samsung Electronics
    • Pure Storage
    • NetApp
    • Micron Technology
    • CISCO
    • Toshiba
    • Hitachi
    • Lenovo
    • Dell
    • HPE

第 22 章先決條件與使用的縮寫

第23章研究方法

簡介目錄
Product Code: PMRREP33040

Persistence Market Research, a leading market research firm, has conducted an in-depth analysis of the global AI-Powered Storage Market. This comprehensive report provides valuable insights into key market dynamics, growth drivers, challenges, and emerging trends. It offers a detailed overview of the AI-powered storage segment within the information technology industry, presenting exclusive data and statistics projecting the market's growth trajectory from 2024 to 2031.

Key Insights:

  • AI-Powered Storage Market Size (2024): US$ 23.3 Billion
  • Projected Market Value (2031): US$ 110 Billion
  • Global Market Growth Rate (CAGR 2024 to 2031): 18.9%

AI-Powered Storage Market - Report Scope:

The AI-Powered Storage Market encompasses a diverse range of hardware, software, and services leveraging artificial intelligence (AI) and machine learning (ML) technologies to optimize storage infrastructure, data management, and analytics capabilities. This market serves enterprises, cloud service providers, data centers, and managed service providers, offering AI-driven storage solutions for data processing, analysis, and insights generation. AI-powered storage platforms enable organizations to improve data accessibility, scalability, and performance while reducing storage costs, complexity, and management overhead. Market growth is driven by increasing data volumes, demand for real-time analytics, and adoption of AI-driven automation for storage optimization and predictive maintenance.

Market Growth Drivers:

The global AI-Powered Storage Market benefits from several key growth drivers. The exponential growth of data generated by digital transformation initiatives, IoT devices, and multimedia content fuels demand for AI-powered storage solutions capable of handling diverse data types and workloads. Moreover, advancements in AI algorithms, deep learning models, and neural networks enable predictive analytics, anomaly detection, and data classification for storage optimization and data governance. Furthermore, the shift towards hybrid and multi-cloud environments, edge computing, and containerized storage architectures drives demand for AI-driven storage platforms that deliver seamless data mobility, security, and compliance across distributed IT infrastructure. Additionally, the growing need for real-time insights and decision-making capabilities in industries such as finance, healthcare, and retail accelerates adoption of AI-powered storage for data analytics and business intelligence applications.

Market Restraints:

Despite its promising growth prospects, the AI-Powered Storage Market faces challenges related to technology integration, data privacy, and talent shortage. Integrating AI-driven storage solutions with existing IT infrastructure and legacy storage systems may require significant investments in hardware, software, and professional services, impacting adoption rates and return on investment. Moreover, concerns about data security, privacy, and regulatory compliance pose barriers to deploying AI-powered storage platforms, particularly in highly regulated industries with strict data protection requirements. Additionally, the shortage of skilled AI and data science professionals capable of designing, implementing, and managing AI-powered storage solutions limits market growth and innovation. Addressing these barriers requires collaboration between technology vendors, cybersecurity experts, and regulatory authorities to develop robust, scalable, and secure AI-driven storage solutions that meet enterprise needs and regulatory standards.

Market Opportunities:

The AI-Powered Storage Market presents significant growth opportunities driven by technological innovations, industry partnerships, and vertical market expansion. Emerging trends such as AI-driven data management, federated learning, and edge AI processing offer new avenues for storage vendors to differentiate their offerings and address evolving customer needs. The development of AI-powered storage solutions with built-in data governance, encryption, and compliance features enables organizations to meet regulatory requirements and mitigate cybersecurity risks in data-intensive environments. Furthermore, strategic partnerships with cloud service providers, AI software vendors, and industry-specific solution providers facilitate market penetration and customer adoption of AI-driven storage platforms. Moreover, investment in AI talent development, training programs, and certification initiatives fosters innovation and talent pipeline growth in the AI-Powered Storage Market.

