Cloudflare, Inc. (NYSE: NET), the leading connectivity cloud company, today launched Identity-Aware AI Gateway, giving IT and security teams their clearest view yet into how employees use AI at work. For the first time, companies can see exactly which employee or agent sent a request to an AI model, set individual or team-level spending limits, and automatically flag risky content, all without building new systems or disrupting how people work. A companion feature, User Insights, goes further by learning what normal AI usage looks like for every person and automated system on a network and alerting teams the moment something breaks that pattern.

AI use inside companies is growing fast, and two problems are growing with it: rising costs and security blind spots. On the cost side, even as individual AI requests get cheaper, employees and automated bots are sending far more of them and bills are spiking with little warning or explanation. On the security side, sensitive information like employee names, passwords, and confidential files can quietly pass through to outside AI providers with no one noticing. Today’s tools can cap overall AI spending across an account, but they can’t tell you who triggered those costs or what was sent, leaving IT teams managing damage after the fact instead of preventing it.

“When security is clunky, it becomes a speed bump that slows down innovation. Right now, companies are wary of surprise AI bills or accidental data leaks, so their instinct is to lock down access and restrict what teams can build,” said Dane Knecht, CTO of Cloudflare. “Connecting our access controls directly to AI Gateway flips that dynamic. Teams get the freedom to work with any AI model they choose. IT gets real-time visibility, guardrails, and the budget controls they actually need.”

Together, AI Gateway and User Insights allow enterprises to:

• See Exactly Who’s Sending What: By connecting AI Gateway with Cloudflare Access, every AI request is now tied to a verified identity whether that’s an employee or an automated system.
• Catch Unusual Behavior Before It Becomes a Problem: User Insights tracks each user’s AI activity over time and builds a user baseline. When spending spikes well beyond what’s normal for a specific user or system, IT gets an alert.
• Surface Efficiency Opportunities That Are Easy To Miss at Scale: User Insights checks whether employees are using high-powered models for simple tasks that lighter, less expensive models could handle so efficiency gains are easy to find.
• Enforce Identity-Based Access and Authentication: Companies can replace blind, shared API keys by integrating with their Identity Provider (IdP) and Zero Trust (ZTNA) infrastructure. This validates user and device posture before sending requests to the model provider without slowing adoption, recording verified identities directly in request logs.
• Have One Place to See and Control all AI traffic: Instead of managing AI usage piecemeal across every tool and model provider, all requests flow through a single point. That gives IT immediate visibility across the board, the ability to cache repeat requests and cut redundant costs, rate limiting to stop runaway usage before it hits the invoice, and automatic filters that strip out employee names, passwords, and other sensitive data before they ever reach an outside AI provider.

“Shared API keys make it almost impossible to tell who is using an AI service or apply the access rules we already have for employees. Putting Cloudflare Access in front of AI Gateway gives each request an authenticated identity and lets us use our existing identity policies at the gateway. Our teams can adopt AI tools without creating a separate authentication system for every client,” said Max Baumgarten, Security Engineer at Flexport.