Amid the rapid adoption of AI, data readiness remains a significant challenge. Gartner reports that 63% of organizations either lack or are unsure about having proper data management practices to support AI. 

Entering 2025–2026, as enterprises begin building local AI and private AI infrastructures, these limitations become even more apparent. Many AI initiatives are hindered not by data or models, but by storage systems not designed for modern AI workloads. This is where Huawei AI Storage plays a pivotal role as a strategic data foundation, enabling AI to run faster, more stable, and more efficiently. 

  

What is AI Storage and Why is it Critical for Enterprise AI? 

AI Storage is a data storage approach specifically designed to meet the unique requirements of AI workloads, from AI training to inferencing. Unlike traditional storage optimized for transactions or archiving, AI Storage focuses on large-scale parallel data access, low latency, and high throughput—key characteristics required by modern AI models, big data analytics, and HPC workloads. 

In enterprise AI contexts, AI Storage serves as the data foundation that determines how fast and reliably AI processes can run. Without AI-ready storage, the performance of compute and models cannot be fully leveraged. Therefore, AI Storage is a strategic element in building scalable, efficient, and secure AI data infrastructure. 

  

Why AI Needs Storage Different from Conventional Systems 

AI workloads demand data handling that is very different from traditional enterprise applications. Training and inferencing involve processing large-scale data simultaneously and continuously, making storage a critical part of the AI pipeline—not just a supporting layer. 

When storage is not designed for these characteristics, performance bottlenecks are inevitable. Training slows down, inferencing becomes inconsistent, and infrastructure efficiency drops. This explains why many AI initiatives fail to achieve optimal results, even with advanced compute and models. 

  

The Rise of Local AI and Private AI Infrastructure in Enterprises

The growth of local AI and private AI infrastructure marks a shift in how enterprises build and operate AI. AI is now deployed closer to data sources, integrated with internal systems, and fully controlled by the organization. 

This approach is widely adopted by enterprises in the finance and manufacturing sectors, where data control and regulatory compliance are top priorities. In these scenarios, data infrastructure readiness becomes a determining factor for the successful, sustainable implementation of AI. 

  

 Huawei AI-Native Storage for Modern AI Infrastructure

To meet these needs, Huawei AI Storage was developed as a solution designed specifically for AI from the ground up. It is not an adaptation of legacy systems, but a data foundation aligned with how modern AI works. 

With AI-native architecture and intelligent data management, Huawei AI Storage helps enterprises eliminate data bottlenecks in the AI pipeline. This ensures faster, more stable training and inferencing, while providing a storage foundation ready to support AI development in enterprise environments. 

  

Performance, Reliability, and Energy Efficiency for AI Workloads

Enterprise-scale AI workloads require more than high performance alone. Continuous training and inferencing demand storage capable of maintaining consistent and reliable performance. Unstable storage reduces AI pipeline efficiency and makes AI outcomes difficult to sustain. 

Huawei AI Storage addresses these challenges with a combination of stable high performance, enterprise-grade reliability, and energy-efficient design. Its AI-native architecture and intelligent data acceleration reduce data bottlenecks while minimizing data center power consumption, providing a foundation ready for long-term AI workloads. 

  

OceanStor A800 and OceanStor A600: AI Storage Solutions for Diverse Business Needs

Huawei offers AI Storage solutions tailored to the scale and requirements of enterprise AI. OceanStor A800 and OceanStor A600 are designed to support a wide range of AI scenarios by accelerating the end-to-end AI workflow, from data ingestion and training to inference. These solutions are applicable across multiple industries, including financial services, healthcare, intelligent computing centers, scientific research, and autonomous driving platforms. This approach allows organizations to build AI infrastructure progressively without compromising performance or efficiency. 

OceanStor A800

OceanStor A800 is designed for large-scale AI clusters and hig-performance computing environments. It delivers high performance for intensive AI data processing, training, and inference workloads through an AI-native architecture and intelligent data acceleration. Support for emerging data types, such as vector data and multi-level KV cache, helps reduce inference latency while improving overall efficiency, making it ideal for AI labs, research centers, and enterprises without infrastructure bottlenecks.  

 

OceanStor A600  

OceanStor A600 combines high performance, capacity, AI-native capabilities, and energy efficiency to support most small and medium-scale enterprise AI workloads. It offers flexible deployment options for enterprise data centers, on-premises environments, and private AI infrastructures, enabling stable and efficient AI operations. 

 

Advantages of Huawei AI Storage Over Conventional AI-Ready Storage

Huawei AI Storage provides a storage approach specifically designed for AI, unlike conventional storage merely adapted for AI workloads. It delivers not only high performance, but also stability, energy efficiency, and intelligent data management, enabling enterprises to build scalable and sustainable AI platforms. 

Key advantages of Huawei AI Storage: 

  • AI-Native Architecture: Built from the ground up for AI workloads, enabling large-scale parallel data access and fast processing without bottlenecks. 
  • Intelligent Data Acceleration: Speeds up data flow across the AI pipeline, from ingestion to training and inferencing, delivering faster insights. 
  • Ultra-High Performance: Supports large-scale AI training, HPC, LLMs, computer vision, and enterprise analytics with consistent performance. 
  • High Energy Efficiency: Reduces power consumption without compromising performance, supporting data center sustainability. 
  • Smart Management System: Simplifies monitoring, resource optimization, and AI data lifecycle management centrally. 
  • Flexible Deployment: Suitable for central data centers, AI labs, on-premises, or private AI infrastructures. 
  • Global Trust and Local Implementation: Huawei as a global principal and Virtus as the official distributor in Indonesia ensure long-term technical and operational support. 

Explore More: Huawei OceanStor Data Storage on Virtus Technology Indonesia 

Build Enterprise AI with the Right Storage Foundation Together with Virtus

Virtus Technology Indonesia, as the official Huawei distributor, is ready to help enterprises deploy Huawei AI Storage safely, quickly, and tailored to their AI needs. End-to-end services—from consulting and architecture design to deployment and local support—ensure companies can maximize AI performance and stability sustainably. 

Contact the Virtus team via this link to strengthen your AI data foundation and accelerate AI development efficiently and reliably. 

 

Author: Moyna Farla Tsabitah 

CTI Group Content Writer Intern