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AI330: Identity & Access Management in Agentic AI NEW

Training: Artificial Intelligence

Participants learn how AI agents, in the context of non-human identities and autonomous access, can securely, in a controlled manner, and compliantly access systems, data, and processes and be integrated into enterprise systems. The practice-oriented training provides a technical and organizational introduction to MCP, Identity & Access Management (IAM), and governance for AI agents – including secure connectivity via MCP servers, access control, delegation, and auditing.

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Possible course languages: German

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Agenda:

From LLMs to AI Agents
- LLM evolution
- Agent frameworks, architecture & design patterns
- Case study: OpenClaw
- Security risks of AI agents
MCP Server
- Model Context Protocol (MCP)
- Integration and authentication
- Registry API
IAM for AI Agents
- Identity & Access Management (IAM)
- OAuth & access control
- Delegation & On-Behalf-Of (OBO) flow
- Limitations of classic IAM systems
- Governance & role management for agents
- Audit, monitoring & reporting
- IAM best practices for AI agents
Practical Scenarios
- Ticketing platform scenario
- Defense scenario: Securing mission-critical logistics with AI agents in DDIL environments
- Logistics scenario: AI agents in transport and warehouse logistics in companies
- Healthcare scenario: Automating patient management and billing with Agentic AI
- Manufacturing scenario: Improving predictive maintenance, parts logistics, and compliance requirements with Smart Factory agents
- Insurance scenario: AI-supported underwriting
Hands-on Sandbox
- Ticketing platform scenario with Maverics.ai
Scenario reviews & takeaways

Objectives:

At the end of the course AI330 Identity & Access Management in Agentic AI, participants will have a comprehensive overview and practical understanding of how AI agents can be operated securely in enterprise environments, with the following focus areas:

Fundamentals of AI agents (Agentic AI), their architecture, frameworks, and differences from classic LLMs
Security risks and governance aspects of autonomous AI agents
Understanding of the Model Context Protocol (MCP) and its role in integration, authentication, and standardization of agents
Why “on-premise”, “disconnected”, and “open” are relevant criteria for AI agentsImplementing Identity & Access Management (IAM) for AI agents including OAuth, delegation, and On-Behalf-Of (OBO) flows
Limitations of classic IAM systems and modern approaches to securely control and monitor agents
Audit, monitoring, and reporting for agents in productive enterprise systems Implementation of governance, role management, and access control for MCP servers and agents
Practical application in various real-world scenarios (ticketing, logistics, healthcare, manufacturing, insurance, defense)
Hands-on experience with sandbox environments to apply concepts directly and identify risks

Target audience:

The training AI330 Identity & Access Management in Agentic AI is aimed at:

IAM Engineers, Identity Architects
Operators of MCP servers, cloud/platform teams
Data Engineers, MLOps/ML Engineers
SecOps, API/integration teams
Security professionals
Product Owners for AI services, pioneers of Agentic AI
Other IT professionals

Prerequisites:

To participate in the course AI330 Identity & Access Management in Agentic AI, you should meet the following prerequisites:

Experience with typical “LLM” usage
General technical IT knowledge
Good English skills (the course language is German, the hands-on sandbox is in English)
Familiarity with simulated web environments

Beneficial for a deeper understanding:

Basics of IT security
Basics of Identity & Access Management

Description:

AI agents (Agentic AI) offer companies enormous opportunities, but also pose new risks, especially when they autonomously access systems, data, and processes. The explosion of non-human identities and the associated security risks make it necessary to operate AI agents securely and in a controlled manner.

In this practice-oriented training AI330 Identity & Access Management in Agentic AI, you will learn how to use AI agents securely, in a controlled manner, and compliantly. The course AI330 Identity & Access Management in Agentic AI provides a comprehensive technical and organizational introduction to MCP, Identity & Access Management (IAM), and governance for AI agents. Participants gain practical insights into integrating AI agents into enterprise systems, secure connectivity via MCP servers, and the implementation of access control, delegation, and auditing.