AI 파워드 스토리지 시장 - 세계 산업 규모, 점유율, 동향, 기회, 예측 : 제공별, 스토리지 시스템별, 스토리지 아키텍처별, 스토리지 매체별, 최종사용자별, 지역별, 경쟁(2019-2029년)

Global AI Powered Storage Market was valued at USD 3.9 Billion in 2023 and is anticipated to project robust growth in the forecast period with a CAGR of 6.80% through 2029.

AI-powered storage refers to storage solutions that integrate artificial intelligence (AI) technologies to optimize and manage data storage systems more efficiently and intelligently. Traditional storage systems often face challenges such as inefficient data management, difficulty in predicting storage needs, and high operational costs. AI-powered storage addresses these issues by leveraging machine learning algorithms and predictive analytics to automate data management processes, improve storage performance, and enhance scalability. One key aspect of AI-powered storage is predictive analytics, which enables storage systems to anticipate future storage requirements based on historical data patterns, user behavior, and workload characteristics. By analyzing data access patterns and storage utilization trends in real-time, AI algorithms can dynamically allocate storage resources, optimize data placement, and ensure that critical data is readily accessible while less frequently accessed data is stored cost-effectively. AI-powered storage solutions enhance data security and reliability by proactively identifying and mitigating potential risks and vulnerabilities. AI algorithms can detect anomalies in data access patterns or storage behavior, indicating potential security breaches or performance issues before they escalate. This proactive approach minimizes downtime and ensures continuous availability of data, critical for organizations operating in fast-paced and data-intensive environments. AI-powered storage contributes to operational efficiency by automating routine tasks such as data tiering, backup and recovery processes, and capacity planning. This automation reduces manual intervention, lowers operational costs, and allows IT teams to focus on strategic initiatives rather than day-to-day maintenance tasks. Additionally, AI-powered storage facilitates seamless integration with cloud environments and hybrid IT architectures, enabling organizations to leverage the scalability and flexibility of cloud storage while maintaining control over sensitive data on-premises. The market for AI-powered storage is expected to grow rapidly as organizations increasingly prioritize data-driven decision-making, scalability, and operational efficiency. With advancements in AI technologies and increasing volumes of data generated across industries, the demand for intelligent storage solutions that can manage and derive insights from large datasets will continue to rise. As businesses seek to extract maximum value from their data assets while managing storage costs and complexity, AI-powered storage solutions are poised to play a pivotal role in shaping the future of data management and storage infrastructure..

Key Market Drivers

Advancements in Artificial Intelligence and Machine Learning Technologies

Another significant driver accelerating the AI Powered Storage Market is the rapid advancements in artificial intelligence (AI) and machine learning (ML) technologies. AI-powered storage solutions integrate these technologies to automate and optimize various aspects of data management, storage provisioning, and performance tuning. Machine learning algorithms enable storage systems to learn from historical data patterns, predict future storage needs, and adapt dynamically to changing workload demands. This predictive capability is particularly valuable in dynamic environments where data access patterns fluctuate, such as e-commerce platforms during peak shopping seasons or healthcare systems handling patient data.

Furthermore, AI-powered storage enhances data security by continuously monitoring for anomalous behavior or potential threats, detecting and responding to security incidents in real-time. This proactive approach is essential in safeguarding sensitive information from increasingly sophisticated cyber threats and ensuring compliance with data protection regulations.

Moreover, AI-powered storage solutions are pivotal in optimizing cloud storage environments and hybrid IT architectures. These solutions facilitate seamless data migration, replication, and synchronization between on-premises infrastructure and cloud platforms while ensuring data integrity and availability. By automating data management tasks and optimizing resource allocation across hybrid environments, organizations can achieve greater agility, scalability, and cost-efficiency in their IT operations.

Increasing Focus on Operational Efficiency and Cost Optimization

A key driver fostering the adoption of AI-powered storage solutions is the growing emphasis on operational efficiency and cost optimization within organizations. Traditional storage infrastructures often struggle with inefficiencies such as overprovisioning, underutilization of storage resources, and high operational overheads associated with manual management tasks. AI-powered storage addresses these challenges by automating routine operations, optimizing storage utilization, and improving overall system performance.

