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NetApp Unveiled New AI Storage Management Features

The company introduced AI-powered infrastructure tools to address data silos and improve project performance.

Updated on Sept. 29, 2026 in Artificial Intelligence

Isometric editorial illustration featuring geometric storage cubes and data conduits in teal and cream, representing enterprise infrastructure systems.
NetApp debuted new AI-powered storage management tools at its annual conference, aiming to help enterprises consolidate fragmented data and scale AI operations. AI Illustration. Upload story photo >

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NetApp debuted new AI-powered storage management capabilities at the NetApp Insight 2026 conference. These features aim to help businesses transition AI initiatives from the pilot stage to full production.

Why it matters

Many organizations struggle with scaling AI due to data quality issues and fragmented infrastructure. These tools are designed to streamline operations by addressing the underlying data silos that often hinder enterprise AI success.

The new features include automated remediation and predictive maintenance insights for infrastructure. Users can now integrate large language models directly into the NetApp Console to manage their ONTAP data software environments.

The players

NetApp

This global company provides data management and storage software solutions designed for hybrid cloud environments.

George Kurian

He serves as the Chief Executive Officer of NetApp and has emphasized the necessity of strategic business leadership for successful AI integration.

IDC

This global market intelligence firm provides data and analysis on information technology and telecommunications trends.

The details

NetApp introduced these tools to mitigate the challenges identified by IDC, which found that seven-in-ten business leaders struggle with data silos. By integrating predictive analytics and automated management into their existing platform, the company intends to help firms improve data quality, which is considered the top factor for successful project implementation.

Timeline

  1. An MIT study from August 2025 found that 95% of AI projects were failing.

  2. Research in January 2026 indicated that half of all agentic AI projects remained stalled at the pilot phase.

  3. NetApp Insight 2026 took place in September 2026.

The Tech Race

NetApp's strategy follows the pattern set by the IDC report on data silos as a primary obstacle for AI adoption. The company is positioning itself to win the infrastructure battle by focusing on data quality rather than just model development.

IT administrators and data managers can expect reduced manual intervention through automated remediation and predictive maintenance. These tools aim to simplify the daily management of large-scale infrastructure by integrating AI insights directly into existing console workflows.

The takeaway

The move underscores that the biggest bottleneck for modern AI is often the underlying data architecture rather than the models themselves. Businesses looking to improve AI success rates should prioritize integrating management software that bridges data silos.

Further reading

For more on how companies are scaling automated infrastructure, see the latest updates in Artificial Intelligence.

Source note: This article includes information reported by ITProUK.

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Do you believe clear business strategy is more important than the specific technology adopted?