Key Questions Answered in the Report:

  • What factors are driving the growth of the AI-Powered Storage Market globally?
  • How are advancements in AI algorithms and machine learning technologies reshaping the competitive landscape of AI-driven storage solutions?
  • What are the key challenges and opportunities facing storage vendors and enterprise customers in the AI-Powered Storage Market?
  • Which industries and use cases offer the highest growth potential for AI-powered storage adoption?
  • What strategies are leading companies employing to differentiate their AI-driven storage offerings and gain market share?

Competitive Intelligence and Business Strategy:

Leading players in the global AI-Powered Storage Market, including storage vendors, AI software providers, and cloud service providers, focus on innovation, partnerships, and customer-centric strategies to drive market growth and maintain competitiveness. These companies invest in research and development to develop AI-driven storage platforms with advanced features such as data deduplication, compression, and tiering for cost optimization and performance enhancement. Moreover, strategic alliances with AI software vendors, system integrators, and industry partners enable companies to integrate AI-driven analytics, data management, and automation capabilities into their storage solutions, delivering added value to customers. Furthermore, emphasis on customer engagement, solution customization, and vertical market specialization enhances brand reputation and customer loyalty in the competitive landscape of AI-Powered Storage Market.

Key Companies Profiled:

  • Intel Corporation
  • NVIDIA Corporation
  • IBM
  • Samsung Electronics
  • Pure Storage
  • NetApp
  • Micron Technology
  • CISCO
  • Toshiba
  • Hitachi
  • Lenovo
  • Dell
  • HPE

AI-Powered Storage Market Research Segmentation:

By Offering

  • Software
  • Hardware

By Storage System

  • Direct-Attached Storage
  • Network-Attached Storage
  • Storage Area Network

By Storage Architecture

  • Hard Disk Drives (HDD)
  • Solid-State Drives (SSD).

By End User

  • Enterprises
  • Government Bodies
  • Cloud Service Providers
  • Telecom Companies

By Region

  • North America
  • Europe
  • Asia-Pacific
  • ROW

Table of Contents

1. Executive Summary

  • 1.1. Global Market Outlook
  • 1.2. Summary of Statistics
  • 1.3. Key Market Characteristics & Attributes
  • 1.4. Fact.MR Analysis and Recommendations

2. Market Overview

  • 2.1. Market Coverage / Taxonomy
  • 2.2. Market Definition / Scope / Limitations

3. Market Risks and Trends Assessment

  • 3.1. Risk Assessment
    • 3.1.1. COVID-19 Crisis and Impact on AI Powered Storage Market
    • 3.1.2. COVID-19 Impact Benchmark with Previous Crisis
    • 3.1.3. Impact on Market Value (US$ Mn)
    • 3.1.4. Assessment by Key Countries
    • 3.1.5. Assessment by Key Market Segments
    • 3.1.6. Action Points and Recommendation for Suppliers
  • 3.2. Key Trends Impacting the Market
  • 3.3. Formulation and Product Development Trends

4. Market Background

  • 4.1. AI Powered Storage Market, by Key Countries
  • 4.2. AI Powered Storage Market Opportunity Assessment (US$ Mn)
    • 4.2.1. Total Available Market
    • 4.2.2. Serviceable Addressable Market
    • 4.2.3. Serviceable Obtainable Market
  • 4.3. Market Scenario Forecast
    • 4.3.1. Demand in optimistic Scenario
    • 4.3.2. Demand in Likely Scenario
    • 4.3.3. Demand in Conservative Scenario
  • 4.4. Investment Feasibility Analysis
    • 4.4.1. Investment in Established Markets
      • 4.4.1.1. In Short Term
      • 4.4.1.2. In Long Term
    • 4.4.2. Investment in Emerging Markets
      • 4.4.2.1. In Short Term
      • 4.4.2.2. In Long Term
  • 4.5. Forecast Factors - Relevance & Impact
    • 4.5.1. Top Companies Historical Growth
    • 4.5.2. Growth in Automation, By Country
    • 4.5.3. AI Powered Storage Market Adoption Rate, By Country
  • 4.6. Market Dynamics
    • 4.6.1. Market Driving Factors and Impact Assessment
    • 4.6.2. Prominent Market Challenges and Impact Assessment
    • 4.6.3. AI Powered Storage Market Opportunities
    • 4.6.4. Prominent Trends in the Global Market & Their Impact Assessment

