Shadow AI, prompt-level data leakage, agent-to-agent traffic — here’s what security and network executives are actually prioritizing around AI governance, and the 4 questions every platform must answer.
Thirty-five percent of organizations surveyed for Versa’s inaugural Annual State of SASE + AI Report, “The Cost of Complexity suffered a security breach in the past year that was directly caused or worsened by poor coordination between networking and security teams. Not by a sophisticated nation-state actor. Not by a zero-day exploit. By the seam between two teams that report to different people, fund different tools, and measure success differently.
Artificial Intelligence is rapidly reshaping infrastructure operations. Much of the early focus has been on transforming security operations including automating threat detection, accelerating response times, and reducing security analyst fatigue. While these advancements are essential, they address only part of the problem. Modern enterprises operate highly distributed environments where network performance, application delivery, and user experience are just as critical as security. Limiting AI transformation to security operations alone is no longer sufficient. Enterprises today require a unified operational model that spans network operations, security enforcement, user experience, and infrastructure management. The real opportunity is not just to make security…
Dell’Oro Group is putting a sharper name on something enterprise teams have been feeling for a while: in the AI era, the “WAN” cannot be a collection of loosely coupled products anymore. It has to operate like one end-to-end system with one policy model, one telemetry story, and one operational workflow.
This series introduced the building blocks of enterprise GenAI security. In Parts 1–6 we introduced the building blocks. This post shows how the whole system works end-to-end, using one simple picture and a few real-world walk-throughs.
By now you’ve seen the building blocks:
Discovery
Control
Prompt inspection
Model governance
Tool governance
This post ties these pieces into one system that a real enterprise can run.
CVE-2026-21858 (aptly dubbed “Ni8mare”) is a critical vulnerability affecting n8n, a widely deployed workflow automation platform increasingly used to build agentic AI pipelines. It weaponizes a simple arbitrary file read flaw into full, unauthenticated Remote Code Execution (RCE)
Generative AI is rapidly becoming embedded in enterprise workflows. Developers use it for code generation, analysts rely on it for research, and business teams leverage it for content creation and productivity. While the efficiency gains are significant, generative AI also introduces a new class of security risks that traditional security architectures were never designed to address.
Remote Browser Isolation (RBI) is a critical defense against zero-day threats, data loss, and unmanaged device risk. Learn how Versa RBI integrates natively with Unified SASE to secure the browser across your enterprise.
Artificial Intelligence is pushing enterprise data centers to their limits and most aren’t ready. As organizations deploy GPU-packed clusters and scale out AI inference, traditional architectures struggle to deliver the performance, scalability, and uncompromising security that modern AI demands. Regulated industry-based Enterprises or those with critical intellectual property or sensitive information are not willing to put their sensitive data on third-party clouds or AI applications hosted elsewhere.
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