Fortinet Launches AI Security for Firewalls

The company introduced a new service designed to inspect AI traffic and protect enterprise data.

Updated on Oct. 26, 2026 in Artificial Intelligence

Isometric editorial illustration of a modular server chassis with graphics processing units, representing enterprise cybersecurity for AI applications. — Fortinet released its FortiGuard Inline AI Security Service to help organizations inspect and secure AI traffic within their enterprise firewall infrastructure. AI Illustration. Upload story photo >

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Fortinet announced the release of its FortiGuard Inline AI Security Service to provide inspection and guardrails for AI applications. The service integrates directly into existing FortiGate firewalls to monitor prompts and responses in real time.

Why it matters

Organizations require specialized AI security tools as traditional systems fail to assess AI-specific threats during rapid enterprise adoption. This service helps businesses identify shadow AI usage and enforce data loss prevention policies across their networks.

The system detects 35 types of personally identifiable information and supports more than 50 predefined compliance policies. It operates as a cloud-delivered offering that inspects prompts, responses, and tool calls in real time.

The players

Fortinet

This Sunnyvale-based cybersecurity corporation serves over one million customers worldwide.

The details

The platform enables organizations to mask sensitive data while monitoring interactions between applications and AI models. Users can also self-host the associated FortiAIGate technology on-premises or on Kubernetes environments using NVIDIA GPUs.

Fortinet announced the new service on October 26, 2026.

The Tech Race

This development marks a shift in how legacy network infrastructure adapts to the rapid growth of generative AI within enterprise environments. It positions the firm against competitors by evolving the FortiGate firewall series to secure AI model inputs and outputs.

IT administrators can now implement robust AI guardrails through their existing security infrastructure without the need for additional hardware deployments. This approach streamlines workflow improvements while helping companies maintain compliance during internal AI adoption.

The takeaway

Enterprises should prioritize visibility into AI interactions to mitigate the risks associated with unauthorized model usage. Regularly updating security policies ensures that sensitive information remains protected as internal tools continue to evolve.