5. Key Success Factors

  • 5.1. Manufacturers' Focus on Low Penetration High Growth Markets
  • 5.2. Banking on with Segments High Incremental Opportunity
  • 5.3. Peer Benchmarking

6. Global AI Powered Storage Market Demand Analysis 2019-2023 and Forecast, 2024-2031

  • 6.1. Historical Market Analysis, 2019-2023
  • 6.2. Current and Future Market Projections, 2024-2031
  • 6.3. Y-o-Y Growth Trend Analysis

7. Global AI Powered Storage Market Value Analysis 2019-2023 and Forecast, 2024-2031

  • 7.1. Historical Market Value (US$ Mn) Analysis, 2019-2023
  • 7.2. Current and Future Market Value (US$ Mn) Projections, 2024-2031
    • 7.2.1. Y-o-Y Growth Trend Analysis
    • 7.2.2. Absolute $ Opportunity Analysis

8. Global AI Powered Storage Market Analysis 2019-2023 and Forecast 2024-2031, By Offering

  • 8.1. Introduction / Key Findings
  • 8.2. Historical Market Value (US$ Mn) and Analysis By Offering, 2019-2023
  • 8.3. Current and Future Market Value (US$ Mn) and Analysis and Forecast By Offering, 2024-2031
    • 8.3.1. Hardware
    • 8.3.2. Software
  • 8.4. Market Attractiveness Analysis By Offering

9. Global AI Powered Storage Market Analysis 2019-2023 and Forecast 2024-2031, By Storage System

  • 9.1. Introduction / Key Findings
  • 9.2. Historical Market Value (US$ Mn) and Analysis By Storage System, 2019-2023
  • 9.3. Current and Future Market Value (US$ Mn) and Analysis and Forecast By Storage System, 2024-2031
    • 9.3.1. Direct-attached Storage (DAS)
    • 9.3.2. Network-attached Storage (NAS)
    • 9.3.3. Storage Area Network (SAN)
  • 9.4. Market Attractiveness Analysis By Storage System

10. Global AI Powered Storage Market Analysis 2019-2023 and Forecast 2024-2031, By Storage Architecture

  • 10.1. Introduction / Key Findings
  • 10.2. Historical Market Value (US$ Mn) and Analysis By Storage Architecture, 2019-2023
  • 10.3. Current and Future Market Value (US$ Mn) and Analysis and Forecast By Storage Architecture, 2024-2031
    • 10.3.1. File- and Object-Based Storage
    • 10.3.2. Object Storage
  • 10.4. Market Attractiveness Analysis By Storage Architecture

11. Global AI Powered Storage Market Analysis 2019-2023 and Forecast 2024-2031, By Storage Medium

  • 11.1. Introduction / Key Findings
  • 11.2. Historical Market Value (US$ Mn) and Analysis By Storage Medium, 2019-2023
  • 11.3. Current and Future Market Value (US$ Mn) and Analysis and Forecast By Storage Medium, 2024-2031
    • 11.3.1. Hard Disk Drive (HDD)
    • 11.3.2. Solid State Drive (SSD)
  • 11.4. Market Attractiveness Analysis By Storage Medium

12. Global AI Powered Storage Market Analysis 2019-2023 and Forecast 2024-2031, By End-user

  • 12.1. Introduction / Key Findings
  • 12.2. Historical Market Value (US$ Mn) and Analysis By End-user, 2019-2023
  • 12.3. Current and Future Market Value (US$ Mn) and Analysis and Forecast By End-user, 2024-2031
    • 12.3.1. Enterprises
    • 12.3.2. Government Bodies
    • 12.3.3. Cloud Service Providers
    • 12.3.4. Telecom Companies
  • 12.4. Market Attractiveness Analysis By End-user

