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Ivanti: Why Data Fragmentation Limits AI Effectiveness in IT

Ivanti
06/27/2026
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it fails because it can't see the full picture. So I'm Sterling Parker, SVP of our technical solutions and services at Avanti, and here's why data fragmentation is the biggest thing holding AI back for customers. From what we see every day, nearly 90% of IT teams say siloed data hurts their ability to operate securely and efficiently. When AI is pulling from disconnected systems, the answers obviously get harder to trust. So second, automation doesn't scale. Over 60% of teams say silos slow their incident response. And AI might flag an issue, but teams still have to jump between tools to get that fixed. The good news, customers who use AI to unify tools and workflows are already seeing faster resolutions, better collaboration with their teams and fewer handoffs, especially those organizations that are the most mature. And if you want AI to actually improve support outcomes, it starts with that connected data. That's one of the clearest findings from our latest research, and that's why you need to take it closer.

TL;DR

  • AI effectiveness is limited by data fragmentation, with 90% of IT teams reporting that siloed data hurts security and operational efficiency.
  • Over 60% of teams experience slower incident response due to disconnected systems, requiring manual navigation between tools even after AI identifies issues.
  • Organizations using AI to unify workflows are seeing faster resolutions, better collaboration, and fewer handoffs, particularly among mature implementations.

Summary

Sterling Parker, SVP of Technical Solutions and Services at Ivanti, addresses the critical challenge of data fragmentation in AI-driven IT operations. Drawing from recent research, Parker explains that nearly 90% of IT teams report that siloed data undermines their ability to operate securely and efficiently. When AI systems pull from disconnected sources, the reliability of insights diminishes significantly. The presentation highlights that over 60% of teams experience delayed incident response due to data silos, forcing staff to navigate multiple tools even after AI flags issues. However, organizations that have successfully unified their tools and workflows through AI are already experiencing measurable improvements in resolution speed, team collaboration, and operational efficiency. Parker emphasizes that connected data is the foundational requirement for AI to deliver meaningful support outcomes, positioning data integration as the primary enabler of AI success in IT environments.

Chapters

0:00 - The AI Visibility Problem
0:14 - Data Silos Impact Operations
0:27 - Automation Scaling Challenges
0:39 - Benefits of Unified Workflows

Key Quotes

0:00 "AI doesn't fail because it's not smart enough, it fails because it can't see the full picture."
0:15 "Nearly 90% of IT teams say siloed data hurts their ability to operate securely and efficiently."
0:29 "Over 60% of teams say silos slow their incident response."

FAQ

Why does data fragmentation limit AI effectiveness in IT operations?

When AI pulls from disconnected systems, it lacks the complete context needed to provide reliable insights. This forces teams to manually verify information across multiple tools, undermining the efficiency gains AI is supposed to deliver.


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