Netskope Launches AI Security Platform to Monitor and Protect Enterprise AI Systems

Companies are adopting artificial intelligence quickly. AI tools are now being used in everyday workflows, internal applications, and automated processes. Many organizations are also building their own models or connecting AI agents to business systems.

That growth is creating new security concerns. AI systems often interact directly with corporate data, applications, and external services. In many cases, security teams have limited visibility into how those interactions happen or what data is being accessed.

Netskope is addressing this challenge with Netskope One AI Security, a set of capabilities designed to help organizations monitor and control AI applications, models, agents, and data flows from a single platform.

Extending Security to AI Systems

Netskope says the new capabilities build on its existing security platform, which many organizations already use to secure web, cloud, and SaaS traffic.

Melody Nouri, Senior Product Marketing Manager at Netskope, explained to ChannelE2E that the approach extends the same architecture used to protect user activity.

Nouri said the company’s Zero Trust Engine plays a key role in how these controls work.

Performance is also part of the design. AI applications often require fast data access, which can make security enforcement difficult.

Nouri added that Netskope’s long focus on data security helps organizations manage AI risks.

New Capabilities Focus on AI Activity

The release introduces several tools designed to help security teams manage AI environments.

Netskope One Agentic Broker provides visibility into communications between AI agents and enterprise data sources. It allows organizations to monitor Model Context Protocol (MCP) transactions and apply policies to those interactions.

Netskope One AI Guardrails helps prevent AI-related threats such as prompt injection and jailbreaking. It also moderates interactions between users, agents, and large language models.

Netskope One AI Gateway allows organizations to apply security controls to private AI models or applications that run inside their own environments.

Netskope One AI Red Teaming tests AI systems by simulating attacks against models and applications to identify weaknesses before they are deployed.

These capabilities aim to give security teams a clearer view of how AI systems interact with enterprise data and infrastructure.

Improving Visibility Into AI Risks

One challenge for many organizations is understanding how AI agents interact with internal tools and systems.

Nouri said the platform was designed to help address that visibility gap.

One example is visibility into protocols used by AI agents.

The platform also allows organizations to monitor how AI agents use enterprise tools.

For companies with strict data governance requirements, deployment flexibility can also be important.

Organizations can also adjust how guardrails operate based on their risk tolerance.

Opportunities for MSPs and Managed Security Providers

As organizations deploy more AI systems, managed security service providers may begin building services focused on monitoring and governing those environments. Netskope sees this as a natural extension of the security services many providers already offer.

“AI security is opening up a significant new service opportunity for MSSPs, and Netskope One AI Security is purpose-built to support that. We see service providers building managed offerings across three core areas,” said Melody Nouri, Senior Product Marketing Manager at Netskope.

The first area is continuous monitoring of AI activity. As AI agents interact with data sources, applications, and tools, organizations need visibility into what those systems are doing and how they behave over time.

“Continuous monitoring is a natural starting point. MSSPs can offer ongoing visibility into AI agent actions and interactions, tracking tool usage, data access patterns, and anomalous behaviors across their customers' AI environments.”

Governance is another area where service providers may play a role. As organizations experiment with new AI use cases, policies and controls may need to evolve quickly.

“Because the AI threat landscape evolves so rapidly, service providers can also deliver a governance layer that regularly reviews and updates controls, thresholds, and policies as new AI use cases emerge within an organization.”

Netskope also expects providers to offer services around testing and validating AI models before they are deployed.

“Where things get particularly compelling is around red team testing. Netskope's AI Red Teaming gives MSSPs a repeatable, automated capability to stress-test customers' privately hosted AI models before every release, running adversarial scenarios that surface vulnerabilities before they can be exploited.”

Over time, those services could shift security operations toward more proactive oversight of AI environments.

“Together, these capabilities let service providers move well beyond reactive security into proactive AI risk management, which is exactly what enterprises will need as their AI footprint continues to grow.”

As AI systems become part of everyday enterprise operations - analyzing data, interacting with applications, and automating tasks - security teams are increasingly focused on understanding how those systems operate. That means gaining visibility into how AI agents, models, and tools interact with enterprise environments and ensuring appropriate controls are in place as their use expands.