Fastly has launched a suite of AI-focused security and management tools, including AI Runtime Control, AI Firewall, and enhanced API Security. These features are designed to provide real-time governance, token spend management, and protection against prompt injection for enterprises managing AI agents and models at the edge.
The launch of Fastly AI Runtime Control signals a shift from AI experimentation to production-scale management where cost and security are the primary bottlenecks. By moving governance to the edge, Fastly allows streaming and tech enterprises to mitigate prompt injection and manage token spend without the latency of centralized security layers. This move positions the CDN provider as a critical intermediary between enterprise APIs and the autonomous agents that now dominate network traffic. As machine-generated requests outpace human interactions, the industry's focus will shift from model performance to runtime reliability. Watch for whether these edge-based controls successfully reduce the high percentage of organizations currently exceeding their AI infrastructure budgets.
Fastly's AI Runtime Control arrives as CDN and edge-security vendors race to capture enterprise AI governance budgets. In September 2026, Mux and Synamedia announced a partnership integrating Mux's real-time QoE signals with Synamedia's Quortex Switch for smarter CDN switching decisions, demonstrating how delivery-layer intelligence is becoming a differentiator for platforms that sit between content and viewers. Fastly's approach extends that logic one layer further by adding model-level governance at the edge rather than relying on application-layer middleware. The company's positioning targets enterprises that already run workloads on Fastly's edge network and want to avoid bolting on separate AI gateway products.
The business case for edge-based AI governance is sharpened by data on how quickly AI workloads are straining existing infrastructure budgets. Bitmovin's 2026/2027 Video Developer Report found that 98 percent of 486 respondents now use AI or ML for video, with 46 percent employing AI tools daily, underscoring that AI is no longer an experimental add-on but a production dependency across the streaming stack. That ubiquity creates the exact governance gap Fastly is targeting: organizations that have deployed AI across encoding, moderation, and personalization pipelines but lack centralized visibility into token consumption, model routing, and prompt-level security. Fastly's AI Firewall and API Security features aim to close that gap without requiring teams to re-architect their delivery layer.
On the technical side, Fastly competes with a growing field of AI gateway and runtime-control products that address similar concerns from different architectural positions. Mux launched its Robots product in early 2026, moving video AI analysis natively inside its platform so that moderation, summarization, and Q&A jobs run next to the video asset, eliminating the need for developers to manage external provider keys or orchestration code. That pattern of collapsing AI governance into the platform that already handles the workload mirrors Fastly's edge-native approach, though Mux focuses on video-specific workflows while Fastly targets cross-industry model access control. Independent analysis of the video developer tooling market notes that Bitmovin holds advantages in codec coverage and enterprise procurement maturity while Mux leads in developer ergonomics and bundled analytics, suggesting that buyers evaluating AI runtime control will weigh similar tradeoffs between breadth of governance features and integration simplicity with their existing delivery stack.
Fastly has launched AI Runtime Control and an AI Firewall to provide real-time governance over model access and token usage. As machine-generated traffic grows significantly faster than human interactions, these edge-based tools help enterprises manage costs, prevent prompt injection attacks, and ensure runtime reliability without adding latency to their existing infrastructure.
It is a new solution that centralizes model calls through a single endpoint, allowing enterprises to manage rate limiting, failover across multiple providers, and token spending at the network edge.
The AI Firewall was launched to identify and block prompt injection attacks directly at the network edge, providing security for enterprises using autonomous coding agents and other AI models.
Machine-generated traffic accounted for over 50% of Fastly's network activity during July and August, with AI traffic growing 6.5 times faster than human traffic in early 2026.
According to McKinsey data cited by Fastly, 93% of organizations are currently exceeding their AI budgets.
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