The DLP Do-Over: Learning From Gen AI Mistakes

For more insights on moving beyond legacy DLP, visit the Zscaler Retire Legacy DLP Portal

I promise—this isn’t another blog about Generative AI. Don’t get me wrong, I have nothing against GenAI. It’s just that what we’re experiencing now is a perfect example of a cycle we’ve seen play out in the industry time and time again.

This is a blog about problem solving—or, more specifically, about the price we pay for solving them (with GenAI as today’s trending solution). Let me explain.

IT is excellent at solving problems. Typically, a solution arrives in the form of a point product that someone is eager to sell. The promise of unlimited power through visibility and control is hard to resist. Thanks to that shiny, new tool, the problem usually gets fixed, and most of the boxes are checked. We feel whole again. That is...until the next technological challenge arises.

But what is the real cost? Beyond the upfront sticker price, the hidden cost often doesn’t reveal itself until years later. Only then do you look back at a stack of security approaches bolted onto your environment and see the toll it has taken. The hidden price emerges as overlap, complexity, integration headaches, and operational inefficiencies. And yet, those costs are rarely considered at the start.

Legacy DLP: A Road Paved with Potholes

Now, let’s talk about how this impacts data security. First, I want to be clear—legacy approaches to Data Loss Prevention (DLP) weren’t bad solutions for their time. For the past 20 years, DLP has been the go-to method for addressing specific data security challenges. This one-problem-at-a-time process did its job: network visibility? Check. Endpoint control? Done. Cloud visibility? Tack that on too.

But here’s the issue—it’s like continuously patching potholes on an aging road. It helps for a while, but eventually the road traveled becomes far too difficult to navigate. And frankly, a lot of this is outside your control. Consider this: most CISOs probably inherited at least 60% of their tech stack when they joined their current company. This is exactly why the term "technical debt" exists.

And there’s a bigger question—how can a system architected 20 years ago keep up with today’s threats, like risks posed by GenAI or agentic, adaptive AI? The short answer: it can’t. Here’s what you’re likely up against:

• Alert Overload: So many alerts, so little time.
• Policy Chaos: Fragmented DLP policies that feel like they require a master’s degree to manage.
• Escalating Costs: Between hardware refreshes and scaling needs, it’s a financial treadmill.
• Endless Admin Work: Patching, managing security updates, and relying on an overworked support team.

If this sounds familiar, you’re not alone.

The SSE Shift: Scalability, Agility, Control

So, is there a better way? Yes—and this is precisely why embracing the cloud has been so transformative. The cloud offers scalability, agility, and performance that legacy approaches simply cannot match. Enter Gartner's Security Service Edge (SSE).

Designed as a Swiss Army knife for security, Gartner’s SSE excels in many areas, but its true strength lies in its flexible architecture. With centralized, high-performance inline cloud inspection and a robust API framework, SSE is built to address a wide range of security needs while providing the flexibility to support future innovation and growth

From tackling cyber threats and VPN limitations to solving data security challenges, SSE has become the go-to strategy for organizations looking to eliminate the technical debt we’ve been talking about.

While I won’t go too deep into the full scope of Gartner’s SSE here, it’s important to set the stage for what comes next—the exciting part: securing your data against all forms of data risk.

From Legacy to Leading: Your Modern Data Security Checklist

This brings us to the reason we’ve all gathered here: how to retire legacy DLP in favor of a modern architecture. You’re building for the future of data security, so we want to get this right. To ensure success, let’s explore a few key conceptual pillars of data security that are critical for building a robust and airtight data protection strategy.. These are non-negotiable—compromising on them could jeopardize your long-term outcomes:

Pillar 1: Bring Classification into Focus using AI

The saying holds true: you can’t protect what you can’t see. In today’s hyper-connected world, data is dynamic—it moves everywhere, and it moves fast. Achieving visibility and mapping where your data resides are foundational steps in building a robust data security strategy.

The ability to classify sensitive data wherever it exists—whether in IaaS, SaaS, on-premises, or endpoints—is critical. To stay ahead, you need to adopt innovative AI-powered classification solutions that go beyond traditional methods like regex and keyword matching. Approaches like LLM Classification can now find sensitive data that could never be found before.  AI-driven classification is the future, delivering deeper insights and adaptive protection as your data evolves.

Pillar 2: An Inline Defense, Powered by Cloud Proxy

Strong data security requires inline proxy inspection for data in motion—don’t let anyone tell you otherwise. API-based data security is important for controlling data at rest, but it must be paired with an inline proxy to ensure visibility and control over data in motion.