13. Global AI Powered Storage Market Analysis 2019-2023 and Forecast 2024-2031, By Region

  • 13.1. Introduction
  • 13.2. Historical Market Value (US$ Mn) and Analysis By Region, 2019-2023
  • 13.3. Current Market Size (US$ Mn) & Analysis and Forecast By Region, 2024-2031
    • 13.3.1. North America
    • 13.3.2. APAC
    • 13.3.3. Europe
    • 13.3.4. ROW
  • 13.4. Market Attractiveness Analysis By Region

14. North America AI Powered Storage Market Analysis 2019-2023 and Forecast 2024-2031

  • 14.1. Introduction
  • 14.2. Pricing Analysis
  • 14.3. Historical Market Value (US$ Mn) and Trend Analysis By Market Taxonomy, 2019-2023
  • 14.4. Market Value (US$ Mn) & Forecast By Market Taxonomy, 2024-2031
    • 14.4.1. By Country
      • 14.4.1.1. U.S.
      • 14.4.1.2. Canada
      • 14.4.1.3. Rest of North America
    • 14.4.2. By Storage Architecture
    • 14.4.3. By Offering
    • 14.4.4. By Storage System
    • 14.4.5. By Storage Medium
    • 14.4.6. By End-user
  • 14.5. Market Attractiveness Analysis
    • 14.5.1. By Country
    • 14.5.2. By Storage Architecture
    • 14.5.3. By Offering
    • 14.5.4. By Storage System
    • 14.5.5. By Storage Medium
    • 14.5.6. By End-user

15. Latin America AI Powered Storage Market Analysis 2019-2023 and Forecast 2024-2031

  • 15.1. Introduction
  • 15.2. Pricing Analysis
  • 15.3. Historical Market Value (US$ Mn) and Trend Analysis By Market Taxonomy, 2019-2023
  • 15.4. Market Value (US$ Mn) & Forecast By Market Taxonomy, 2024-2031
    • 15.4.1. By Country
      • 15.4.1.1. Brazil
      • 15.4.1.2. Mexico
      • 15.4.1.3. Rest of Latin America
    • 15.4.2. By Storage Architecture
    • 15.4.3. By Offering
    • 15.4.4. By Storage System
    • 15.4.5. By Storage Medium
    • 15.4.6. By End-user
  • 15.5. Market Attractiveness Analysis
    • 15.5.1. By Country
    • 15.5.2. By Storage Architecture
    • 15.5.3. By Offering
    • 15.5.4. By Storage System
    • 15.5.5. By Storage Medium
    • 15.5.6. By End-user

16. Europe AI Powered Storage Market Analysis 2019-2023 and Forecast 2024-2031

  • 16.1. Introduction
  • 16.2. Pricing Analysis
  • 16.3. Historical Market Value (US$ Mn) and Trend Analysis By Market Taxonomy, 2019-2023
  • 16.4. Market Value (US$ Mn) & Forecast By Market Taxonomy, 2024-2031
    • 16.4.1. By Country
      • 16.4.1.1. Germany
      • 16.4.1.2. France
      • 16.4.1.3. U.K.
      • 16.4.1.4. Italy
      • 16.4.1.5. Russia
      • 16.4.1.6. Rest of Europe
    • 16.4.2. By Storage Architecture
    • 16.4.3. By Offering
    • 16.4.4. By Storage System
    • 16.4.5. By Storage Medium
    • 16.4.6. By End-user
  • 16.5. Market Attractiveness Analysis
    • 16.5.1. By Country
    • 16.5.2. By Storage Architecture
    • 16.5.3. By Offering
    • 16.5.4. By Storage System
    • 16.5.5. By Storage Medium
    • 16.5.6. By End-user

