Data silos constrain IT operations and AI ambitions
A report released by Ivanti last week points out that data silos are widening the gap between the reality and goals of IT teams. The survey shows that over half of technology professionals believe security and IT data are isolated within their organizations, leading to slow security responses, low IT efficiency, and hindering the effective use of AI tools.

Briefing at a Glance
- A report released last week by software company Ivanti shows that data silos are widening the gap between the reality and goals of IT teams. The company surveyed more than 1,200 IT and cybersecurity professionals.
- More than half of technology professionals said that security and IT data within their organizations are isolated from each other. The survey noted that data silos affect efficiency, collaboration, visibility, security, and the ability of organizations to execute broader strategies.
- Data blocking hinders various functions within enterprises. More than three-fifths of respondents attributed slow security responses to data silos, and two-fifths reported IT inefficiency. Nearly 30% of IT professionals said data deficiencies prevent them from effectively using AI tools.
Deep Insights
In the pursuit of efficiency, the data puzzle has become an obstacle on the path forward for enterprises. Additionally, those focusing on AI projects face a stronger sense of urgency in strengthening practices and establishing governance.
"Data ownership is often a hot potato topic, but in the AI era, it has become unavoidable," said Stijn Christiaens, co-founder and chief data citizen at Collibra. According to a report by SoftServe earlier this year, nearly two-thirds of decision-makers said that no one in their organization truly understands data collection or access.
Analysts told CIO Dive that organizations need a comprehensive data strategy, requiring leaders to think deeply about data governance, quality, performance, lineage, and diversity. Without a solid foundation, enterprises may overlook a key differentiator in their overall AI efforts.
Even as pressure to push AI projects into production increases, most enterprise data strategies remain insufficient at present.
"The data investment required for generative AI is by no means trivial," said Rita Sallam, distinguished vice president analyst at Gartner, during a webinar in March.
Amid economic uncertainty, enterprises need to weigh how to prioritize projects and investments while shifting attention to cost-saving measures and building flexibility into plans. According to the Ivanti survey, optimizing IT costs is the top strategic priority for more than two-fifths of IT professionals this year.
Christiaens said that enterprises may fall into a common trap of pitting innovation against governance, especially when facing potential tariffs and other volatility pressures.
"This is a false dichotomy," Christiaens said. "Without ownership and accountability, innovation is impossible."