Meet Aembit IAM for Agentic AI. See what’s possible →

Author: Apurva Davé

JIT access replaces the common practice of issuing and locally storing keys with a workflow that evaluates a workload’s rights every time it tries to access sensitive data.
How do you govern entities that can learn, adapt, and act independently while maintaining security and compliance?
AI agents are accessing sensitive systems with little oversight. Aembit’s new IAM for Agentic AI gives security teams policy-based control, secretless access, and full auditability—built for the speed and scale of AI.
The core problem is that human IAM was never built for workload scale or behavior.
Instead of treating access as a secrets problem, teams should treat it as an identity problem.
This struggle stems from a reliance on outdated, static credentials and a tension between development velocity and security.
AI agents require broad API access across multiple domains simultaneously—LLM providers, enterprise APIs, cloud services, and data stores—creating identity management complexity that traditional workload security never anticipated.
One careless push unlocked 52 AI models, but the real story is how to keep this from happening again.
Secrets managers worked when workloads stood still. Agentic AI is forcing the vault door shut.
With the increasing complexity of cloud environments and the proliferation of APIs, exposed secrets have become a widespread concern.