17. Asia Pacific AI Powered Storage Market Analysis 2019-2023 and Forecast 2024-2031

  • 17.1. Introduction
  • 17.2. Pricing Analysis
  • 17.3. Historical Market Value (US$ Mn) and Trend Analysis By Market Taxonomy, 2019-2023
  • 17.4. Market Value (US$ Mn) & Forecast By Market Taxonomy, 2024-2031
    • 17.4.1. By Country
      • 17.4.1.1. China
      • 17.4.1.2. Japan
      • 17.4.1.3. South Korea
      • 17.4.1.4. Rest of Asia Pacific
    • 17.4.2. By Storage Architecture
    • 17.4.3. By Offering
    • 17.4.4. By Storage System
    • 17.4.5. By Storage Medium
    • 17.4.6. By End-user
  • 17.5. Market Attractiveness Analysis
    • 17.5.1. By Country
    • 17.5.2. By Storage Architecture
    • 17.5.3. By Offering
    • 17.5.4. By Storage System
    • 17.5.5. By Storage Medium
    • 17.5.6. By End-user

18. Middle East and Africa AI Powered Storage Market Analysis 2019-2023 and Forecast 2024-2031

  • 18.1. Introduction
  • 18.2. Pricing Analysis
  • 18.3. Historical Market Value (US$ Mn) and Trend Analysis By Market Taxonomy, 2019-2023
  • 18.4. Market Value (US$ Mn) & Forecast By Market Taxonomy, 2024-2031
    • 18.4.1. By Country
      • 18.4.1.1. GCC Countries
      • 18.4.1.2. South Africa
      • 18.4.1.3. Turkey
      • 18.4.1.4. Rest of Middle East and Africa
    • 18.4.2. By Storage Architecture
    • 18.4.3. By Offering
    • 18.4.4. By Storage System
    • 18.4.5. By Storage Medium
    • 18.4.6. By End-user
  • 18.5. Market Attractiveness Analysis
    • 18.5.1. By Country
    • 18.5.2. By Storage Architecture
    • 18.5.3. By Offering
    • 18.5.4. By Storage System
    • 18.5.5. By Storage Medium
    • 18.5.6. By End-user

