At NetApp INSIGHT 2025, the company continued to deliver on its plan to transform storage from a passive repository to an active data foundation for the enterprise. This vision reflects a broader industry shift toward infrastructure that not only stores data but orchestrates, governs, and accelerates its use — especially for AI-driven workloads. Many of the keynotes featured videos from its key hyperscaler partners (Google, Microsoft, AWS) alongside an announcement of NVIDIA DGX SuperPOD-certified AFX. Most notably, CEO George Kurian set the vision for AI with the company’s plan to connect unstructured data to structured data through its AI Data Engine, connected via knowledge graphs. On the second day of the event, client keynotes featured presenters from the NFL and the San Francisco 49ers. Track sessions also included stories from Scotiabank, GSK, Ford Motor Company, and Siemens, among others.

Key Themes Emerging From The Event

  • Disaggregated architectures: NetApp introduced AFX, a modular all-flash platform that separates performance from capacity, enabling independent scaling. This approach mirrors a growing trend toward architectures optimized for AI pipelines and GPU adjacency.
  • Active metadata and embedded services: The emphasis on “active metadata” signals a move toward dynamic data fabrics that enable semantic search, governance, and lifecycle control — capabilities essential for retrieval-augmented generation and other AI workflows.
  • Unified control planes: NetApp Console replaces BlueXP, modernizing and simplifying management across hybrid and multicloud environments. It also unifies the controls for data services, storage, orchestration, and resilience capabilities into a single tool.
  • Security and resilience: Enhancements in ransomware detection, such as the announcements of real-time ransomware detection for block volumes and isolated recovery environments, underscore the expectation that compliance and protection should be embedded within infrastructure.

Why Enterprises Should Pay Attention

These developments are not just vendor-specific — they’re indicators of where storage strategy must evolve:

  1. AI workloads demand proximity and scale: Architectures must minimize data movement and maximize throughput for training and inference.
  2. Governance must be native: Regulatory compliance and risk mitigation need to be intrinsic to the data layer.
  3. Metadata is strategic: Rich metadata management is becoming a cornerstone for AI-driven insights and automation.

NetApp’s vision of a “data foundation” aligns with these imperatives. Whether or not you adopt NetApp solutions, the principles — disaggregation, embedded governance, and active metadata — should inform your roadmap.

Why It Matters

The AI era is reshaping infrastructure priorities. For technology leaders, this will mean rebuilding your infrastructure as platforms with observability, accountability, security, and intelligibility built in and then functionality exposed as services. I’ve been calling it the “OASIS framework,” and it’s the basis for some of my upcoming research. For your current storage portfolio, this will mean turning your storage into a data foundation:

  • Audit your current storage platforms: Can it support GPU adjacency, hybrid flexibility, and metadata-driven workflows?
  • Embed data services: Observability, data classification, and security capabilities should be integrated into your storage layer.
  • Plan for scale and control: Architect for governance and scalability from the start, not as afterthoughts.

Next step: Connect with Forrester for guidance on evolving your storage platform strategy. Better yet, meet me at Forrester’s Technology & Innovation Summit in Austin and see my keynote on architecting infrastructure as platforms to address an agentic AI future.