Zero Networks has launched AI Segmentation, a new set of capabilities designed to give enterprises direct control over how artificial intelligence operates within their environments. With this release, the company aims to move beyond simple visibility and address growing risks tied to AI adoption, including uncontrolled agent activity, rapid lateral movement, and compliance challenges.
As organizations increasingly integrate AI into daily operations, the attack surface continues to expand. In fact, recent telemetry from Zero Networks shows that AI usage is already present in nearly 80% of enterprise environments. Moreover, tens of thousands of endpoints are actively interacting with platforms such as ChatGPT, Gemini, and Claude. At the same time, the surge in API calls reaching hundreds of thousands signals a sharp rise in backend automation and AI-driven processes.
However, despite this rapid adoption, most organizations are not enforcing meaningful controls. As a result, very little AI-related access is being restricted, creating a significant gap between awareness and actual security enforcement.
To close this gap, Zero Networks introduces AI Segmentation as a comprehensive approach to managing AI risks. First, the platform enables granular control over AI access at the network level. This means organizations can determine which AI tools employees and systems can use, while automatically blocking unauthorized or shadow AI services.
In addition, the solution provides full visibility into AI agents operating within the environment. Security teams can identify what these agents are accessing and how they communicate, while enforcing strict identity-based controls and least-privilege access across all interactions.
Another critical capability focuses on preventing AI-driven lateral movement. By eliminating unnecessary connectivity between systems, the platform stops threats from spreading across the network. Consequently, both malicious actors and compromised AI agents are prevented from accessing sensitive resources.
Furthermore, Zero Networks enhances protection for large language model (LLM) environments by restricting access at the network layer. This helps defend against risks such as data poisoning, hidden backdoors, and unauthorized system interactions.
“Most vendors are out there selling AI hype. We’re not. Zero Networks puts enterprises in control of AI full stop,” said Benny Lakunishok, CEO and Co-Founder of Zero Networks. “This isn’t just visibility. It’s real control. Real-time, deterministic control over AI agents, combined with AI-driven visibility and an integrated Compliance and Risk Engine that continuously scores risk, maps activity to frameworks like NIS2 and CIS Benchmarks, and flags what actually matters. While others are still watching dashboards, Zero is enforcing outcomes stopping lateral movement and preventing threats from becoming business problems.”
In parallel, the company has embedded AI into its compliance and risk engine. This allows security teams to analyze network activity using natural language queries while continuously mapping behavior against regulatory frameworks such as NIS2 and CIS Benchmarks. As a result, organizations can identify critical risks in real time and maintain compliance more effectively.
Ultimately, Zero Networks’ AI Segmentation reflects a broader shift in cybersecurity strategy. As AI adoption accelerates, enterprises must move beyond monitoring and take active control of how AI systems interact with their infrastructure. By combining visibility, enforcement, and automation, the new platform aims to help organizations secure AI-driven environments with greater precision and confidence.
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