Organizations are rethinking their data security stack because fragmented tools create blind spots, complexity, and extra workload for already stretched teams. As data volumes grow and AI adoption accelerates, security leaders need a single, consistent way to see and protect their data.

According to the 2026 Data Security Index, 88% of surveyed decision-makers expect their data security and compliance budgets to increase in the next year, and they are directing that investment toward consolidation and integration. In fact, 86% of surveyed leaders say a comprehensive platform with integrated solutions outperforms managing multiple best-in-breed tools that must be manually integrated and maintained.

Key reasons for this shift include:

• Better visibility: Poor integration, lack of a unified view across environments, and disparate tools are top visibility challenges. A unified platform helps teams see where data lives, who accesses it, and how it’s protected.
• Simpler operations: Leaders want to reduce vendor sprawl. One security leader put it plainly: instead of managing 15 tools from 15 vendors, they’d rather work with fewer vendors, each covering more ground.
• Stronger risk detection and response: Consolidation improves threat detection, speeds response, and reduces false positives by correlating signals across workloads.

In practice, this is driving adoption of Data Security Posture Management (DSPM) strategies that unify visibility, continuous risk assessment, and policy enforcement across data environments. By embedding DSPM into their core operations, organizations are moving from reactive, fragmented efforts to a more cohesive, proactive data security strategy that can support responsible AI adoption.

GenAI is reshaping how employees work, but it’s also changing the risk profile for data security teams. Employees are eager to use AI to boost productivity, often faster than governance can keep up.

According to the 2025 Work Trends Index, the majority of global knowledge workers surveyed report using AI, and more than 70% say they are bringing their own AI tools to work. This “bring your own AI” trend means employees frequently turn to consumer-grade tools or log in with personal accounts, outside corporate controls.

The impact on security is already visible:

• 32% of data security incidents reported by surveyed organizations involve the use of GenAI tools.
• 35% of organizations expect incident volumes to rise in the coming year due to GenAI usage.
• Use of personal credentials for GenAI at work has increased by 5 percentage points year over year.
• Use of personal devices to access GenAI for work has grown by 9 percentage points year over year.

Security leaders are less worried about GenAI as a technology and more about where and how employees use it. Unsanctioned tools and personal accounts can expose confidential data to external systems, with little visibility into where that data goes.

In response, nearly half of surveyed organizations are tightening controls. 47% are implementing specific GenAI controls in 2025, up from 39% the previous year. Their top priorities include:

• Preventing sensitive data from being uploaded into GenAI tools.
• Training employees on secure GenAI usage.
• Detecting anomalous user activity and identifying risky users.
• Identifying sensitive data being uploaded to or generated by GenAI tools.

The goal isn’t to slow down AI-driven productivity. Instead, organizations are steering employees toward sanctioned AI tools, reinforcing safe practices, and building clear approval processes so they can enable GenAI use while keeping data protected.

Security teams are increasingly using GenAI not just to secure AI, but to enhance their entire data security program. GenAI agents and automation are helping teams handle more data, detect risks faster, and reduce manual work.

The 2026 Data Security Index shows strong momentum:

• 82% of surveyed organizations report they have developed plans to use GenAI within their data security operations, up from 64% in 2024.

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

• Discovering sensitive data across environments.
• Detecting critical data security risks earlier.
• Investigating potential incidents more efficiently.
• 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 that GenAI is helping them:

• Automate routine tasks and reduce manual overhead. One security executive estimated at least a 40% reduction in manual overhead around their data security program and more than a 50% improvement in processes.
• Adapt to evolving risks by continuously observing, learning, and recommending policy changes based on far more data than manual processes could handle.
• Free up specialists to focus on higher-value, strategic work instead of repetitive investigations.

Human oversight remains essential. Organizations are pairing GenAI agents and automation with expert review to ensure decisions are sound and aligned with policy. When combined with integrated platforms and DSPM, GenAI is helping security teams reimagine how they manage data risk at scale—making it easier to keep pace with both growing data volumes and rapid AI adoption.