---
title: "Your AI agents need context: BARC interview | DataXray"
description: "Kevin Petrie of BARC and Kyle DuPont of DataXray on why AI agents need context, and why it’s trapped in files no one can find."
url: "https://www.dataxray.io/resources/barc-interview/"
language: "en-US"
---

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INTERVIEW · BARC

# Your AI agents need context. It’s trapped in files no one can find.

BARC surveyed 225 data and AI leaders. 79% are confident they can govern unstructured data for AI, but only 29% fully know where it lives. Kevin Petrie, VP of Research at BARC, and Kyle DuPont, CEO of DataXray, talk through why that gap exists, what it means for the teams building AI on top of it, and where the fix starts.

WATCH THE INTERVIEW

THE CONVERSATION

## What Kevin and Kyle get into

Kevin leads the data management practice at BARC, writing on AI, data integration, and data governance. For 30 years he has worked out what technology means for practitioners, as an industry analyst, instructor, marketer, services leader, and tech journalist. He built a data analytics services team for EMC Pivotal across the Americas and EMEA, and ran field training at data integration provider Attunity, now part of Qlik. A frequent speaker and co‑author of two books on data management, Kevin’s main interest is teaching data and AI leaders how to capitalize on the value of their data.

Kyle co‑founded DataXray after watching enterprise after enterprise hit the same wall on AI: the files holding their most valuable information, the documents, emails, and contracts AI needs to work, were the files no tool could open, read, or classify. He has worked with major financial institutions, government agencies, and defense organizations to bring that data into view and make it ready for AI, compliance, and security workflows. DataXray reads and classifies files across the enterprise estate, feeding the results into the AI, compliance, and security tools already in place, without moving the data.

Why confidence and capability don’t match, and what that means for the AI roadmap your board just approved.

What breaks when a curated pilot meets petabytes of real files, and why vector databases alone won’t fix it.

The role no one talks about that may matter most for AI. It’s not the one you’d guess.

Why data quality means something different for files than for tables, and why most teams haven’t worked that out.

THE FULL REPORT

## Harnessing Unstructured Data for AI Innovation

The interview draws on this BARC study. The full report has the findings from all 225 data and AI leaders, including where organizations stand on data readiness, where governance falls short, and what the leaders do differently.

[Download the report](https://www.dataxray.io/research/barc-2026/)