Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Everyone’s racing to build copilots right now. But making an agentic AI that feels like a trusted teammate—one that understands context, acts safely, and simplifies complex workflows—is harder than it looks. While building Nyx, our agentic AI copilot for security teams, our team spent a lot of time thinking about how to make her an effective team member - skilled and trustworthy.

Shadow AI refers to the unauthorized or unmonitored use of AI tools (like ChatGPT, Copilot, Claude, and Gemini) by employees in the workplace. It’s now one of the fastest-growing data exfiltration vectors. Employees are pasting source code, customer or patient data, contract terms, and even M&A info into gen AI tools, often without realizing the risk. And many legacy DLP tools are still catching up.

Your organization runs on data. But do you actually know where it goes every day? Between Slack messages, Google Drive shares, AI assistants, and browser uploads, your sensitive data is constantly moving: Every one of these moments is a data exposure risk.

For years, data loss prevention has been synonymous with pain: These legacy approaches treat every potential incident the same, forcing teams to waste time deciphering what really happened and why it matters. Meanwhile, real risks slip through the cracks because no team can manually keep up.

As AI transforms the security landscape, security leaders face a critical decision.

Sensitive data is zooming across dozens of platforms every day, from Slack to email to gen AI platforms and many more sources. We all need this connectivity to stay productive, but the connectivity also creates countless opportunities for data to slip through the cracks. A single misplaced email attachment can end up exposing confidential information in a matter of seconds.

The rise of generative AI has fundamentally changed how we work, create, and collaborate. But as organizations rush to integrate AI tools into their workflows, they're inadvertently creating entirely new categories of data risk that traditional security measures weren't designed to handle.

Organizations investing in Microsoft 365 E5 licensing expect enterprise-grade email protection. Yet despite premium security features, customer feedback reveals persistent challenges with Microsoft Purview DLP across Exchange Online environments. Microsoft deployment specialists report seeing clients deploy Purview on their own, discover a wealth of false positives, and turn off the policies or set them to audit mode. Policies never become useful.

In our previous blog (Beyond Attachments: How Email Becomes Your Biggest Data Exfiltration Vector), we exposed the critical gaps in standard email data loss prevention (DLP) tools that allow data exfiltration to continue despite significant investment in native controls. Organizations that have implemented targeted solutions to address these gaps report dramatic improvements in their security posture. Here's what comprehensive email DLP actually looks like in practice.