Immuta, a leader in data security, has released its 2025 State of Data Security Report, revealing the optimism and concerns around evolving data infrastructures. The report, commissioned by Immuta and conducted by UserEvidence, surveyed over 700 data leaders and professionals from across the U.S., UK, Canada, and Australia. The report highlights how organizations are grappling with the dual challenge of securing data while ensuring timely access, especially as AI adoption accelerates.

Findings from the Report

• Legacy Systems Can't Keep Up
  According to Matthew Carroll, Co-founder and CEO of Immuta, traditional systems for provisioning data access are broken, unable to scale with the increasing number of users and data demands. The report calls for a shift in approach, focusing on people, processes, and technology as core elements of IT and business strategy.

• AI Presents New Data Access Challenges
  60% of respondents claim their organizations are failing to keep pace with AI-driven data demands. Nearly half of organizations highlight compliance and privacy as primary concerns, while 64% struggle to provide timely and secure data access to authorized users. Data leaders must strike a balance between security and access to fully capitalize on AI investments.

• The Impact of Data Access Issues
  A significant 64% of data leaders report that data access challenges are hurting the ROI of their data platforms. These issues are causing downstream effects such as missed internal goals (31%), lost revenue (30%), and collaboration roadblocks (30%).

Complex Access Controls Are Hindering AI Implementation

For AI adoption to succeed, organizations need seamless and secure access to quality data. However, 55% of data leaders feel their current data security strategy isn't keeping up with the evolving demands of AI, up from 50% in the previous year. AI implementation is further hindered by:

• 46% reporting difficulties in integrating AI with existing systems
• 39% citing a shortage of skills to manage AI systems
• 29% mentioning complex data access controls

These challenges are slowing AI adoption and putting organizations at a competitive disadvantage.

Strategies for Balancing Data Access and Governance

To achieve AI success, organizations must find a balance between access, agility, governance, and security. Key strategies being implemented include:

1. Data Monitoring Systems (82%)
   Enhanced data protection through real-time understanding of data usage and storage.

2. Additional Cloud Platforms (76%)
   To scale with growing data volumes, flexible platforms are being adopted, ensuring the right teams have access to the right data.

3. Internal Data Marketplaces (68%)
   Defining roles, rules, and capabilities that lead to successful AI implementation and data governance.

As data demands grow and AI adoption accelerates, data leaders must rethink their approach to data access and governance. By implementing strategies such as data monitoring systems, flexible cloud platforms, and internal data marketplaces, organizations can strike the right balance between securing data and enabling access, ensuring AI success and business growth.