Silver Spring, USA/ Maryland, October 30th, 2025, CyberNewsWire

• The new capabilities, anchored by Blended Identity and the MCP Identity Gateway, give enterprises a secure and auditable way to manage how AI agents identify themselves and access sensitive systems.

Aembit today announced the launch of Aembit Identity and Access Management (IAM) for Agentic AI, a set of capabilities that help organizations safely provide and enforce access policies for AI agents as they move into production. The release introduces Blended Identity, which defines how AI agents act on behalf of verified users, and the MCP Identity Gateway, which ensures secure access to enterprise resources based on identity, access policy, and runtime attributes.

The new offering extends the Aembit Workload IAM Platform to address one of the most pressing operational questions in artificial intelligence and modern IT: how to control what autonomous and user-driven AI agents can access, under what conditions, and with what accountability.

AI agents are rapidly becoming a key part of enterprise operations. Nearly half of technology executives say they are already adopting or fully deploying agentic AI, and about the same share expect most of their AI deployments to be autonomous within two years, according to an EY survey. These agents retrieve sensitive data, open tickets, and execute code across cloud, on-premises, and SaaS environments.

Yet most access models were built for people, not self-directed software. Many still rely on static secrets and shared credentials, creating risk and obscuring accountability. Worse yet, agents’ actions are often hidden behind the identity of a human, making it almost impossible to audit the actions each actor has taken. The result is a widening gap between the pace of AI adoption and the ability of organizations to secure it with confidence.

Aembit IAM for Agentic AI assigns each agent a cryptographically verified identity, issues ephemeral credentials, and enforces policy at runtime. The system records every access decision and maintains attribution across both human-driven and autonomous agent activity. By bringing agent activity under the same centralized policy control plane that governs other workloads, Aembit enables enterprises to deploy AI at scale while maintaining control, auditability, and compliance.

“Enterprises want to say yes to agentic AI, and they’re asking Aembit for ways to securely grant agents access to data and applications,” said David Goldschlag, co-founder and CEO of Aembit. “Aembit IAM for Agentic AI gives enterprises the same level of control and audit over agent access that IAM systems have long provided for employees. Our approach enables organizations to advance their AI initiatives without expanding their threat and risk surface.”

The release introduces two core capabilities to the Aembit Workload IAM Platform:

• Blended Identity, which gives every AI agent its own verified identity and, when needed, binds it to the human it represents. This establishes a single, traceable identity for each agent action and allows Aembit to issue a secure credential that reflects that combined context.
• MCP Identity Gateway, which receives that identity credential and controls how agents connect to tools through the Model Context Protocol (MCP). The gateway authenticates the agent, enforces policy, and performs token exchange to securely retrieve the necessary access permissions for each connected resource – without ever exposing them to the agent runtime.

Together, this functionality allows enterprises to apply least-privilege access, revoke permissions immediately when needed, and ensure that every AI action is attributable and auditable. They operate on Aembit’s established Workload IAM foundation, which enforces policy dynamically at runtime, issues ephemeral credentials just in time, and records structured events for full traceability.

Aembit developed IAM for Agentic AI through collaboration with large businesses, government organizations, and innovative agentic AI startups deploying AI for operational and security workloads. Those efforts helped shape an approach that combines enterprise enforcement with the adaptability AI projects demand.

“AI agents don’t live inside one stack or trust domain,” said Kevin Sapp, co-founder and CTO of Aembit. “They move between hybrid environments in seconds. With Aembit, every agent carries a verified identity that our gateway can authenticate and control in real time. It’s how enterprises can give agents the access they need to work, while never losing sight of who they are or what they touch.”

Aembit IAM for Agentic AI is now available to customers using its Workload IAM Platform. Organizations can learn more, request a demo, or get started today at aembit.io.

About Aembit

Aembit is the identity and access management platform for agentic AI and workloads. It enforces access based on identity, context, and centrally managed policies, giving organizations a singular place to control access risk from AI agents, automate credential management, and accelerate AI adoption. With Aembit, enterprises can confidently control access to sensitive resources across all the workloads that power their business. Users can visit aembit.io and follow the company on LinkedIn.

Contact

Apurva Dave
Aembit
[email protected]