Intelligent model routing is the practice of sending each AI request to the least expensive model that can still complete the task well enough. A simple classifier, rules engine, or confidence check may choose between a small local model, a mid-tier hosted model, or a larger frontier model. The goal is to preserve useful output quality while reducing token costs, latency, and infrastructure load.
In cyber security, routing matters because AI systems are metered services and every unnecessary model call increases exposure, cost, and operational complexity. Defenders use routing to keep routine lookups, summarization, and classification on cheaper systems, while reserving stronger models for sensitive or ambiguous cases. Attackers may try to game the router by adding noise, unusual phrasing, or adversarial prompts that push traffic toward a weaker model or trigger repeated escalations. Good routing logic therefore needs monitoring, fallback rules, and clear policies for high-risk content, so the system stays efficient without creating blind spots.