Tag: Agentic AI

AI agents need identity controls, scoped access, and runtime enforcement before they are trusted with production systems.
AI agents need more than working credentials. They need verifiable identity, task-scoped access, and clear attribution.
Visibility tells you what your agents are doing. Enforcement determines what they’re allowed to do. Here’s what the Aembit team saw at Identiverse that confirmed the gap.
Aembit now supports Microsoft Copilot Studio, giving security teams secure agent authentication to enterprise resources, least-privilege access at runtime, and a complete audit trail of every access event.
As AI moves from chat windows to enterprise systems, data leakage becomes an identity and access problem.
A working prototype can mask the harder problem: keeping every workload, agent, credential, policy, and audit trail consistent across production environments.
Whether you want simple fire-and-forget alerts or full two-way control, here’s how to securely wire your AI agent into Slack
Workforce and customer agents may rely on similar identity infrastructure, but the trust models, access patterns, and security risks behind them differ significantly.
Aembit IAM for Agentic AI combines blended identity with an MCP Identity Gateway for enterprise agents.
Most CISOs fear AI agent risks, but legacy IAM can’t govern autonomous systems. A new identity model built on attestation is emerging.