Furthermore, AI-powered storage solutions enable predictive maintenance capabilities by analyzing performance metrics and identifying potential issues before they escalate into costly downtime events. This proactive maintenance approach minimizes service disruptions, enhances system reliability, and extends the lifespan of storage hardware, thereby reducing maintenance costs and enhancing overall IT infrastructure resilience.

Moreover, AI-powered storage contributes to cost savings through efficient data compression, deduplication, and data lifecycle management strategies. These capabilities help organizations optimize storage capacity, reduce storage footprint, and lower overall storage costs without compromising data accessibility or performance. Additionally, by facilitating centralized management and monitoring of storage resources across distributed environments, AI-powered storage solutions enable IT teams to streamline operations, improve resource allocation, and achieve greater operational efficiency.

Key Market Challenges

Complexity of Implementation and Integration

Another significant challenge in the AI Powered Storage Market is the complexity of implementing and integrating AI-powered storage solutions within existing IT infrastructures. Organizations often operate heterogeneous IT environments comprising legacy systems, on-premises data centers, and various cloud platforms. Integrating AI-powered storage solutions seamlessly across these diverse environments requires overcoming compatibility issues, data migration complexities, and ensuring interoperability and performance optimization. Legacy systems may lack support for modern AI technologies or standardized APIs, complicating data extraction, and analysis processes. Moreover, data migration projects entail significant resource allocation, downtime risks, and adherence to data residency and compliance requirements. Organizations must invest in skilled IT personnel, conduct thorough planning, and deploy robust change management practices to minimize disruptions, ensure data integrity, and maximize the benefits of AI-powered storage deployments. Furthermore, integrating AI-powered storage solutions with existing cybersecurity measures and incident response protocols is essential to mitigating security risks and maintaining data confidentiality and availability. By addressing the challenges of implementation and integration, organizations can unlock the transformative potential of AI-powered storage solutions to enhance operational efficiency, drive innovation, and achieve sustainable growth in a data-driven digital economy.

Key Market Trends

AI-Driven Automation and Intelligent Data Management

Another key trend shaping the AI Powered Storage Market is the evolution towards AI-driven automation and intelligent data management capabilities. AI-powered storage solutions utilize machine learning algorithms to automate routine data management tasks, optimize storage resource allocation, and enhance data lifecycle management processes. These technologies enable predictive analytics for capacity planning, data tiering, and performance optimization based on real-time data insights and workload patterns. Organizations leverage AI-driven automation to streamline storage provisioning, data migration, and disaster recovery operations, reducing operational complexities and minimizing human intervention. Furthermore, intelligent data management capabilities empower organizations to enforce data governance policies, ensure regulatory compliance, and mitigate security risks proactively. As businesses continue to embrace digital transformation initiatives and prioritize data-driven decision-making, the demand for AI-powered storage solutions with advanced automation and intelligent data management functionalities is expected to grow. This trend underscores the pivotal role of AI in transforming storage infrastructures into agile, scalable, and intelligent platforms capable of supporting dynamic business requirements in a data-centric environment.

Hybrid and Multi-cloud Optimization Strategies

A significant trend influencing the AI Powered Storage Market is the adoption of hybrid and multi-cloud optimization strategies. Organizations increasingly leverage multiple cloud service providers (CSPs) and hybrid IT architectures to optimize cost, performance, and scalability while maintaining flexibility and data sovereignty. AI-powered storage solutions play a crucial role in facilitating seamless data migration, replication, and synchronization across hybrid and multi-cloud environments. These solutions employ AI algorithms to automate workload placement, optimize data transfer speeds, and ensure data consistency and accessibility across distributed cloud platforms. Moreover, AI-powered storage enables organizations to implement intelligent data placement strategies based on workload requirements, compliance policies, and cost considerations. By optimizing hybrid and multi-cloud deployments, businesses can achieve greater operational agility, scalability, and resilience, effectively managing fluctuating workloads and optimizing IT resource utilization. This trend reflects a strategic shift towards leveraging AI-powered storage solutions as integral components of hybrid IT strategies, enabling organizations to harness the benefits of cloud computing while maintaining control over critical data assets and enhancing overall business continuity and competitiveness.

