Fastly Launched AI Security and Control Tools
The company introduced new firewall and runtime features to govern model access and spending for global organizations.
Updated on Sept. 21, 2026 in Artificial Intelligence
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Fastly has launched AI Runtime Control, AI Firewall, and API Security capabilities. The platform aims to help organizations govern model access, control rising costs, and protect applications as machine-generated traffic surges.
Why it matters
Organizations are struggling to manage production scaling for AI, with 93% of firms currently exceeding their allocated AI budgets. These new tools allow companies to enforce security and routing policies directly in the request path to mitigate risks and overspending.
AI-driven traffic grew 6.5 times faster than human traffic between January and May 2026. By July and August 2026, machine-generated traffic accounted for more than 50% of total traffic on the Fastly network.
The players
Fastly
Fastly is a global cloud computing services provider that operates an edge cloud platform designed to speed up, secure, and improve the performance of web applications.
The details
The platform routes model calls through a single endpoint to evaluate prompts and apply security policies in the request path across various model providers. This structure enables administrators to exert granular control over model access and real-time security threats.
Timeline
January through May 2026: AI traffic growth significantly outpaced human traffic growth.
July and August 2026: Machine-generated traffic surpassed 50% of the Fastly network total.
September 21, 2026: Fastly announced its new suite of AI security and control capabilities.
Roadmap
This move signals a broader transition in the cloud industry, where providers are pivoting from general traffic delivery to specialized governance for generative AI models. It positions Fastly to capture market share by addressing the critical pain points of cost and security in AI infrastructure.
Users and developers can expect improved workflow reliability and tighter security oversight when interacting with AI model providers. These tools help teams prevent budget overruns by centralizing routing and monitoring for AI applications.
The takeaway
Organizations should prioritize infrastructure that integrates security directly into the AI request path to maintain control over costs. Monitoring the ratio of machine-generated traffic is now an essential step for teams aiming to scale AI operations safely.
Further reading
Learn more about the evolving landscape of Artificial Intelligence solutions.
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Do you trust that businesses have sufficient control over the AI models and agents they deploy?
