How AI and Orchestration Unlock DLP's True Potential

When DLP first came to market in the mid-2000s, it was hailed as security’s “next big thing” - the tool that promised to protect sensitive data, curb insider risk, and ease compliance headaches. Yet for many organizations, it has fallen short of that promise.

Early tools relied on resource-intensive inspection and manual, rule-based policies (regex, dictionaries, classification labels). They were built for endpoints and perimeter defenses, with on-premises scanning and a narrow focus on known data types and sanctioned services. The model was reactive and produced volumes of low-fidelity alerts because it lacked user intent and data-flow context across cloud and SaaS.²

The outcome was costly: overwhelming alerts, endless policy tuning, and wasted resources that drove many organizations to scale back or abandon DLP altogether. This disconnect is striking when you consider that 76% of enterprises still rely on DLP as a core capability¹. As Forrester’s Heidi Shey memorably puts it, “DLP is the craft glitter of cybersecurity: sparkly and full of promise for what you can achieve with it - and a potential mess that gets stuck in every crevice.^*1 DLP is indeed everywhere, but too often it has created more operational burden than risk reduction. Gartner notes that projects not tied to broader business initiatives often reflect “an absent or immature data security governance program” - one reason so many programs stall.

The AI Shift in Data Loss Prevention

DLP today is evolving. With AI and data context, modern solutions can detect real risks more accurately, reduce alert volume, and enforce policies with far less manual effort. But not all AI is created equal. Too often, what’s marketed as AI is really just a natural language interface - useful for queries, but not meaningfully improving detection or automation.

The real breakthrough comes when AI is embedded directly into the DLP intelligence layer. Instead of relying only on content inspection, modern systems analyze business context, user behavior, and data movement patterns to make better decisions. For example, AI can distinguish when a finance employee sending divestiture documents to an approved advisor is legitimate versus when sending that same data to a personal email or competitor domain is a violation. 

By applying risk-based logic at scale, AI enables triage to be streamlined, policies to be created automatically, and enforcement to continuously improve. These are capabilities that aren’t feasible with manual tuning. Industry analysts echo this shift. Gartner observes that “AI and ML are reshaping DLP by reducing reliance on static classification and enabling adaptive, context-aware controls.”^*2 Forrester similarly points out that “modern DLP considers both content and context, enabling more confident risk-based responses.”^*1‍

What is DLP Orchestration?

DLP controls aren’t confined to a single product. They’re embedded in many different security products: email gateways, endpoint agents, enterprise firewalls, CASBs, SaaS-native tools, web gateways, and even newer categories like browser or AI security. 

Organizations can enable DLP within these tools to block unauthorized data movement across the user-initiated channels of exfiltration: email, endpoints, networks, cloud, and web.

The problem is that each of these tools runs in isolation. They generate their own alerts, enforce their own policies, and rarely share context. This fragmentation has made DLP noisy, inconsistent, and hard to manage at scale - compounding the challenge of analyzing alerts, tuning policies, and maintaining any level of consistency.

DLP orchestration is an intelligence layer that sits on top of existing DLP tools. It connects them through APIs, centralizes alerts and policies, and applies AI to automate triage and response. As Francis Odum of SACR puts it, “The future isn’t about replacing existing tools, but enhancing them with an AI-powered ‘policy brain.’”

Cyera’s Omni DLP is the first implementation of this model. Here’s how it delivers DLP orchestration in practice:

• Unifies detection across DLP tools by centralizing alerts and policy management
• Automates triage by aggregating and summarizing every alert, filtering benign activity, and elevating critical incidents - all powered by AI
• Improves policy performance by identifying false positives, tracking accuracy over time, and recommending rules changes to strengthen coverage and enforcement

The Role of DSPM

DLP orchestration strengthens how organizations protect data in motion and data in use, but not all  sensitive data comes across the wire. Large volumes of it remain at rest, often unseen or unclassifed by traditional DLP.

This is where data security posture management (DSPM) adds tremendous value. DSPM discovers sensitive and risky data wherever it lives, identifies who has access, and maps how it flows. It provides a scalable, automated way to uncover exposures that would otherwise require painful, manual engagement with business stakeholders.

When paired with orchestration, DSPM extends DLP’s reach. The same data DSPM identifies at rest can inform and strengthen DLP detection and enforcement policies across your existing DLP stack. Together, DSPM and DLP create a self-reinforcing cycle that continuously improves accuracy, coverage, and overall data security posture.

Traditional DLP wasn’t sustainable before - and now, with AI-driven workloads accelerating and data sprawling across systems, the challenge has only compounded. Gartner predicts that by 2027, 70% of CISOs will adopt a consolidated approach to address both insider risk and data exfiltration use cases². Without orchestration, organizations are left with blind spots and a flood of uncorrelated alerts. They also lack a clear way to see how the business is using data, identify what’s truly critical, and enforce protections with precision.

Turning Orchestration into Outcomes  

Cyera Omni DLP is designed to meet organizations wherever they are.

For organizations with abandoned, immature, or no DLP program, Omni DLP establishes protections quickly. Suggested policies and automated alert analysis deliver outcomes in weeks rather than months.

For organizations with established DLP programs, Omni DLP connects to disparate tools and enriches alerts with context. This reduces alert fatigue, sharpens detection accuracy, and helps teams focus on critical incidents. It also evaluates existing DLP policies to identify where controls are overblocking or under-enforcing, enabling teams to tune policies for both precision and coverage.

Omni DLP doesn’t replace what you already have. It leverages existing DLP investments by orchestrating across tools, ensuring policies are applied consistently and alerts are prioritized with the right context.

Proof in Action

One enterprise struggled with a legacy DLP tool that flagged nearly every outbound email as risky. The team was overwhelmed with false positives. Legitimate customer communications were blocked alongside real violations, making it nearly impossible to spot true risks.

With orchestration in place, the difference was immediate. The system surfaced repeated incidents of an employee sharing sensitive information with unauthorized third parties - issues that had been buried in noise before - while allowing legitimate messages to flow through without disruption. 

Within days, the security team had accurate policies that replaced months of failed manual tuning.

Across deployments, organizations consistently report:

• 95% fewer inaccurate alerts
• 90% less manual effort for policy management and triage
• Single-pane visibility across email, endpoints, cloud, and web 

Agentless onboarding enables these outcomes in minutes, not months, by connecting directly through APIs.

The Urgency of Now

With 72% of enterprises planning to increase investment in DLP capabilities over the next year¹, security leaders are determined not to repeat past failures. Many are pairing visibility with enforcement - combining DSPM to map sensitive data at rest with DLP to protect it in motion. 

Together, they reduce wasted effort, improve accuracy, and unify posture with protection.

Cyera Omni DLP provides the missing link: making data protection effective, scalable, and sustainable in today’s environment. Whether you’re starting fresh, restarting after failed attempts, or modernizing an existing program, Cyera delivers with AI-driven automation, orchestration, and contextual intelligence. It reduces noise, accelerates time-to-value, and fulfills the long-standing promise of data loss prevention.

Ready to see how it works? Take a Guided Tour of Omni DLP

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1. Forrester, The Guide to Modern Data Loss Prevention, Heidi Shey, June 2025
2. Gartner, Market Guide for Data Loss Prevention, Andrew Bales et al., April 2025

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