Segmental Insights

End User Insights

In 2023, the Banking, Financial Services, and Insurance (BFSI) sector emerged as the dominant segment in the AI Powered Storage Market and is projected to maintain its leadership position during the forecast period. The BFSI sector has been at the forefront of adopting AI-powered storage solutions to address critical business challenges, including data management, regulatory compliance, cybersecurity, and customer experience enhancement. AI-powered storage technologies enable BFSI organizations to efficiently manage and analyze vast amounts of transactional data, customer information, and financial records in real-time. These solutions leverage machine learning algorithms to automate data processing, detect fraudulent activities, and optimize risk management strategies, thereby enhancing operational efficiency and decision-making capabilities. Moreover, in a highly regulated industry landscape, AI-powered storage supports compliance with stringent data protection regulations such as GDPR and PCI DSS by implementing robust encryption, access controls, and data governance frameworks. As BFSI institutions continue to prioritize digital transformation initiatives and seek competitive differentiation through data-driven insights and operational agility, the demand for AI-powered storage solutions is expected to grow. These solutions empower BFSI organizations to harness the power of AI and advanced analytics to drive innovation, mitigate risks, and deliver personalized services that meet evolving customer expectations. Furthermore, the ongoing expansion of digital banking services, the rise of fintech innovations, and the increasing adoption of cloud computing and hybrid IT architectures further underscore the significance of AI-powered storage in enabling BFSI enterprises to achieve scalability, resilience, and regulatory compliance while maintaining data security and operational continuity.

Offering Insights

In 2023, the Software segment emerged as the dominant offering in the AI Powered Storage Market and is expected to maintain its leadership position during the forecast period. Software solutions play a pivotal role in AI-powered storage environments by enabling advanced functionalities such as data analytics, machine learning algorithms, and predictive analytics. These software solutions are essential for optimizing storage resource allocation, automating data management tasks, and extracting actionable insights from large datasets in real-time. AI-powered storage software leverages sophisticated algorithms to analyze data patterns, predict storage requirements, and enhance data accessibility and security. Furthermore, AI-driven software solutions facilitate intelligent data governance, ensuring compliance with regulatory frameworks and enabling organizations to enforce data privacy policies effectively. As businesses across various industries increasingly rely on data-driven decision-making and digital transformation initiatives, the demand for AI-powered storage software is expected to grow. These solutions empower organizations to streamline operations, improve business agility, and achieve competitive advantages by harnessing the full potential of AI technologies for data management and storage optimization. Moreover, as AI continues to evolve and integrate with storage architectures and systems, the software segment of the AI Powered Storage Market will continue to innovate, offering scalable, efficient, and intelligent solutions that meet the complex storage needs of modern enterprises. This trend underscores the pivotal role of AI-powered storage software in driving innovation, enhancing operational efficiency, and supporting digital transformation strategies across industries globally

Regional Insights

In 2023, North America emerged as the dominant region in the AI Powered Storage Market and is anticipated to maintain its leadership position throughout the forecast period. North America's dominance can be attributed to several key factors driving the adoption of AI-powered storage solutions across various industries. The region boasts a highly developed IT infrastructure, significant investments in AI research and development, and a strong presence of leading technology companies specializing in storage and data analytics. North American enterprises are early adopters of advanced technologies, including AI and machine learning, to gain competitive advantages through enhanced data management, operational efficiency, and innovation. Industries such as BFSI (Banking, Financial Services, and Insurance), healthcare, retail, and manufacturing in North America are leveraging AI-powered storage solutions to optimize business processes, improve customer experiences, and mitigate operational risks. Favorable government policies and initiatives promoting digital transformation and AI adoption further bolster the growth of the AI Powered Storage Market in North America. These policies encourage investment in AI technologies and support the development of AI ecosystems conducive to innovation and entrepreneurship. The region's proactive approach to cybersecurity and data privacy regulations enhances trust and confidence in AI-powered storage solutions, particularly among industries handling sensitive information. As AI continues to evolve and integrate with storage architectures and systems, North America remains at the forefront of driving technological advancements and shaping the future of AI-powered storage solutions globally. The region's leadership in AI innovation, coupled with its robust market demand and supportive ecosystem, positions North America as a pivotal hub for AI Powered Storage Market growth and development in the years ahead.

Key Market Players

• Intel Corporation
• NVIDIA Corporation
• IBM Corporation
• Samsung Electronics Co., Ltd
• Pure Storage, Inc
• NetApp, Inc
• Micron Technology, Inc.
• Cisco Systems, Inc
• Toshiba Corporation
• Hitachi, Ltd.

