Identify AI model overuse with User Insights

Cloudflare has expanded AI Gateway User Insights to help organizations understand AI usage beyond model names, token counts, and request volumes by classifying conversations into task categories such as coding, research, writing, summarization, and data analysis. The update includes an “overkill” view that identifies cases where a high-capability model may be handling work that could potentially be completed by a faster or less expensive option, while allowing teams to investigate related users, agents, applications, costs, latency, token use, and conversation turns before changing workflows. These signals also support Potential Savings and an Auto Router, available in closed beta, which can select models based on task complexity, conversation patterns, model fit, and cost rather than automatically choosing the cheapest option. Classification is performed asynchronously through a Cloudflare Worker using eligible AI Gateway logs, produces derived categories and aggregate reporting rather than exposing raw prompts, and may lag traffic by about one day. User Insights can associate activity with users, teams, and applications through AI Gateway metadata and Cloudflare Access, and the capabilities are available free to AI Gateway users.

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