Organizations are rethinking their data security stack because fragmented tools create **visibility gaps, complexity, and higher risk**. From the 2026 Data Security Index research:

• 88% of surveyed decision-makers expect their data security and compliance budgets to increase, and a key focus is consolidating tools.
• 86% of surveyed leaders say a comprehensive platform with integrated solutions outperforms managing multiple best-in-breed tools that must be manually integrated.

Security leaders report three recurring challenges with fragmented tools:

• Poor integration with data security management platforms
• Lack of a unified view across environments
• Disparate tools with no centralized dashboard

This makes it hard to connect insights, correlate events, and maintain consistent protection. In response, organizations are:

• Consolidating vendors and tools to simplify operations
• Adopting integrated platforms that bring together visibility, protection, detection, and investigation
• Embedding Data Security Posture Management (DSPM) to unify visibility, continuous risk assessment, and policy enforcement

The result is a more cohesive data security strategy that helps teams:

• Improve threat detection and response
• Gain better visibility into data risks across workloads
• Reduce manual overhead and tool sprawl

In short, unified platforms help turn a complex, siloed data landscape into something more manageable, actionable, and aligned with responsible AI adoption.

Generative AI is reshaping how people work, but it is also introducing new data security pressures. According to the 2025 Work Trends Index and the 2026 Data Security Index:

• The majority of global knowledge workers surveyed report using AI.
• More than 70% say they are bringing their own AI tools to work.
• 32% of data security incidents reported by surveyed organizations involve the use of GenAI tools.
• 35% of organizations expect a higher volume of incidents in the coming year due to GenAI usage.

Two behaviors are driving much of the concern:

• Using personal credentials to access GenAI for work has increased by 5 percentage points year over year.
• Using personal devices to access GenAI for work has grown by 9 percentage points year over year.

These patterns can push confidential data outside corporate protections, making it harder to see where data goes and who can access it. To respond, organizations are:

• Implementing specific GenAI controls: 47% of surveyed organizations are doing this in 2025, up from 39% the previous year.
• Prioritizing controls that:
  • Prevent sensitive data from being uploaded into GenAI tools
  • Train employees on secure GenAI use
  • Detect anomalous user activity and identify risky users
  • Identify sensitive data being uploaded to or generated by GenAI tools
• Blocking unsanctioned GenAI tools while steering employees toward approved, governed options.

The goal is not to slow down AI-driven productivity, but to reimagine AI usage with guardrails—combining visibility, clear policies, and employee education so teams can use GenAI confidently without exposing sensitive data.

Security leaders are increasingly using GenAI not just as a risk to manage, but as a capability to strengthen their own programs. The 2026 Data Security Index highlights a clear shift:

• 82% of surveyed organizations report they have developed plans to use GenAI within their data security operations, up from 64% in 2024.
• 92% of surveyed decision-makers say they feel confident using GenAI to strengthen data security.

Teams are applying GenAI across both proactive and reactive use cases, including:

• Discovering sensitive data across environments
• Detecting critical data security risks
• Investigating potential incidents more quickly
• Assessing the security posture of data environments
• Securing data environments with more precise controls
• Fine-tuning data security policies based on real-world patterns

Leaders report tangible efficiency gains. One senior security executive noted that GenAI helped:

• Reduce manual overhead around their data security program by about 40%
• Improve processes by more than 50%

By automating routine tasks and analyzing more data than manual methods can handle, GenAI helps teams:

• Scale investigations and monitoring without equivalent headcount growth
• Adapt faster to evolving risks
• Free up specialists for higher-value, strategic work

Human oversight remains essential, but GenAI agents and automation are helping security teams reimagine how they manage data risk—moving from reactive, manual workflows to more proactive, data-driven operations.