The Growing Demand for AI-Driven Storage

The growing demand for data center storage is driven by the increasing adoption of artificial intelligence (AI) and machine learning (ML) workloads. According to a survey conducted by Western Digital in partnership with Foundry in February 2025, AI and ML workloads now consume an average of 24% of storage infrastructure. This trend is expected to continue, with the demand for AI-driven storage growing exponentially.

Drivers of Storage Growth

The survey identified several key drivers of storage growth, including:

• AI/ML workloads (68%)
• Expansion of private cloud and hybrid cloud environments (54%)
• High-resolution content (45%)
• Internet of things and edge computing (42%)
• Compliance and data retention policies (39%)

These drivers highlight the increasing importance of AI and ML workloads in driving storage growth. As AI adoption continues to grow, the demand for high-performance storage solutions will only increase.

Priorities and Objectives

When it comes to storage investments, organizations have a range of priorities and objectives. According to the survey, these include:

1. Longevity and durability of devices (90%)
2. Total cost of ownership (TCO) (86%)
3. Energy efficiency and power savings (82%)
4. Compliance with sustainability goals (72%)
5. Availability of trade-in or refurbishment programs (66%)
6. Vendor’s commitment to environmental, social, and governance (ESG) initiatives (65%)
7. Recyclability and circularity of storage components (62%)

These priorities highlight the importance of considering both the short-term and long-term costs associated with storage investments.

Storage Vendor Selection

When it comes to selecting a storage vendor, organizations have a range of priorities. According to the survey, these include:

1. Reliability and durability (highly ranked by all respondents)
2. AI and analytics readiness (47%)
3. Scalability (42%)
4. Energy efficiency and sustainability (74% of enterprise-size organizations)

These priorities highlight the importance of selecting a vendor that can meet the evolving needs of AI and ML workloads.

Growth Comes with Growing Pains

The growth of storage demand is causing major pain points for organizations. According to the survey, the average storage demand growth is 27% over the past year, with 51% of respondents experiencing increases of 25% to 50% or more.

1. Costs associated with storage expansion
2. Meeting AI and analytics performance demands
3. Security and compliance concerns
4. Data access speeds and latency issues
5. Managing unstructured data growth
6. Migration challenges (on-premises to cloud and vice versa)
7. Vendor lock-in or lack of flexibility

These pain points highlight the need for organizations to develop strategies that can address the evolving demands of AI and ML workloads.

Critical Needs and Challenges

The growing demand for AI-driven storage presents several critical needs and challenges. According to the survey, these include:

1. Reliability, scalability, power, cooling, and overall costs
2. Data in the data center is not homogeneous; different applications and data types have varying access requirements
3. The need for a tiered storage approach that is cost-effective and flexible
4. The importance of aligning storage with the specific nature of the workload

These needs and challenges highlight the need for organizations to develop storage strategies that can meet the evolving demands of AI and ML workloads.

The Future of Data Center Storage

The growing demand for AI-driven storage presents several opportunities and challenges. According to the survey, organizations must consider the following:

1. Next-gen storage technologies
2. Deep architectural flexibility
3. The importance of aligning storage with the specific nature of the workload

By considering these factors, organizations can develop storage strategies that can meet the evolving demands of AI and ML workloads.

Conclusion

The growing demand for AI-driven storage presents several opportunities and challenges for organizations. By considering the drivers of storage growth, priorities and objectives, storage vendor selection, growth comes with growing pains, critical needs and challenges, and the future of data center storage, organizations can develop strategies that can meet the evolving demands of AI and ML workloads. Ultimately, aligning storage with the specific nature of the workload is key to unlocking AI’s full potential while optimizing total cost of ownership.