An inline cloud proxy with SSL inspection unlocks powerful capabilities around real-time data blocking, application control, visibility into Gen AI prompts, user behavior insights, and more. Better yet, when delivered from the cloud, you get the best of both worlds: strong visibility and control combined with agile, scalable inspection—without the burden of managing, maintaining, or patching it yourself.

It’s important to note that building a cloud-delivered, scalable inline proxy is no small feat. Choose proven proxy vendors that have been tested by millions of users across the world’s largest enterprises. Skipping this due diligence can be a one-way ticket to business-impacting outages—something nobody wants.

Pillar 3: Proactive Risk Reduction from robust API’s

It’s also important to focus on finding and fixing risks that may be hiding in plain sight across your ecosystems. Many of the largest breaches we’ve seen in the past have been caused by a hidden misconfiguration that allowed adversaries to walk in through the back door. These risks are avoidable—provided you have the right tools in hand.

Enter the posture management capabilities of Data Security Posture Management (DSPM) and SaaS Security Posture Management (SSPM). Designed to hunt and destroy dangerous misconfigurations, these approaches leverage APIs across your cloud ecosystem to catalog sensitive data, prioritize where it resides, and identify which environmental risks are leaving it exposed.

What should you look for in a posture management solution? Big hint: it’s our next Pillar.

Pillar 4: Centralize DLP, because everything uses it.

Let’s play a game: list all the data security approaches that rely on DLP to get their job done. Inline, Endpoint, Email, DSPM, CASB/SSPM, GenAI Security, BYOD.  Now picture a piece of data traveling through all these locations. Can you imagine having different DLP verdicts for the same data across each one? And what if you need to secure a custom piece of data—how many different consoles would you have to touch to set up the inspection logic? Hopefully you get my point.

Centralizing your DLP around one central inspection engine is key to building a streamlined, efficient data security platform. This is one of the major reasons Gartner retired the DLP Magic Quadrant and rolled data security and DLP capabilities into Gartner's SSE. The centralization of DLP technology makes life so much easier. Take their lead and make this a priority.

Pillar 5: Supersize your Channel Support

Lastly, look for a platform that supports all the data loss channels you need to secure—and then some. As you grow with your SSE platform, you’ll want flexibility and scalability to add more protecting power to your strategy. Start with Gen AI, Web DLP, and DSPM/SSPM. Then, when you’re ready, add Endpoint DLP to streamline your device agent footprint. Throw on Email for more consistent DLP alerting, and bring in BYOD security if unmanaged devices are a pain point. The possibilities keep adding up.

The best part about adopting an SSE platform with this level of flexibility is that you can grow into it incrementally, retiring legacy solutions as contracts expire. It’s a smart, efficient way to reduce technical debt and lean into a more streamlined approach.

Ready for a DLP Do-over?

Gen AI has emerged as both a blessing and a curse. While brimming with tremendous potential, it also acts as a revealing mirror, exposing data security challenges that just can’t be ignored:

• Do I have the agility to scale protection to meet new AI challenges?
• Can I find and secure all my sensitive data, wherever it resides?
• Is my current architecture modern enough to handle today’s demands?
• Are operational costs and complexity holding me back?

These aren’t just questions—they’re roadblocks standing between organizations and the comprehensive data security they need. Solving them is no trivial task, but Zscaler has been helping enterprises tackle these challenges head-on with its purpose-built data security platform.

Zscaler’s approach to data protection has empowered thousands of organizations to elevate and transform their data security programs:

• Groundbreaking Data Classification powered by innovative AI-driven LLM approach
• Proactive risk mitigation with fully integrated DSPM
• Unparalleled inline defenses backed by the industry’s leading inline proxy
• Broadest channel coverage you can get in a platform all around a centralized DLP
• Powerful Workflow Automation that drastically accelerates operational response

The result? A truly comprehensive, integrated platform that centralizes DLP, streamlines operations, reduces cost and complexity, and is future-ready for whatever data security can throw at you.

Taking It Further: Resources to Explore

If you’d like to see what all the fuss is about, you’ve got plenty of options to explore. Whether you’re ready to dive in or just curious to learn more, we’ve got the resources to help you take that next step:

• Learn More - Retire Legacy DLP Portal
• Save $2.1M Annually - IDC Zscaler Study
• Take the Next Step - Schedule a Demo or Contact Us

Let’s give your data security the upgrade it deserves!