19. Key Countries AI Powered Storage Market Analysis 2019-2023 and Forecast 2024-2031

  • 19.1. Introduction
    • 19.1.1. Market Value Proportion Analysis, By Key Countries
    • 19.1.2. Global Vs. Country Growth Comparison
  • 19.2. US AI Powered Storage Market Analysis
    • 19.2.1. Value Proportion Analysis by Market Taxonomy
    • 19.2.2. Value & Analysis and Forecast by Market Taxonomy, 2024-2031
      • 19.2.2.1. By Storage Architecture
      • 19.2.2.2. By Offering
      • 19.2.2.3. By Storage System
      • 19.2.2.4. By Storage Medium
      • 19.2.2.5. By End-user
  • 19.3. Canada AI Powered Storage Market Analysis
    • 19.3.1. Value Proportion Analysis by Market Taxonomy
    • 19.3.2. Value & Analysis and Forecast by Market Taxonomy, 2024-2031
      • 19.3.2.1. By Storage Architecture
      • 19.3.2.2. By Offering
      • 19.3.2.3. By Storage System
      • 19.3.2.4. By Storage Medium
      • 19.3.2.5. By End-user
  • 19.4. Mexico AI Powered Storage Market Analysis
    • 19.4.1. Value Proportion Analysis by Market Taxonomy
    • 19.4.2. Value & Analysis and Forecast by Market Taxonomy, 2024-2031
      • 19.4.2.1. By Storage Architecture
      • 19.4.2.2. By Offering
      • 19.4.2.3. By Storage System
      • 19.4.2.4. By Storage Medium
      • 19.4.2.5. By End-user
  • 19.5. Brazil AI Powered Storage Market Analysis
    • 19.5.1. Value Proportion Analysis by Market Taxonomy
    • 19.5.2. Value & Analysis and Forecast by Market Taxonomy, 2024-2031
      • 19.5.2.1. By Storage Architecture
      • 19.5.2.2. By Offering
      • 19.5.2.3. By Storage System
      • 19.5.2.4. By Storage Medium
      • 19.5.2.5. By End-user
  • 19.6. Germany AI Powered Storage Market Analysis
    • 19.6.1. Value Proportion Analysis by Market Taxonomy
    • 19.6.2. Value & Analysis and Forecast by Market Taxonomy, 2024-2031
      • 19.6.2.1. By Storage Architecture
      • 19.6.2.2. By Offering
      • 19.6.2.3. By Storage System
      • 19.6.2.4. By Storage Medium
      • 19.6.2.5. By End-user
  • 19.7. France AI Powered Storage Market Analysis
    • 19.7.1. Value Proportion Analysis by Market Taxonomy
    • 19.7.2. Value & Analysis and Forecast by Market Taxonomy, 2024-2031
      • 19.7.2.1. By Storage Architecture
      • 19.7.2.2. By Offering
      • 19.7.2.3. By Storage System
      • 19.7.2.4. By Storage Medium
      • 19.7.2.5. By End-user
  • 19.8. Italy AI Powered Storage Market Analysis
    • 19.8.1. Value Proportion Analysis by Market Taxonomy
    • 19.8.2. Value & Analysis and Forecast by Market Taxonomy, 2024-2031
      • 19.8.2.1. By Storage Architecture
      • 19.8.2.2. By Offering
      • 19.8.2.3. By Storage System
      • 19.8.2.4. By Storage Medium
      • 19.8.2.5. By End-user
  • 19.9. Russia AI Powered Storage Market Analysis
    • 19.9.1. Value Proportion Analysis by Market Taxonomy
    • 19.9.2. Value & Analysis and Forecast by Market Taxonomy, 2024-2031
      • 19.9.2.1. By Storage Architecture
      • 19.9.2.2. By Offering
      • 19.9.2.3. By Storage System
      • 19.9.2.4. By Storage Medium
      • 19.9.2.5. By End-user
  • 19.10. UK AI Powered Storage Market Analysis
    • 19.10.1. Value Proportion Analysis by Market Taxonomy
    • 19.10.2. Value & Analysis and Forecast by Market Taxonomy, 2024-2031
      • 19.10.2.1. By Storage Architecture
      • 19.10.2.2. By Offering
      • 19.10.2.3. By Storage System
      • 19.10.2.4. By Storage Medium
      • 19.10.2.5. By End-user
  • 19.11. China AI Powered Storage Market Analysis
    • 19.11.1. Value Proportion Analysis by Market Taxonomy
    • 19.11.2. Value & Analysis and Forecast by Market Taxonomy, 2024-2031
      • 19.11.2.1. By Storage Architecture
      • 19.11.2.2. By Offering
      • 19.11.2.3. By Storage System
      • 19.11.2.4. By Storage Medium
      • 19.11.2.5. By End-user
  • 19.12. Japan AI Powered Storage Market Analysis
    • 19.12.1. Value Proportion Analysis by Market Taxonomy
    • 19.12.2. Value & Analysis and Forecast by Market Taxonomy, 2024-2031
      • 19.12.2.1. By Storage Architecture
      • 19.12.2.2. By Offering
      • 19.12.2.3. By Storage System
      • 19.12.2.4. By Storage Medium
      • 19.12.2.5. By End-user
  • 19.13. South Korea AI Powered Storage Market Analysis
    • 19.13.1. Value Proportion Analysis by Market Taxonomy
    • 19.13.2. Value & Analysis and Forecast by Market Taxonomy, 2024-2031
      • 19.13.2.1. By Storage Architecture
      • 19.13.2.2. By Offering
      • 19.13.2.3. By Storage System
      • 19.13.2.4. By Storage Medium
      • 19.13.2.5. By End-user
  • 19.14. GCC Countries AI Powered Storage Market Analysis
    • 19.14.1. Value Proportion Analysis by Market Taxonomy
    • 19.14.2. Value & Analysis and Forecast by Market Taxonomy, 2024-2031
      • 19.14.2.1. By Storage Architecture
      • 19.14.2.2. By Offering
      • 19.14.2.3. By Storage System
      • 19.14.2.4. By Storage Medium
      • 19.14.2.5. By End-user
  • 19.15. South Africa AI Powered Storage Market Analysis
    • 19.15.1. Value Proportion Analysis by Market Taxonomy
    • 19.15.2. Value & Analysis and Forecast by Market Taxonomy, 2024-2031
      • 19.15.2.1. By Storage Architecture
      • 19.15.2.2. By Offering
      • 19.15.2.3. By Storage System
      • 19.15.2.4. By Storage Medium
      • 19.15.2.5. By End-user
  • 19.16. Turkey AI Powered Storage Market Analysis
    • 19.16.1. Value Proportion Analysis by Market Taxonomy
    • 19.16.2. Value & Analysis and Forecast by Market Taxonomy, 2024-2031
      • 19.16.2.1. By Storage Architecture
      • 19.16.2.2. By Offering
      • 19.16.2.3. By Storage System
      • 19.16.2.4. By Storage Medium
      • 19.16.2.5. By End-user
    • 19.16.3. Competition Landscape and Player Concentration in the Country

