How Enterprises Can Rethink Data Management in the AI Era

Enterprise data is growing at an exponential rate, with IDC projecting that global data creation will reach 175 zettabytes by 2025. A significant portion of this data is unstructured—videos, sensor data, and logs—requiring more than just traditional storage solutions. Businesses now seek intelligent storage systems that offer real-time analytics, automated data classification, and built-in cybersecurity measures to ensure data remains both accessible and secure.

As enterprises generate data at an unprecedented scale, traditional storage and management strategies are no longer sufficient. Sanjay Agrawal, CTO and Head Presales at Hitachi Vantara, India and SAARC, shares how the company is pioneering data management with AI-driven storage solutions, business-centric SLAs, and sustainability-focused innovations.

Why Traditional Storage Strategies Are No Longer Sufficient

The data landscape has evolved dramatically in the past decade. Enterprises now generate diverse forms of data—human, business, and machine data—that require a sophisticated approach to storage and management. While structured business data was once the primary focus, the exponential rise in human and machine-generated data has shifted priorities.

"Our data strategy today is vastly different from a decade ago. Enterprises are no longer just managing structured business data in terabytes. Now, we are dealing with petabyte-scale human and machine data, requiring a shift from operational management to innovation." Sanjay adds.

Historically, enterprises managed structured data (databases, transactions) in centralized storage systems. However, the shift towards AI-driven applications, IoT data streams, and real-time analytics demands a new approach. Key challenges include:

· Data Fragmentation: Enterprises now operate across on-premises, cloud, and hybrid environments, making data silos a growing issue.

· Cyber Threats: With ransomware attacks increasing by 66% YoY (Sophos, 2023), data protection strategies need to evolve beyond backup solutions.

· Scalability Bottlenecks: AI and analytics workloads require low-latency, high-throughput storage architectures to perform optimally.

Hitachi Vantara addresses this transformation with a unified platform that supports real-time business applications and large-scale data analytics. By streamlining petabyte-scale data management, enterprises can focus on innovation rather than operational complexities.

Agrawal emphasizes the need for a unified approach that can handle both structured and unstructured data:

"By bringing petabyte-scale data management onto a single common underlying storage platform, we enable enterprises to concentrate on extracting insights rather than just managing different siloed storage infrastructure for different types of data."

The storage market is crowded with vendors offering various go-to-market strategies, but Hitachi Vantara differentiates itself through a customer-centric approach. Instead of focusing solely on configurations, the company prioritizes architectural resilience, ensuring enterprise-grade SLAs across all storage solutions, including mid-range offerings.

By integrating high responsiveness, scalability, and reliability into mission-critical workloads, Hitachi Vantara provides enterprise-level assurance, making its solutions the preferred choice for organizations seeking long-term data reliability.

Moving from Management to Automation

Artificial Intelligence (AI) is reshaping the way storage solutions function. AI-driven automation eliminates the need for manual interventions in storage provisioning and optimization.

• AI helps dynamically provisions storage from an underutilized storage array instead of picking up the capacity from the one that was manually set at the time of implementation but over time became overutilized, in real time, optimizing space and performance across storage arrays in data center.
• Advanced AI fingerprinting based approach helps populate new data in data catalog in near real-time , and that is essential for enterprises building data lakes in digital era.

These intelligent enhancements ensure that Hitachi Vantara’s storage solutions are efficient, responsive, and aligned with evolving enterprise demands.

To address these challenges, enterprises are shifting towards AI-powered storage platforms that can:

· Dynamically allocate resources: Using predictive analytics, AI optimizes storage utilization in real time, reducing wasted capacity.

· Automate data classification: AI-driven metadata tagging enables rapid search and retrieval, critical for data lakes and real-time analytics.

· Enhance cybersecurity: Immutable snapshots and AI-based anomaly detection help detect ransomware attacks before they encrypt critical files.

Agrawal highlights how AI is transforming storage provisioning:

"Earlier, storage provisioning required manual configuration. Today, AI dynamically scans all available storage arrays in real-time, allocating space based on actual availability. This optimizes both performance and efficiency, reducing human intervention."

Comparing AI-Powered Storage with Legacy Systems

Why SLAs Are Now Business-Centric

Beyond performance metrics like IOPS (Input/Output Operations Per Second) and latency, enterprises now look for business-level SLAs that guarantee:

· 100% data availability (with financial compensation for downtime)

· Data reduction guarantees to optimize storage footprint without hidden conditions

· Cyber recovery warranties, ensuring businesses can recover from ransomware without relying solely on cyber insurance

According to Agrawal, these commitments go beyond technical assurances: “Customers today demand business-level guarantees. If a system fails, they don’t just need a warranty—they need to be compensated. Our approach technology ensures high-availability guarantees and sub-100-microsecond response times, along with business-level SLAs that protect customer interests." Our enterprise systems can tolerate more than 2 controller failures and we provide 'eight nines' uptime

Industries with mission-critical workloads, such as banking, telecom, and manufacturing, increasingly rely on Hitachi Vantara’s technology. However, the company is also expanding into mid-range and tier-two markets, offering unmatched SLAs that extend beyond technical performance.

Hitachi Vantara’s recovery warrantee also ensures business continuity in an unlikely event of a ransomware attack. The company takes full responsibility for data recovery with easy and early availability of the data to the business users after the attack, making its offering a proactive, business-first approach to data protection.

Sustainability in Data Storage: The Next Big Focus in Enterprise Storage

With data centers consuming nearly 3% of global electricity (IEA, 2023), enterprises are increasingly prioritizing energy efficiency in storage procurement. The industry is shifting towards:

· Storage systems with AI-powered workload balancing, reducing energy consumption

· Data deduplication and compression, minimizing redundant storage needs

· Lifecycle extension strategies, allowing hardware upgrades instead of full replacements

Agrawal highlights Hitachi’s approach to sustainability:

"Sustainability must be considered across the entire storage lifecycle—from manufacturing to retirement. Our systems are produced with 38% higher efficiency, leverage guaranteed data reduction, and reduce CO₂ emissions by optimizing power consumption."

A key benchmark emerging in the industry is IOPS-per-watt, helping enterprises evaluate storage solutions based on energy efficiency.

The Future of Enterprise Data Management

As enterprises navigate the complexities of AI-driven workloads, cybersecurity threats, and sustainability requirements, data storage is no longer just about capacity—it’s about intelligence, automation, and resilience. Organizations investing in AI-powered, cyber-resilient, and energy-efficient storage architectures will be better positioned to handle future data challenges.