With the AI market is expanding at a CAGR of 37.3% between now and 2030, organizations are collectively investing billions of dollars each year in AI projects to solve challenges spanning nearly every industry. But AI engines require huge quantities of AI data storage in order to learn, improve, and produce models effective enough to meet or exceed human cognitive ability.
This raises the question — can legacy data infrastructures handle these never-before-seen volumes of data? Increasingly the answer is no, which has led to the development of AI-native data platforms designed specifically for the new demands of AI innovation.
In this post we’ll explore what AI storage is, why it matters, how it works, and how it benefits organizations adopting AI at scale.
What is AI Storage?
AI storage is the new foundational technology supporting AI growth. It’s an innovative approach to data storage that has been re-engineered from the ground up to maximize data speed, scale, resiliency, availability, and security.
AI data storage integrates with an organization’s machine learning and deep learning processes to increase the speed and performance of these tasks. By doing so, it not only accelerates AI model development, but also enables more intelligent and sophisticated models by allowing more data to be used in the learning process.
Another important characteristic of AI storage is data reduction technologies like compression, deduplication and more modern approaches such as similarity. By more efficiently handling data with built-in data reduction technology, AI data storage decreases data size and, therefore, the costs required to store it.
To sum up, AI requires new approaches to data storage, management, and access to properly perform its intended function and add exponential value to today’s companies and consumers. AI storage is the solution making that happen.
Why Is AI Storage Needed Now in 2025?
AI has exploded in recent years, with 77% of companies now either using or exploring the use of AI in their businesses. This growth is exciting to see, but the result is that immense pressure is now being placed on existing data systems that weren’t built for AI.
For most organizations, their data architectures have ballooned over time and become slow and complex to maintain. Plus, these legacy infrastructures were designed to handle lower data volumes, and even newer cloud-native environments were built with lightweight, transactional tasks in mind. Neither approach is suitable for the massive amounts of data and compute power that AI engines require in order to excel.
In addition to this data complexity, IT teams are increasingly being pushed to do more with less. But managing multiple disjointed data systems can quickly burn through the ever-shrinking IT budget and leave organizations with sub-par AI outcomes.
How Does AI Storage Work?
The unique design of AI data storage systems allows AI engines to process data quickly and at any scale. Their core characteristics include:
Single-Tier Design
AI storage is a simple, universal storage infrastructure that unifies data environments into a single, resilient tier of flash. With AI data storage, there are no hard drives or additional data storage tiers required.
Flash Data Storage
AI storage relies on flash data storage technology, which, like a solid-state drive (SSD), uses fast memory chips to store, read, and write large amounts of data without any moving parts. This approach offers much greater speed and performance than traditional spinning-platter hard drives.
Disaggregated Architecture
AI storage ensures resource speed and availability by provisioning, maintaining, and scaling storage needs and compute power separately. With AI data storage, there are no forced coupling or system-wide upgrade requirements.
These AI storage characteristics enable fast, global data access across all the locations an organization may compute, plus the ability to capture data snapshots at exabyte scale, and at any system depth, without impacting performance.
What are the Benefits of AI Data Storage?
AI storage has become critical for businesses looking to adopt AI at scale in 2025. Here’s why:
Speed: The unified, single-tier, parallel architecture of AI storage delivers all-flash performance and enterprise simplicity for optimal data availability and system speed.
Security: The right AI storage platform provides reliable multi-tenant and multi-protocol support, with unified ACLs enabling enterprise-grade security for all structured and unstructured data storage needs.
Scale: With flash storage technology and compounding data efficiencies, AI storage offers an affordable way to make any volume of data AI-ready, on-prem or in the cloud.
AI data storage offers a streamlined solution with no need for separate storage systems or multi-layer orchestration. Plus, besides being faster, more secure, and more scalable than legacy data infrastructures, AI storage lowers the total cost of ownership and improves budget predictability.
How to Get Started
With a focus on availability, affordability, and scalability, AI storage platforms such as VAST Data accelerate the entire AI data pipeline to address the needs of today’s data-driven organizations. And industry leaders are taking note — Pixar, CoreWeave, and many other innovative companies have turned to VAST Data to power their generative AI initiatives.
Let VAST Data help you bring your AI projects to life with data storage designed specifically to support them. Schedule a personalized demo with our team today to see how AI data storage can enable your AI development goals.
