AI Access Control for Enterprise AI: Turning Policy Into Runtime Enforcement
API keys authenticate software. Policy objects decide what that software is allowed to do. The previous post in this series ended on a question asked in a meeting room: who actually decided we're allowed to do this? The argument was that the answer has to exist before a gateway can enforce anything, and that the gateway's job is to make the answer repeatable. This post is about what that answer…
Identity authentication has evolved to include more nuanced access policies. API keys initially only identified software, then evolved to API keys with OAuth scopes that allowed delegation. Enterprise AI introduces new governance questions that credentials cannot answer, such as which business unit owns the workload, which providers are approved, and which specific models are allowed.
These governance decisions must be made at request time, but identity alone cannot carry them. Virtual keys are one implementation that turns governance decisions into runtime objects. These keys contain all the relevant information about the access policy, such as the allowed models, budget limits, rate limits, and expiry date.
The key is created through a governance discussion, not within codebases, and eliminates the duplication of policy interpretations. The virtual key hierarchy mirrors the organization, with customers containing teams, and teams containing virtual keys. Each budget can be attached at any level, and when a request arrives, the budgets in that chain are evaluated together.
If a request is refused, a defined failure response is returned, ensuring governance decisions are enforced.
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