The evolution of intelligent data infrastructure: Rethinking data control in the AI era

An AI assistant needs access to enterprise data—documents, knowledge bases, runbooks, internal communications—to be useful. But within those same repositories, sensitive information often exists—intentional or otherwise.

In this scenario, an internal AI assistant begins accessing data it shouldn’t. The platform evaluates that access in real time, understands the relationship between the data, the identity, and the behavior, and intervenes before any sensitive information is exposed.

This is one example of a broader shift. Any legitimate identity—human, application, or AI—can access data in ways that introduce risk. Controlling that risk requires both visibility and enforcement at the point of data access. Because NetApp sits directly in the data path, we can do exactly that, extending this approach across a wide range of data security and governance use cases.

Working within the existing ecosystem

Organizations already operate complex ecosystems of security, governance, and data management tools. The goal is not to add another standalone system into an already crowded environment. Instead, we believe the infrastructure layer can serve as a point of convergence - working alongside existing tools and partners while providing unique visibility into how data is being accessed and used.

This is why our approach is designed to integrate with the broader ecosystem. Partners across the data security and AI governance landscape—including Cyera and Enkrypt.AI—help customers understand data sensitivity, AI risk, and governance requirements. Combined with the vantage point of the data layer, these insights move organizations from isolated visibility toward coordinated understanding and control.

More importantly, we see this work as the beginning of a broader conversation with customers. As organizations rethink how data is accessed and used across increasingly complex environments, their feedback will help shape the evolution of these capabilities.

The next step in intelligent data infrastructure

At NetApp, we have seen enterprise data infrastructure evolve in step with how organizations use their data. For years, the focus was on where data is stored—ensuring it could be protected, moved, and accessed reliably across increasingly complex environments. More recently, we have worked with customers to build intelligent data infrastructure that helps them understand their data and make it usable across applications, analytics platforms, and emerging AI systems.

The next step in that evolution may be to understand and influence how that data is used.

As automated systems, applications, and AI models increasingly interact directly with enterprise data environments, organizations will need new ways to observe those interactions, understand them, and respond when something unexpected occurs.

At NetApp, we believe the data layer has a unique role to play in helping customers navigate this shift. Our goal is to explore these capabilities alongside customers and partners as part of the continuing evolution of intelligent data infrastructure.

In an AI-driven world, the question is no longer just where data lives—it’s how it is used, and how that use is understood and controlled.

Speak to our product team and explore more about what we’re up to.