NetApp's unified storage plays for production AI at INSIGHT event

When artificial intelligence transitions from experimentation to live deployment, a single technology could prove essential: unified storage that bridges data across multiple locations. NetApp Inc., which specializes in enterprise data storage systems, is betting that its unified approach can reduce the operational friction that has slowed AI adoption. Organizations implementing AI have consistently cited data management as their biggest challenge, and NetApp's unified storage platform aims to simplify how enterprises handle data flows for AI applications.

"AI is forcing enterprises to rethink infrastructure around the data," said Krista Case, principal analyst for theCUBE Research. "Training, RAG, inference and agentic workloads need governed, current data that may span the data center, cloud and edge. That makes fragmentation and data movement increasingly expensive, not just in performance terms, but in security, governance and operational complexity. NetApp's opportunity is to make the existing enterprise data estate usable by AI without forcing organizations to create yet another data silo."

NetApp will present its strategy for AI-ready infrastructure at its INSIGHT event on Sept. 30, with coverage streaming live on theCUBE, the livestreaming platform operated by SiliconANGLE Media. The broadcast will showcase NetApp executives and storage specialists discussing how the company plans to support data mobility and build foundations for enterprise AI deployment.

Unified storage as a prerequisite for AI applications

Research from theCUBE's application development team indicates that 64% of organizations have already embedded AI capabilities into their software delivery processes. This widespread adoption has created demand for unified storage systems that keep data accessible and ready for AI operations across different environments.

"Unified storage is becoming an important part of that foundation because developers are increasingly building applications that depend on real-time data, distributed architectures and AI-generated context," said Paul Nashawaty, principal analyst for theCUBE research. "Our research points to real-time data access becoming a prerequisite for AI-driven applications, while the broader shift toward agent-first development means applications will increasingly need continuous access to trusted data rather than relying on static datasets."

Case and Nashawaty see NetApp positioned to deliver a unified data layer that AI systems can tap into regardless of where information resides. For enterprises moving AI from proof-of-concept to production, this capability matters because it anchors probabilistic systems in reliable, consistent data sources.

"The bigger strategic question isn't simply whether NetApp can deliver faster storage," Nashawaty said. "It's whether it can reduce the data fragmentation and operational complexity that stand between enterprise data and production AI. As AI moves from experimentation into production, unified storage becomes less about where data sits and more about how quickly, consistently and securely applications can use it."

How to follow the coverage

theCUBE's livestream of NetApp INSIGHT will air on Sept. 30, with on-demand replays available afterward. Coverage will be accessible through theCUBE's website and YouTube channel, as well as on SiliconANGLE's main platform.

SiliconANGLE produces two regular programs featuring enterprise technology analysis. "theCUBE Pod," hosted by John Furrier and Dave Vellante, explores major industry shifts including AI, cloud infrastructure, regulatory developments and workplace trends. The show is available on Apple Podcasts, Spotify and YouTube. Additionally, Vellante hosts "Breaking Analysis," a weekly program that combines theCUBE reporting with spending data from Enterprise Technology Research, also distributed across Apple Podcasts, Spotify and YouTube.

Event participants

theCUBE will conduct interviews with industry specialists at NetApp INSIGHT to examine how the company is evolving its storage, cloud and data capabilities for production AI environments. Discussion topics will include unified data access, infrastructure modernization, partner ecosystems, AI-ready platforms and the expanding requirements of enterprise systems.