Report Scope:

In this report, the Global AI Powered Storage Market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:

AI Powered Storage Market, By Offerings:

• Hardware
• Software

AI Powered Storage Market, By Storage System:

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

AI Powered Storage Market, By Storage Architecture:

• File- & Object-Based Storage
• Object Storage

AI Powered Storage Market, By Storage Medium:

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

AI Powered Storage Market, By End-User:

• BFSI
• Healthcare
• Media & Entertainment
• Retail
• Manufacturing
• Telecommunication

AI Powered Storage Market, By Region:

• North America
  • United States
  • Canada
  • Mexico
• Asia-Pacific
  • China
  • India
  • Japan
  • South Korea
  • Indonesia
• Europe
  • Germany
  • United Kingdom
  • France
  • Russia
  • Spain
• South America
  • Brazil
  • Argentina
• Middle East & Africa
  • Saudi Arabia
  • South Africa
  • Egypt
  • UAE
  • Israel

Competitive Landscape

Company Profiles: Detailed analysis of the major companies presents in the Global AI Powered Storage Market.

Available Customizations:

Global AI Powered Storage Market report with the given market data, TechSci Research offers customizations according to a company's specific needs. The following customization options are available for the report:

Company Information

• Detailed analysis and profiling of additional market players (up to five).

Table of Contents

1. Product Overview

• 1.1. Market Definition
• 1.2. Scope of the Market
• 1.3. Markets Covered
• 1.4. Years Considered for Study
• 1.5. Key Market Segmentations

2. Research Methodology

• 2.1. Objective of the Study
• 2.2. Baseline Methodology
• 2.3. Key Industry Partners
• 2.4. Major Association and Secondary Sources
• 2.5. Forecasting Methodology
• 2.6. Data Triangulation & Validation
• 2.7. Assumptions and Limitations

3. Executive Summary

4. Voice of Customers

5. Global AI Powered Storage Market Outlook

• 5.1. Market Size & Forecast
  • 5.1.1. By Value
• 5.2. Market Share & Forecast
  • 5.2.1. By Offerings (Hardware, Software)
  • 5.2.2. By Storage System (Direct-attached Storage (DAS), Network-attached Storage (NAS), Storage Area Network (SAN))
  • 5.2.3. By Storage Architecture (File- & Object-Based Storage, Object Storage)
  • 5.2.4. By Storage Medium (Hard Disk Drive (HDD), Solid State Drive (SSD))
  • 5.2.5. By End-User (BFSI, Healthcare, Media & Entertainment, Retail, Manufacturing, Telecommunication)
  • 5.2.6. By Region
• 5.3. By Company (2023)
• 5.4. Market Map

6. North America AI Powered Storage Market Outlook

• 6.1. Market Size & Forecast
  • 6.1.1. By Value
• 6.2. Market Share & Forecast
  • 6.2.1. By Offerings
  • 6.2.2. By Storage System
  • 6.2.3. By Storage Architecture
  • 6.2.4. By Storage Medium
  • 6.2.5. By End-User
  • 6.2.6. By Country
• 6.3. North America: Country Analysis
  • 6.3.1. United States AI Powered Storage Market Outlook
    • 6.3.1.1. Market Size & Forecast
      • 6.3.1.1.1. By Value
    • 6.3.1.2. Market Share & Forecast
      • 6.3.1.2.1. By Offerings
      • 6.3.1.2.2. By Storage System
      • 6.3.1.2.3. By Storage Architecture
      • 6.3.1.2.4. By Storage Medium
      • 6.3.1.2.5. By End-User
  • 6.3.2. Canada AI Powered Storage Market Outlook
    • 6.3.2.1. Market Size & Forecast
      • 6.3.2.1.1. By Value
    • 6.3.2.2. Market Share & Forecast
      • 6.3.2.2.1. By Offerings
      • 6.3.2.2.2. By Storage System
      • 6.3.2.2.3. By Storage Architecture
      • 6.3.2.2.4. By Storage Medium
      • 6.3.2.2.5. By End-User
  • 6.3.3. Mexico AI Powered Storage Market Outlook
    • 6.3.3.1. Market Size & Forecast
      • 6.3.3.1.1. By Value
    • 6.3.3.2. Market Share & Forecast
      • 6.3.3.2.1. By Offerings
      • 6.3.3.2.2. By Storage System
      • 6.3.3.2.3. By Storage Architecture
      • 6.3.3.2.4. By Storage Medium
      • 6.3.3.2.5. By End-User

