Netskope Unveils AI Command Center for Unified AI Security Management
Netskope introduces the One AI Command Center, a platform designed to discover AI assets, assess risks, and automate responses, addressing critical visibility gaps in enterprise AI adoption.
Netskope has launched the Netskope One AI Command Center, a new platform aimed at consolidating AI asset discovery, risk intelligence, and autonomous response capabilities into a single, unified interface. This latest addition to the Netskope One AI Security suite is designed to provide security teams with a clear understanding of the AI applications running within their environments, enabling them to prioritize and accelerate risk mitigation efforts.
The rapid proliferation of AI applications within enterprises has created significant security challenges. According to Netskope Threat Labs, the average organization has seen a fivefold increase in AI applications and a threefold growth in its AI user base over the past year. This surge has resulted in an average of 37 deployed AI agents and 223 AI data policy violations per month. Alarmingly, 94% of organizations report gaps in visibility into their AI activities, with only a small fraction feeling they have complete oversight of their AI pipeline.
The Netskope One AI Command Center addresses these visibility gaps by discovering all AI assets, regardless of whether they are corporate-sanctioned or shadow IT, managed or unmanaged, cloud-based or on-premises. The platform maps these discovered AI assets to the identities, data stores, and tools they interact with. This comprehensive mapping allows for the surfacing of critical risk insights, which are then correlated with Netskope's existing knowledge bases concerning data sensitivity, user risk profiles, and application trustworthiness.
By meticulously mapping the relationships between AI assets, user identities, and sensitive data stores, the platform can uncover hidden attack paths and potential risk exposures. From the same interface, security teams can receive actionable recommendations, including the creation or refinement of security policies, the initiation of remediation workflows, or the launch of in-depth investigations. This integrated approach aims to streamline the security operations lifecycle for AI.
In addition to the core AI Command Center functionalities and discovery via inline traffic inspection, Netskope has introduced two new components to enhance asset discovery. Endpoint AI discovery leverages enhancements to the Netskope One Client to scan managed endpoints for installed AI applications, running processes, and listening ports, identifying local AI agents and browser extensions. Complementing this, Server AI discovery utilizes a lightweight eBPF agent to intercept TLS-encrypted AI traffic at the kernel level on corporate virtual machines and Kubernetes nodes, extending discovery to critical AI infrastructure within the enterprise perimeter.
Further bolstering the platform's capabilities is the new AgentSkope AI Risk AISecOps agent. This autonomous intelligence layer is designed to handle the triage and investigation of AI-related security incidents, drive automated responses, and effectively scale a security team's expertise without requiring a proportional increase in headcount. This aims to automate repetitive tasks and allow human analysts to focus on more complex threats.
Sanjay Beri, CEO of Netskope, emphasized the critical need for such a solution, stating, "Organizations have adopted AI faster than any security team can manually track, triage, or contain, and the tools nobody approved are almost always the ones carrying the highest risk." He highlighted that the One AI Command Center provides a unified operational view, enabling security teams to manage every AI asset, its connections, and the data it touches, thereby allowing organizations to embrace AI securely.
Jennifer Glenn, Research Director for Data and Information Security at IDC, noted the pervasive visibility gap created by the explosion of enterprise AI adoption and data sprawl. She concluded that platforms combining comprehensive AI discovery with real-time risk correlation are essential for security operations to anticipate, prioritize, and autonomously eliminate AI-fueled threats at the speed required by the current threat landscape.