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What is Agentic AI

5 min readAgentic AI systems act autonomously to achieve goals, planning multi-step tasks and adapting to changing conditions. Learn how they differ from traditional AI.

Agentic AI systems act autonomously to achieve goals, planning multi-step tasks and adapting to changing conditions.
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Service accounts outnumber human users but operate with static credentials and minimal oversight.
The exposure demonstrates how ordinary errors can reveal internal credentials and how stronger limits on scope and lifespan can contain the impact.
The incident demonstrates how autonomous behavior reshapes intrusion patterns when identity is not clearly assigned or enforced.
These four architectural patterns reveal how AI agents differ fundamentally from traditional workloads.
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.
Securing MCP servers requires rethinking the entire communication stack, not just adding TLS and calling it done.
From Coca-Cola to Campbell Soup, Renee Guttmann knows what lasts as security changes.
The organizations succeeding with agentic AI are deploying it with constraints.
How do you govern entities that can learn, adapt, and act independently while maintaining security and compliance?
Choosing the right flow is only the beginning. The real challenge is implementing either flow without creating persistent credential vulnerabilities that undermine your security.
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.
Instead of just trusting the token’s signature, attestation-based identity adds an extra layer of security.

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