7. Asia-Pacific AI Powered Storage Market Outlook

• 7.1. Market Size & Forecast
  • 7.1.1. By Value
• 7.2. Market Share & Forecast
  • 7.2.1. By Offerings
  • 7.2.2. By Storage System
  • 7.2.3. By Storage Architecture
  • 7.2.4. By Storage Medium
  • 7.2.5. By End-User
  • 7.2.6. By Country
• 7.3. Asia-Pacific: Country Analysis
  • 7.3.1. China AI Powered Storage Market Outlook
    • 7.3.1.1. Market Size & Forecast
      • 7.3.1.1.1. By Value
    • 7.3.1.2. Market Share & Forecast
      • 7.3.1.2.1. By Offerings
      • 7.3.1.2.2. By Storage System
      • 7.3.1.2.3. By Storage Architecture
      • 7.3.1.2.4. By Storage Medium
      • 7.3.1.2.5. By End-User
  • 7.3.2. India AI Powered Storage Market Outlook
    • 7.3.2.1. Market Size & Forecast
      • 7.3.2.1.1. By Value
    • 7.3.2.2. Market Share & Forecast
      • 7.3.2.2.1. By Offerings
      • 7.3.2.2.2. By Storage System
      • 7.3.2.2.3. By Storage Architecture
      • 7.3.2.2.4. By Storage Medium
      • 7.3.2.2.5. By End-User
  • 7.3.3. Japan AI Powered Storage Market Outlook
    • 7.3.3.1. Market Size & Forecast
      • 7.3.3.1.1. By Value
    • 7.3.3.2. Market Share & Forecast
      • 7.3.3.2.1. By Offerings
      • 7.3.3.2.2. By Storage System
      • 7.3.3.2.3. By Storage Architecture
      • 7.3.3.2.4. By Storage Medium
      • 7.3.3.2.5. By End-User
  • 7.3.4. South Korea AI Powered Storage Market Outlook
    • 7.3.4.1. Market Size & Forecast
      • 7.3.4.1.1. By Value
    • 7.3.4.2. Market Share & Forecast
      • 7.3.4.2.1. By Offerings
      • 7.3.4.2.2. By Storage System
      • 7.3.4.2.3. By Storage Architecture
      • 7.3.4.2.4. By Storage Medium
      • 7.3.4.2.5. By End-User
  • 7.3.5. Indonesia AI Powered Storage Market Outlook
    • 7.3.5.1. Market Size & Forecast
      • 7.3.5.1.1. By Value
    • 7.3.5.2. Market Share & Forecast
      • 7.3.5.2.1. By Offerings
      • 7.3.5.2.2. By Storage System
      • 7.3.5.2.3. By Storage Architecture
      • 7.3.5.2.4. By Storage Medium
      • 7.3.5.2.5. By End-User

