Traditional DLP will not make you compliant. Here’s why a file-centric approach to data protection is now essential.

If you are a CISO or a security leader, you have probably been here before: you invested in DLP solutions, defined policies, trained users, yet sensitive data keeps leaking. Not because your team lacks skills, but because the traditional DLP model is simply inadequate for the world we operate in today.

In this article, I want to share a perspective I have been developing for years, one that led me to completely rethink how data protection should work. I call it DLP 2.0 - not an incremental evolution, but a true paradigm shift.

The structural problem of traditional DLP

Most DLP solutions are built on the same assumption: data is vulnerable and must be protected “on the way out.” This is a perimeter-based model, born in an era when data lived on corporate servers and exfiltration channels were few and controllable.

This approach relies on three pillars: manual document classification by users, policies that block outbound channels (email, USB, cloud, web), and continuous monitoring of data traffic. In theory, it works. In practice, it doesn’t.

According to the Verizon Data Breach Investigations Report 2024, 68% of breaches originate from human error, misconfigured permissions, or unintentional exposure. Not from sophisticated attacks, but from everyday actions: a wrong share, a file uploaded to the wrong tool, a link sent to the wrong recipient.

Traditional DLP cannot intercept these scenarios because they are not “attacks.” They are legitimate actions performed incorrectly. And when you try to block everything, the result is thousands of false positives, frustrated users, administrators forced to bypass controls, and operational costs that outweigh real security benefits.

A context traditional DLP was never designed to handle

Today, sensitive files constantly move across cloud and hybrid environments, email and enterprise chat, collaboration tools like Teams, Slack, Notion, and increasingly generative AI platforms. This is where control is lost.

Then there is Shadow IT - and now Shadow AI. Users adopt unmanaged tools not out of malice, but because they are faster, easier, and more effective than corporate ones. Blocking them slows down the business. Allowing them means losing control.

The global average cost of a data breach reached $4.88 million in 2024. These numbers send a clear message: the current model is not working.

My proposal: DLP 2.0

From this analysis comes what I call the DLP 2.0 vision. The core idea is simple, yet radical: what if data were never vulnerable?

This new paradigm completely overturns traditional logic. You don’t protect the exit points, you protect the file at birth. You don’t chase every possible channel, you make data intrinsically secure. You don’t ask users to “do security,” you remove that burden entirely.

In the DLP 2.0 model, data itself becomes the security perimeter. The approach I propose is built on four fundamental pillars.

1. Immediate encryption at creation

Files are encrypted the moment they are created. There is no vulnerable window. This eliminates, at the root, the problem of data being exposed even temporarily.

2. Automated classification powered by private AI

Private AI analyzes content and automatically applies security tags and operational policies. No human input is required, eliminating the classification errors that plague traditional DLP.

3. Persistent and transparent encryption

Files can be synchronized on user devices and used normally with familiar applications. But they remain encrypted and unusable outside authorized contexts. The user experience stays the same. Security does not.

4. Shadow IT made irrelevant

Even if a file is copied, sent via personal chat, or uploaded to unmanaged tools, the content remains unreadable. There is no longer a need to block legitimate work tools: the data itself carries protection wherever it goes.

What this really changes for a CISO

This paradigm shift delivers concrete, measurable outcomes. Dependence on user training is dramatically reduced: data is protected at the source, without requiring perfect behavior. Critical human errors decrease because mistakes no longer have catastrophic consequences.

Compliance becomes easier: native encryption, full traceability, and continuous file-level control support alignment with GDPR, NIS2, and sector regulations. Audits become simpler because you always know who accessed what, when.

Operational costs go down: fewer policies to manage, fewer false positives to investigate, fewer manual interventions for IT and security teams. And people keep working with familiar tools, without invasive blocks or slowdowns.

DLP 2.0 in practice

This vision is not just theory. With CyberGrant, these principles have been translated into a concrete solution, designed for organizations that need to protect sensitive data without sacrificing productivity.

The technology natively implements a file-centric approach: automatic encryption at creation, AI-driven classification, persistent encryption across devices, and the neutralization of Shadow IT. Files remain usable only within authorized contexts.

If you are evaluating how to meet compliance requirements, whether GDPR, NIS2, or sector-specific regulations, I encourage you to explore this approach. It’s not about adding another control layer, but about rethinking the problem from its foundations.

Traditional DLP has reached the end of its lifecycle. Not because protecting data is the wrong goal, but because chasing outbound channels no longer scales in a cloud-first, AI-driven, distributed world.

DLP 2.0 offers an alternative: protect data at birth, make it intrinsically secure, and eliminate dependence on human behavior. It is a shift in mindset before it is a shift in technology. And I believe it is the only viable path for organizations that truly want to protect their data today.