Enterprises must urgently implement zero trust security architecture for AI agents, not as a future goal, as agentic AI dramatically compresses risk timelines. Continuous verification per action, not just at login, is crucial for AI agents due to their high speed. Permissions granted to AI agents accumulate over time, creating unseen exposures that traditional security models cannot manage. The speed of agentic AI, where thousands of actions can occur in minutes, necessitates a shift in how permissions are handled. Zero trust principles of "just enough, just in time" access are essential to address this accelerated risk. Each AI agent requires its own distinct identity, separate from human logins or shared service accounts, to prevent impersonation. Securely managing agent identities and avoiding shared secrets like API keys embedded directly in code is now a top priority. API gateways and agent gateways are practical enforcement points for zero trust policies, inspecting agent requests in real time. The aim is to move authorization decisions to the moment of each consequential action, not just at initial login. To address the risk of agents rewriting their own permissions, a zero trust framework must also monitor the watchers. Human review of agent output cannot scale, so a new paradigm involving independent AI agents evaluating each other's work is proposed. This framework acknowledges that perfect output validation is impossible, but trusts the structured process. Ultimately, enterprises need comprehensive visibility and management for all AI agents, both internal and external, to secure their operations before widespread adoption makes retrofitting prohibitively expensive.