The AI data platform era is here

Object storage is no longer just storage. It is becoming a foundation for AI data platforms.

Organizations now use object storage to feed AI pipelines, support inference workloads, run analytics environments, and manage distributed data at massive scale. As AI moves from experimentation into production, storage teams need to do more than store data. They need to move it faster, govern it more effectively, and make it easier to use across distributed environments.

That shift is reflected in The Forrester Wave™: Object Storage Solutions, Q2 2026, where NetApp was named a Leader. According to Forrester’s evaluation, NetApp has a “compelling vision of enterprise data infrastructure optimized for hybrid, multicloud, and sovereign use cases” and is “a strong fit for large enterprises managing distributed, regulated object estates that want to balance governance and hybrid consistency against the need for AI-native storage services.”

The requirements have changed

For years, enterprises evaluated object storage primarily on durability, scale, and cost. Those still matter, but they are no longer enough.

Today, customers are asking different questions. Can object storage help scale AI pipelines? Can it move data fast enough for analytics and inference? Can it operate consistently across distributed environments without adding complexity? Can it help teams control who can access, change, and protect data as governance requirements increase?

These are the questions shaping the next phase of object storage.

In our view, organizations are looking beyond durability and scale alone. They increasingly need platforms that can support AI initiatives, evolving governance requirements, and distributed operating models.

According to The Forrester Wave™: Object Storage Solutions, Q2 2026:

"Today's object storage decisions hinge less on raw durability claims and more on how object platforms align with enterprise operating models, AI ambitions, and regulatory realities."

The report also states:

"Buyers should look beyond S3 compatibility alone; instead, they should evaluate where object storage sits in their broader data architecture: whether as a highly regulated system of record, an active AI data plane, or a cloud-native service substrate."

As this market evolves, customers are likely to prioritize platforms that can help them scale data globally, move it into AI workflows faster, and maintain control as data becomes more distributed.

Why NetApp was recognized as a Leader

We believe NetApp's recognition as a Leader reflects years of investment in helping customers manage distributed data, support governance requirements, and prepare for AI-driven workloads.

According to The Forrester Wave™: Object Storage Solutions, Q2 2026:

"NetApp has a compelling vision of enterprise data infrastructure optimized for hybrid, multicloud, and sovereign use cases."

The report further states that NetApp is:

"a strong fit for large enterprises managing distributed, regulated object estates that want to balance governance and hybrid consistency against the need for AI-native storage services."

To us, those capabilities matter because customers are not building simple storage repositories anymore. They are building distributed data environments that need to support AI, analytics, compliance, backup, archive, and cloud-connected workflows at the same time.

The report also noted:

"Its solid roadmap focuses on improving flexibility, expanding data services, modernizing the control plane, and expanding object scale and performance to support future workloads."

And:

"Cloud partnerships, global reach, a strong ISV network, strategic alliances, and top-tier support make NetApp an easy enterprise choice."

That combination of factors matters because customers need to move faster without losing control. They need to support AI workloads while maintaining governance, and they need to scale globally without creating new operational silos. That is where NetApp is focused.

StorageGRID 12.1 shows execution

Being named a Leader only matters if it translates into product execution.

StorageGRID 12.1 is a recent example of how NetApp is helping customers build for the AI data platform era. The release focuses on the same requirements customers are now prioritizing: scale distributed data, move and process data faster, reduce unnecessary work in AI pipelines, and maintain control as environments grow.

Scale distributed data without adding complexity

AI data rarely lives in one place. Customers manage data across data centers, regions, business units, cloud connected environments, and edge locations. If every environment becomes a separate storage silo, teams spend more time managing infrastructure and less time using data.

StorageGRID 12.1 introduces a Global Federated Namespace that lets customers operate multiple StorageGRID environments through a single namespace. Teams can run distributed environments as one logical system, scale beyond the limits of a single cluster, and support larger deployments without redesigning applications or changing how they work.

Move data faster

AI and analytics workloads depend on how quickly teams can access and process data.

StorageGRID 12.1 delivers up to 4x higher throughput for tested configurations, workloads and object sizes. These improvements help teams move data faster, reduce bottlenecks, and support workloads that depend on fast access to large volumes of object data. The biggest gains show up in small-object and mixed workloads, which often create bottlenecks in AI and analytics environments.

For customers, the benefit is simple: pipelines move faster, processing jobs complete sooner, and infrastructure works harder for the workloads that matter.

Process less data

As datasets grow, teams cannot afford to process everything every time. They need to identify what changed and focus only on the data that matters.

StorageGRID 12.1 adds S3 Bucket Change Tracking to help customers identify changes in object data. That helps teams avoid unnecessary reprocessing, reduce compute cost, and speed up inference and retrieval workflows such as RAG pipelines. Instead of spending time and resources processing full datasets, teams can process the data that changed.

That makes AI pipelines more efficient.

Manage object data at scale

When customers manage billions of objects, even simple tasks can become difficult. Moving, replicating, or managing large object sets can require custom scripts, manual checks, and significant effort.

StorageGRID 12.1 adds S3 Batch Operations support for batch replication. This helps customers move data at scale across massive object sets without building one-off tooling. It gives teams a more practical way to manage large-scale object workflows as environments grow.

Stay in control as workloads move into production

As AI and analytics workloads move into production, administrative actions carry more risk. Policy changes, security updates, and controls on sensitive data should not depend on one administrator acting alone.

StorageGRID 12.1 adds multi-admin verification, which requires approval from another administrator before critical operations take effect. This helps customers protect against unintended deletes, unauthorized policy changes, and compliance issues while still keeping teams moving.

That matters in regulated and high-control environments where speed and control both matter.

What comes next

The AI data platform era is still in its early stages. AI models will continue to grow, data will become more distributed, performance expectations will rise, and governance requirements will become more demanding.

The platforms that lead will not simply store data. They will help customers move it faster, put it to work in AI pipelines, manage it across distributed environments, and protect it as requirements change.

That is the direction NetApp is building toward.

StorageGRID 12.1 shows recent execution against that direction. It helps customers scale distributed data, improve throughput for AI and analytics workloads, process less data when possible, manage large object sets more easily, and maintain stronger control as environments grow.

To us, the Forrester Wave recognition shows the direction of the market and validates NetApp’s position in it. As object storage becomes a foundation for AI data platforms, NetApp is helping customers scale, govern, and activate their data for the next generation of AI workloads.

Read the report

Read The Forrester Wave™: Object Storage Solutions, Q2 2026 to learn more about the market trends shaping object storage and why NetApp was named a Leader.

Forrester does not endorse any company, product, brand, or service included in its research publications and does not advise any person to select the products or services of any company or brand based on the ratings included in such publications. Information is based on the best available resources. Opinions reflect judgment at the time and are subject to change. This report is part of a broader collection of Forrester resources, including interactive models, frameworks, tools, data, and access to analyst guidance. For more information, read about Forrester’s objectivity here.