Making Data Usable Where It Lives — Research Paper

Agentic AI Needs On-Demand Governed Context Without Consolidating Environments

For many enterprise AI programs, the data itself is now a tighter constraint than the models or the infrastructure. Most of that data is unstructured and very little has been through the parsing, enrichment, and indexing that make it retrievable by a model. Reaching the data is one engineering problem and preparing it is another; programs that stall are usually stuck on both.

Most of the available fixes were engineered for a different requirement. Cloud data platforms were built to govern the data that comes to them, while storage platforms were built to hold data and keep expensive AI accelerators fed. Both platforms do their jobs well. But agentic AI needs governed, current context pulled on demand from systems that nobody will consolidate, and neither cloud data platforms nor storage platforms were designed to deliver that.

Dell built the AI Data Platform around a very different paradigm, so every layer runs against data where it already sits. Its Data Orchestration function turns raw multimodal data into something a model can retrieve, the Data Engines query and search across the estate, and the Storage Engines hold it all. Shared storage, one governance model, and Dell’s own system software run those three layers as a single platform. A buyer can run one stalled project on that platform without committing to an architecture first. So, the questions for a data leader are: Which AI projects are blocked today, and what is blocking them?

Click the image below to download the full research brief to explore the requirements for making enterprise data usable where it lives.

TABLE OF CONTENTS
The Enterprise AI Bottleneck Has Moved
Why This Is Not the Data Lake Conversation Again
Where Enterprise Data Breaks Down
What a Data Platform for AI Must Achieve
What the Market Offers Today for AI Data Platforms
Dell’s Approach to the AI Data Challenge
How Data and AI Leaders Can Assess Their AI Data Needs
The Pressing Need to Address Agentic Realities

COMPANIES CITED
Dell Technologies
NVIDIA
Starburst
Elastic

Mike Leone
VP & Principal Analyst | + posts

Mike Leone is a principal analyst at Moor Insights & Strategy covering data platforms and analytics, data infrastructure and storage, and data governance and enterprise data strategy. He brings 15 years of analyst experience from his work at Enterprise Strategy Group, where he rose to practice director for data management, analytics, and AI. Mike's work is grounded in a strong technical and strategic foundation, including early roles in software and hardware engineering.

Patrick Moorhead
Founder, CEO and Chief Analyst | + posts

Patrick Moorhead is the founder, CEO, and chief analyst of Moor Insights & Strategy. His big-picture view of technology is grounded in more than 20 years as an executive leading strategy, product management, product marketing, and corporate marketing functions at NCR, AT&T, Compaq, and AMD. He has shared his expertise in areas from silicon to infrastructure to enterprise SaaS and everything in-between in thousands of national broadcast appearances (CNBC, Yahoo Finance), articles (Forbes, CIO), research-based analyses, and podcast episodes. Today, he has 100+ CXO-level advisory clients and is often ranked the #1 technology industry analyst by ARInsights.

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