R0-R5 Risk Tier Model Aims to Govern Which AI Tool Actions Run Automatically

A proposed framework called the R0-R5 Tool Risk Model assigns one of six risk tiers to every AI-executed operation, from informational reads to irreversible external actions like deleting data or sending emails. The model argues that a single blanket policy — either fully automatic or fully human-reviewed — is inadequate for enterprise AI deployments, since write operations carry far greater and often irreversible consequences than reads. Each tier maps to a specific execution policy: low-risk reads run automatically, business-sensitive writes require human confirmation, and the highest-risk actions are blocked outright. If a tool does not explicitly declare its tier, the system defaults conservatively, treating undeclared writes as requiring confirmation. The open-source KeelBase project is cited as a working implementation, featuring a verifiable enforcement chain that includes permission checks, policy gates, human approval steps, and a tamper-evident audit log.