20. Market Structure Analysis

  • 20.1. Market Analysis by Tier of Companies
  • 20.2. Market Concentration
  • 20.3. Market Share Analysis of Top Players
  • 20.4. Market Presence Analysis
    • 20.4.1. By Regional footprint of Players
    • 20.4.2. Product footprint by Players

21. Competition Analysis

  • 21.1. Competition Dashboard
  • 21.2. Competition Benchmarking
  • 21.3. Competition Deep Dive
    • 21.3.1. Intel Corporation
      • 21.3.1.1. Overview
      • 21.3.1.2. Product Portfolio
      • 21.3.1.3. Sales Footprint
      • 21.3.1.4. Strategy Overview
    • 21.3.2. NVIDIA Corporation
      • 21.3.2.1. Overview
      • 21.3.2.2. Product Portfolio
      • 21.3.2.3. Sales Footprint
      • 21.3.2.4. Strategy Overview
    • 21.3.3. IBM
      • 21.3.3.1. Overview
      • 21.3.3.2. Product Portfolio
      • 21.3.3.3. Sales Footprint
      • 21.3.3.4. Strategy Overview
    • 21.3.4. Samsung Electronics
      • 21.3.4.1. Overview
      • 21.3.4.2. Product Portfolio
      • 21.3.4.3. Sales Footprint
      • 21.3.4.4. Strategy Overview
    • 21.3.5. Pure Storage
      • 21.3.5.1. Overview
      • 21.3.5.2. Product Portfolio
      • 21.3.5.3. Sales Footprint
      • 21.3.5.4. Strategy Overview
    • 21.3.6. NetApp
      • 21.3.6.1. Overview
      • 21.3.6.2. Product Portfolio
      • 21.3.6.3. Sales Footprint
      • 21.3.6.4. Strategy Overview
    • 21.3.7. Micron Technology
      • 21.3.7.1. Overview
      • 21.3.7.2. Product Portfolio
      • 21.3.7.3. Sales Footprint
      • 21.3.7.4. Strategy Overview
    • 21.3.8. CISCO
      • 21.3.8.1. Overview
      • 21.3.8.2. Product Portfolio
      • 21.3.8.3. Sales Footprint
      • 21.3.8.4. Strategy Overview
    • 21.3.9. Toshiba
      • 21.3.9.1. Overview
      • 21.3.9.2. Product Portfolio
      • 21.3.9.3. Sales Footprint
      • 21.3.9.4. Strategy Overview
    • 21.3.10. Hitachi
      • 21.3.10.1. Overview
      • 21.3.10.2. Product Portfolio
      • 21.3.10.3. Sales Footprint
      • 21.3.10.4. Strategy Overview
    • 21.3.11. Lenovo
      • 21.3.11.1. Overview
      • 21.3.11.2. Product Portfolio
      • 21.3.11.3. Sales Footprint
      • 21.3.11.4. Strategy Overview
    • 21.3.12. Dell
      • 21.3.12.1. Overview
      • 21.3.12.2. Product Portfolio
      • 21.3.12.3. Sales Footprint
      • 21.3.12.4. Strategy Overview
    • 21.3.13. HPE
      • 21.3.13.1. Overview
      • 21.3.13.2. Product Portfolio
      • 21.3.13.3. Sales Footprint
      • 21.3.13.4. Strategy Overview

22. Assumptions and Acronyms Used

23. Research Methodology