8. Europe AI Powered Storage Market Outlook

• 8.1. Market Size & Forecast
  • 8.1.1. By Value
• 8.2. Market Share & Forecast
  • 8.2.1. By Offerings
  • 8.2.2. By Storage System
  • 8.2.3. By Storage Architecture
  • 8.2.4. By Storage Medium
  • 8.2.5. By End-User
  • 8.2.6. By Country
• 8.3. Europe: Country Analysis
  • 8.3.1. Germany AI Powered Storage Market Outlook
    • 8.3.1.1. Market Size & Forecast
      • 8.3.1.1.1. By Value
    • 8.3.1.2. Market Share & Forecast
      • 8.3.1.2.1. By Offerings
      • 8.3.1.2.2. By Storage System
      • 8.3.1.2.3. By Storage Architecture
      • 8.3.1.2.4. By Storage Medium
      • 8.3.1.2.5. By End-User
  • 8.3.2. United Kingdom AI Powered Storage Market Outlook
    • 8.3.2.1. Market Size & Forecast
      • 8.3.2.1.1. By Value
    • 8.3.2.2. Market Share & Forecast
      • 8.3.2.2.1. By Offerings
      • 8.3.2.2.2. By Storage System
      • 8.3.2.2.3. By Storage Architecture
      • 8.3.2.2.4. By Storage Medium
      • 8.3.2.2.5. By End-User
  • 8.3.3. France AI Powered Storage Market Outlook
    • 8.3.3.1. Market Size & Forecast
      • 8.3.3.1.1. By Value
    • 8.3.3.2. Market Share & Forecast
      • 8.3.3.2.1. By Offerings
      • 8.3.3.2.2. By Storage System
      • 8.3.3.2.3. By Storage Architecture
      • 8.3.3.2.4. By Storage Medium
      • 8.3.3.2.5. By End-User
  • 8.3.4. Russia AI Powered Storage Market Outlook
    • 8.3.4.1. Market Size & Forecast
      • 8.3.4.1.1. By Value
    • 8.3.4.2. Market Share & Forecast
      • 8.3.4.2.1. By Offerings
      • 8.3.4.2.2. By Storage System
      • 8.3.4.2.3. By Storage Architecture
      • 8.3.4.2.4. By Storage Medium
      • 8.3.4.2.5. By End-User
  • 8.3.5. Spain AI Powered Storage Market Outlook
    • 8.3.5.1. Market Size & Forecast
      • 8.3.5.1.1. By Value
    • 8.3.5.2. Market Share & Forecast
      • 8.3.5.2.1. By Offerings
      • 8.3.5.2.2. By Storage System
      • 8.3.5.2.3. By Storage Architecture
      • 8.3.5.2.4. By Storage Medium
      • 8.3.5.2.5. By End-User

9. South America AI Powered Storage Market Outlook

• 9.1. Market Size & Forecast
  • 9.1.1. By Value
• 9.2. Market Share & Forecast
  • 9.2.1. By Offerings
  • 9.2.2. By Storage System
  • 9.2.3. By Storage Architecture
  • 9.2.4. By Storage Medium
  • 9.2.5. By End-User
  • 9.2.6. By Country
• 9.3. South America: Country Analysis
  • 9.3.1. Brazil AI Powered Storage Market Outlook
    • 9.3.1.1. Market Size & Forecast
      • 9.3.1.1.1. By Value
    • 9.3.1.2. Market Share & Forecast
      • 9.3.1.2.1. By Offerings
      • 9.3.1.2.2. By Storage System
      • 9.3.1.2.3. By Storage Architecture
      • 9.3.1.2.4. By Storage Medium
      • 9.3.1.2.5. By End-User
  • 9.3.2. Argentina AI Powered Storage Market Outlook
    • 9.3.2.1. Market Size & Forecast
      • 9.3.2.1.1. By Value
    • 9.3.2.2. Market Share & Forecast
      • 9.3.2.2.1. By Offerings
      • 9.3.2.2.2. By Storage System
      • 9.3.2.2.3. By Storage Architecture
      • 9.3.2.2.4. By Storage Medium
      • 9.3.2.2.5. By End-User

