The Zombie Problem That AI Brought Back from the Dead - Data Sprawl

Michael Mestrovich, VP and CISO at Rubrik

Published Jul 28, 2025

Remember that closet you kept promising to clean out, but instead just kept stuffing more things into it? Now imagine that closet contains all your company's most sensitive data, and AI just dumped ten times more stuff in there while also handing out keys to everyone. That's exactly what Michael Mestrovich, VP and CISO at Rubrik, is warning us about in his eye-opening analysis of how AI has resurrected one of cybersecurity's most stubborn unsolved problems: data sprawl.

A decade ago, security teams threw up their hands in defeat when faced with exploding data volumes from mobile devices and IoT systems. They basically gave up trying. Now AI has brought this zombie problem back to life - with much higher stakes and an even bigger appetite for corporate data!

The Problem in Simple Terms

What's Wrong: Imagine trying to guard a house when you don't know how many rooms it has, what's in each room, or who has keys. That's data sprawl - your company's information scattered everywhere, multiplying faster than anyone can track, and now AI is both gorging on this data AND creating even more of it.

Real Business/Academic Challenges:

  • The AI Data Explosion: AI systems generate massive new data streams - model outputs, training metadata, interaction logs, and analytical reports that accumulate without proper management
  • Invisible Treasure Vaults: Legacy databases containing intellectual property exist in forgotten network corners, unmanaged and unprotected
  • The Manual Management Trap: Organizations assign tiny teams to manually categorize exponentially growing data - an impossible task
  • Security Blind Spots: 74% of surveyed IT leaders report successful data breaches, while 86% paid ransoms
  • AI Access Amplification: AI systems may expose sensitive data to unauthorized individuals, creating new leakage vectors

The Solution

Mestrovich outlines a comprehensive automated approach:
  • Automated Data Discovery & Classification: Use AI-powered tools to find, categorize, and tag data based on sensitivity across all environments
  • Strategic Data Minimization: Implement systematic retention policies and regular purging to reduce attack surfaces
  • Zero Trust Data Controls: Move beyond network perimeter security to least-privilege access for individual data objects
  • Immutable Backup Systems: Protect critical data while maintaining visibility and regular recovery drills

Why This Matters for Praxis AI

This article perfectly validates why our AI middleware orchestration platform was architected with enterprise-grade data governance from day one! While other companies are scrambling to retrofit data security, we've been solving this exact challenge.

Our Built-In Data Governance Excellence:

Our digital experts operate through secure middleware that automatically manages data classification, access controls, and retention policies. We don't create data sprawl - we organize and protect it.

Validated Security in Action:

Our 35% improvement in learner performance metrics come from AI agents that access sensitive educational data while maintaining strict governance boundaries. Universities trust us precisely because we solved the data management challenges this article describes.

The Strategic Advantage:

This research shows data sprawl isn't just a security problem - it's a competitive disadvantage. Organizations using our platform get AI's transformational power without the exponential data management headaches crippling their competitors!

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