How NetApp turns unstructured data into an AI-ready asset

Eighty-four percent of enterprises say their storage is not ready for AI. Most organisations already have the computing power and the models they need. What they lack is a practical way to make their existing data useful to those models. A team builds a promising prototype; it attracts executive attention, then harder questions surface. Where does production-scale data come from, and who governs access to it?

IDC’s Enterprise AI Maturity Study identifies top performers as AI Masters. These organisations invest in data foundations before scaling AI workloads. The payoff is 24.1% revenue improvement over peers. The critical factor is data readiness, not better models.

Another fact is that around 80% of enterprise data sits in unstructured formats that AI models cannot directly consume. Most organisations still tackle data preparation manually, one project at a time. That is precisely where AI initiatives lose momentum and budgets erode.

Intelligence built into the storage layer

NetApp’s approach inverts the conventional model. Rather than copying data to separate AI preparation tools, intelligence moves to where the data already lives. The AI Data Engine (AIDE) is an extension of ONTAP that integrates directly with the NVIDIA AI Data Platform reference design. It discovers, classifies, governs, and prepares enterprise data for AI without requiring migration.

AIDE works across four connected functions. A metadata engine builds a structured, searchable view of the data estate. Data sync maintains currency through automated change detection rather than batch processing. Guardrails scan and classify sensitive content, embedding policy-driven controls directly into AI workflows.

A data curator handles vectorisation, retrieval, and secure RAG endpoints. Data scientists connect these endpoints directly to applications without middleware. AIDE’s built-in compression delivers up to 10x reduction in storage needs for vectorised content.

NetApp AFX complements AIDE as an all-flash, disaggregated storage platform built for AI workloads. Certified for the NVIDIA DGX SuperPOD and scaling to exabyte capacity, AFX uses standard NFS and S3 protocols. Applications connect without the specialist setup that competing parallel file systems demand.

Why acting on data readiness cannot wait

Global AI infrastructure spending will reach $758 billion by 2029. The investment keeps accelerating. Yet MIT’s NANDA Initiative found that 95% of enterprise AisI pilots fail to deliver measurable impact. Th gap between spending and returns sits squarely in the data layer.

UK organisations face additional constraints. More than half of UK SMEs are already using AI, with a further 17% planning adoption. UK GDPR requires personal data processing within the UK jurisdiction. Financial services regulators demand audit trails for AI-driven decisions, while healthcare organisations need sovereign data handling.

NetApp's hybrid architecture addresses these requirements directly. ONTAP manages over 100 exabytes globally, with consistent governance across all environments. Organisations can train models in the cloud and run inference on premises. Data policies follow the data, regardless of location.

The Aston Martin Aramco Formula One Team shows this approach in practice. Headquartered at Silverstone, the team recently deployed a petabyte-scale NetApp infrastructure to support AI capabilities. They process 100 megabytes of data per lap from hundreds of car sensors. SnapMirror transfers the race data back to the UK headquarters after every session.

How Softcat helps you build an AI-ready data foundation

We hold NetApp Prestige Partner status, one of only four in the UK. NetApp also named Softcat its AI Partner of the Year in March 2025. Our track record earned additional recognition through NetApp’s Commercial and Net New Logo awards. Our teams understand both greenfield deployments and the harder work of migrating from established environments.

Our support goes beyond infrastructure. Softcat's Data, Automation, and AI team connects data to real business outcomes. Oakland, which joined the Softcat family in 2025, brings decades of expertise in helping organisations use their data effectively. NetApp AIDE addresses the infrastructure layer. Oakland addresses the strategy layer. Most organisations need both. We address them together.

Making your data work for AI

The organisations succeeding with AI are not the ones with the largest GPU clusters. They are the ones whose data is ready. Intelligent data infrastructure turns passive storage into an active foundation that classifies, governs, and prepares data.

Whether you are planning an AI initiative or working to move beyond the pilot stage, Softcat can help. We will assess your data readiness and build a practical path forward. Please click here to contact our Sales team.