Why are organizations moving from fragmented tools to unified data security platforms?
Organizations are moving from fragmented tools to unified data security platforms because complexity and blind spots have become real risks.
According to the 2026 Data Security Index, security teams are struggling with:
- Poor integration between tools
- Lack of a unified view across environments
- Disparate tools with no centralized dashboard
These silos make it harder to connect insights, correlate events, and maintain visibility across workloads. As a result, leaders are prioritizing consolidation and integrated platforms that:
- Improve threat detection and response
- Make it easier for data security teams to manage and maintain tools
- Provide better visibility into data risks across environments
In fact, 86% of surveyed decision-makers agree that a comprehensive platform with integrated solutions outperforms managing multiple best-in-breed tools that must be manually integrated and maintained. This is also driving adoption of Data Security Posture Management (DSPM) strategies, which unify visibility, continuous data risk assessment, and policy enforcement across data environments.
Ultimately, organizations see unified platforms and DSPM as a way to move from reactive protection to proactive data risk management, while reducing operational overhead for already stretched security teams.
How is generative AI changing data security risks and controls at work?
Generative AI is reshaping how employees work, but it is also changing the data risk profile inside organizations.
On the usage side, the 2025 Work Trends Index shows that most global knowledge workers are using AI, and more than 70% say they are bringing their own AI tools to work. This “bring your own AI” behavior often happens outside corporate controls, using personal credentials and devices. Surveyed decision-makers report:
- Employees using personal credentials to access GenAI for work has increased year over year
- Employees using personal devices to access GenAI for work has also grown year over year
These patterns matter because, according to surveyed organizations, about 32% of data security incidents already involve the use of GenAI tools, and 35% expect incident volumes to rise due to GenAI usage.
In response, organizations are tightening controls while still trying to support productivity. Nearly half (47%) of surveyed organizations are implementing specific GenAI controls, up from 39% the previous year. Their top priorities include:
- Preventing sensitive data from being uploaded into GenAI tools
- Training employees on secure use of GenAI tools
- Detecting anomalous user activity and identifying risky users
- Identifying sensitive data being uploaded to or generated by GenAI tools
Many leaders are also steering employees toward sanctioned, enterprise-grade AI tools and blocking unsanctioned ones. The goal is not to slow innovation, but to ensure GenAI is used in a way that protects sensitive data, maintains compliance, and gives security teams the visibility they need.
How are organizations using GenAI to strengthen their data security programs?
Organizations are increasingly using generative AI not just as a productivity tool for the business, but as a core capability inside their data security programs.
The 2026 Data Security Index shows strong momentum:
- 82% of surveyed organizations 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
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 data security incidents
- Assessing the security posture of data environments
- Securing data environments and fine-tuning data security policies
Leaders report that GenAI agents and automation are helping them:
- Automate routine security tasks and reduce manual overhead
- Analyze far more data than traditional tools or manual processes could handle
- Adapt more quickly to evolving risks
- Free up security staff to focus on higher-value, strategic work
Some organizations estimate that they have reduced manual overhead in their data security programs by at least 40% and improved processes by more than 50% by using GenAI to automate routine tasks and continuously learn from new risks.
At the same time, human oversight remains essential. Organizations are pairing GenAI-driven insights with expert review, ensuring that AI agents and automation scale security operations without sacrificing judgment, context, or accountability.
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