10. Middle East & Africa AI Powered Storage Market Outlook

• 10.1. Market Size & Forecast
  • 10.1.1. By Value
• 10.2. Market Share & Forecast
  • 10.2.1. By Offerings
  • 10.2.2. By Storage System
  • 10.2.3. By Storage Architecture
  • 10.2.4. By Storage Medium
  • 10.2.5. By End-User
  • 10.2.6. By Country
• 10.3. Middle East & Africa: Country Analysis
  • 10.3.1. Saudi Arabia AI Powered Storage Market Outlook
    • 10.3.1.1. Market Size & Forecast
      • 10.3.1.1.1. By Value
    • 10.3.1.2. Market Share & Forecast
      • 10.3.1.2.1. By Offerings
      • 10.3.1.2.2. By Storage System
      • 10.3.1.2.3. By Storage Architecture
      • 10.3.1.2.4. By Storage Medium
      • 10.3.1.2.5. By End-User
  • 10.3.2. South Africa AI Powered Storage Market Outlook
    • 10.3.2.1. Market Size & Forecast
      • 10.3.2.1.1. By Value
    • 10.3.2.2. Market Share & Forecast
      • 10.3.2.2.1. By Offerings
      • 10.3.2.2.2. By Storage System
      • 10.3.2.2.3. By Storage Architecture
      • 10.3.2.2.4. By Storage Medium
      • 10.3.2.2.5. By End-User
  • 10.3.3. UAE AI Powered Storage Market Outlook
    • 10.3.3.1. Market Size & Forecast
      • 10.3.3.1.1. By Value
    • 10.3.3.2. Market Share & Forecast
      • 10.3.3.2.1. By Offerings
      • 10.3.3.2.2. By Storage System
      • 10.3.3.2.3. By Storage Architecture
      • 10.3.3.2.4. By Storage Medium
      • 10.3.3.2.5. By End-User
  • 10.3.4. Israel AI Powered Storage Market Outlook
    • 10.3.4.1. Market Size & Forecast
      • 10.3.4.1.1. By Value
    • 10.3.4.2. Market Share & Forecast
      • 10.3.4.2.1. By Offerings
      • 10.3.4.2.2. By Storage System
      • 10.3.4.2.3. By Storage Architecture
      • 10.3.4.2.4. By Storage Medium
      • 10.3.4.2.5. By End-User
  • 10.3.5. Egypt AI Powered Storage Market Outlook
    • 10.3.5.1. Market Size & Forecast
      • 10.3.5.1.1. By Value
    • 10.3.5.2. Market Share & Forecast
      • 10.3.5.2.1. By Offerings
      • 10.3.5.2.2. By Storage System
      • 10.3.5.2.3. By Storage Architecture
      • 10.3.5.2.4. By Storage Medium
      • 10.3.5.2.5. By End-User

11. Market Dynamics

• 11.1. Drivers
• 11.2. Challenge

12. Market Trends & Developments

13. Company Profiles

• 13.1. Intel Corporation
  • 13.1.1. Business Overview
  • 13.1.2. Key Revenue and Financials
  • 13.1.3. Recent Developments
  • 13.1.4. Key Personnel
  • 13.1.5. Key Product/Services
• 13.2. NVIDIA Corporation
  • 13.2.1. Business Overview
  • 13.2.2. Key Revenue and Financials
  • 13.2.3. Recent Developments
  • 13.2.4. Key Personnel
  • 13.2.5. Key Product/Services
• 13.3. IBM Corporation
  • 13.3.1. Business Overview
  • 13.3.2. Key Revenue and Financials
  • 13.3.3. Recent Developments
  • 13.3.4. Key Personnel
  • 13.3.5. Key Product/Services
• 13.4. Samsung Electronics Co., Ltd
  • 13.4.1. Business Overview
  • 13.4.2. Key Revenue and Financials
  • 13.4.3. Recent Developments
  • 13.4.4. Key Personnel
  • 13.4.5. Key Product/Services
• 13.5. Pure Storage, Inc
  • 13.5.1. Business Overview
  • 13.5.2. Key Revenue and Financials
  • 13.5.3. Recent Developments
  • 13.5.4. Key Personnel
  • 13.5.5. Key Product/Services
• 13.6. NetApp, Inc
  • 13.6.1. Business Overview
  • 13.6.2. Key Revenue and Financials
  • 13.6.3. Recent Developments
  • 13.6.4. Key Personnel
  • 13.6.5. Key Product/Services
• 13.7. Micron Technology, Inc
  • 13.7.1. Business Overview
  • 13.7.2. Key Revenue and Financials
  • 13.7.3. Recent Developments
  • 13.7.4. Key Personnel
  • 13.7.5. Key Product/Services
• 13.8. Cisco Systems, Inc.
  • 13.8.1. Business Overview
  • 13.8.2. Key Revenue and Financials
  • 13.8.3. Recent Developments
  • 13.8.4. Key Personnel
  • 13.8.5. Key Product/Services
• 13.9. Toshiba Corporation
  • 13.9.1. Business Overview
  • 13.9.2. Key Revenue and Financials
  • 13.9.3. Recent Developments
  • 13.9.4. Key Personnel
  • 13.9.5. Key Product/Services
• 13.10. Hitachi, Ltd
  • 13.10.1. Business Overview
  • 13.10.2. Key Revenue and Financials
  • 13.10.3. Recent Developments
  • 13.10.4. Key Personnel
  • 13.10.5. Key Product/Services

14. Strategic Recommendations

15. About Us & Disclaimer