Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Enterprise data has become nomadic. What once lived safely behind corporate firewalls now travels across dozens of cloud applications, gets copied into collaborative documents, flows through AI tools, and transforms as employees work from coffee shops, home offices, and airport lounges.

Back to Table of Contents Data Loss Prevention (DLP) plays a crucial role in protecting information such as personal, financial, and confidential business data from accidental exposure, malicious attacks, or insider threats. As businesses increasingly rely on cloud services and remote workforces, implementing effective DLP is essential to safeguard sensitive data, comply with regulatory requirements, and reduce financial and reputational risks.

The debate over data sovereignty spurred by the U.S. CLOUD Act is intensifying. On June 10, 2025, France’s Senate held a hearing on the role of procurement in data sovereignty, where Anton Carniaux, Director of Public and Legal Affairs at Microsoft France, testified. He stated he could not guarantee that data from French citizens would not be shared with U.S. authorities without explicit authorization from French authorities.

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.

With the abundance of compliance requirements that organizations must comply with, such as HIPAA, PCI and GDPR to name a few, there is an increasing need for organizations to properly classify sensitive data and safeguard it accordingly. Identifying and classifying sensitive data is a crucial initial step in an organization’s compliance journey.

*According to Gartner, by 2026, over 80% of enterprises will have used generative AI APIs or deployed GenAI-enabled applications, up from less than 5% in 2023. This rapid adoption introduces a new and complex attack surface. The adoption of artificial intelligence is no longer an option, it’s an operational inevitability.

We’re thrilled to announce that Netwrix Access Analyzer has been named a Visionary in Data Security Posture Management (DSPM) at the 2025 Global InfoSec Awards, presented by Cyber Defense Magazine during this year’s RSA Conference. This recognition underscores Netwrix’s commitment to pushing the boundaries of what modern data security solutions can do — especially in a world where sensitive data sprawls across cloud, on-premises and hybrid environments.