Next dates:

Winter semester: starts on 21.09.2026

AI Leadership & Change Manager

This training course combines two mission-critical perspectives of modern corporate development: the well-founded use of artificial intelligence and the effective design of change processes in organizations.

Participants will learn not only to classify AI technologically, but also to identify concrete fields of application within their own company, prioritize them sensibly, and actively support change processes regarding introduction, acceptance, and implementation.

The training course is aimed at executives, decision-makers, and those responsible for transformation, innovation, and organizational development who want to apply AI in a practical, responsible manner and with a view to the reality of businesses.

During the course, participants are enabled to build their own AI agents in order to structure AI application scenarios within their own company, develop ideas further, and receive impulses for implementation.

Ticket price per participant:in
10% Discount for Pro members in the Federal Association for AI Transformation

2.900 €

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Provider of this course:

What participants take away from the course

Practical understanding of the introduction and application of AI in companies
Clearer guidance in identifying and prioritizing relevant AI use cases
A better understanding of leadership, communication, and change challenges in the AI context
Concrete impulses for transfer into your own company
Exchange with experts and other participants in a protected learning environment
A structured look at generative AI, agents, automation, and organizational implementation

As a participant in this course, you will receive a structured, practical approach to key questions of AI transformation: from the basics of modern AI, generative AI, agents, and automation to leadership, communication, and change management in an organizational context.

You work on real-world questions from companies, reflect on typical challenges when introducing AI, and develop robust transfer approaches for your own practice. The course combines technological classification, methodological guidance, and a concrete focus on application.

Build the foundation for informed AI decisions in your company

Our goal is to provide you with a sound understanding of Artificial Intelligence, Generative AI, and organizational transformation processes.

You will learn how to identify relevant AI application fields, prioritize use cases sensibly, categorize tools and agents practically, and support change processes in your company realistically and effectively.

The training course is aimed at top management, decision-makers, executives, and those responsible for transformation, innovation, organizational development, and digitalization who do not view AI in isolation as a technology topic, but rather as a leadership, implementation, and change management task.

Target group: Top management, Decision-makers, managers
Mentors: Lecturers of the GENIUS ALLIANCE
Duration: 3 months (50 lessons of 45 minutes each, including 10 lessons of self-study)
Frequency: Weekly online meetings of 90 minutes each
Number of participants: 10-25 persons
Previous knowledge: none
Location: Network and learningCommunity platform
Technology: PC/MAC with browser and smartphone
Platform access: Immediately after acceptance of the application

Seminar Dates: Winter Semester 2026

09/21/2026, 5:00 PM – 6:30 PM – Kick-off
09/22/2026, 5:00 PM – 6:30 PM – Building an AI Agent in Hybrid Organizations
09/28/2026, 5:00 PM – 6:30 PM – Introduction to AI
05.10.2026, 5:00 PM – 6:30 PM – Generative AI
10/06/2026, 5:00 PM – 6:30 PM – AI Use Cases
10/12/2026, 5:00 PM – 6:30 PM – Automation with Projects and Assistants
10/19/2026, 5:00 PM – 6:30 PM – Coding Tools for Agents and Automations
10/24/2026, 09:00 – 17:00 – AI Workshop
10/26/2026, 5:00 PM – 6:30 PM – Fundamentals of Change Processes
10/30/2026, 5:00 PM – 6:30 PM – Perception Processes & Behavior in the Change Process
11/11/2026, 5:00 PM – 6:30 PM – Leadership, Communication & Dealing with Uncertainty in Change
11/16/2026, 5:00 PM – 6:30 PM – Structuring and Shaping Transformation Processes
November 23, 2026, 5:00 PM – 6:30 PM – Sustainable Embedding and Learning in the Change Process
11/28/2026, 9:00 AM – 5:00 PM – Hands-on Workshop: Project Presentation and Transfer into Practice
November 30, 2026, 5:00 PM – 6:30 PM – Change Reality Check: What Really Works
December 7, 2026, 5:00 PM – 7:00 PM – End of the course

Seminar Dates: Spring 2027

February 22, 2027, 5:00 PM – 6:30 PM – Kick-off
02/23/2027, 5:00 PM – 6:30 PM – Building AI Agents in Hybrid Organizations
March 1, 2027, 5:00 PM – 6:30 PM – Introduction to AI
March 8, 2027, 5:00 PM – 6:30 PM – Generative AI
March 15, 2027, 5:00 PM – 6:30 PM – AI Use Cases
04/05/2027, 5:00 PM – 6:30 PM – Automation with Projects and Assistants
04/12/2027, 5:00 PM – 6:30 PM – Coding Tools for Agents and Automations
04/17/2027, 9:00 AM – 5:00 PM – AI Workshop
04/19/2027, 5:00 PM – 6:30 PM – Fundamentals of AI-related change processes
04/26/2027, 5:00 PM – 6:30 PM – Milieus, Perception, and Attribution of Meaning in AI Change
May 3, 2027, 5:00 PM – 6:30 PM – Leadership, Communication, and New Authority in the AI Context
05/10/2027, 5:00 PM – 6:30 PM – Structuring and Design of AI Transformation Processes
05/31/2027, 5:00 PM – 6:30 PM – Implementation, learning processes, and sustainable integration
06/02/2027, 5:00 PM – 6:30 PM – Change Reality Check: What Really Works
June 5, 2027, 9:00 AM – 5:00 PM – Change Workshop
June 7, 2027, 5:00 PM – 7:00 PM – Completion of the course

What makes this course special!

Artificial intelligence does not unfold its benefits in companies through technology alone. The decisive factor is whether application areas are chosen wisely, changes are effectively supported, and new ways of working are integrated into existing organizations.

This is precisely where this course comes in: it combines AI competency with change management competency and teaches how technological possibilities, organizational reality, and leadership responsibility can be brought together.

In addition to understanding core AI fundamentals, participants will gain a realistic picture of how AI transformations unfold in companies: with uncertainty, acceptance issues, leadership requirements, prioritization decisions, and concrete implementation challenges.

At the same time, the course offers a practical approach to generative AI, agents, assistants, automation, and the identification of relevant use cases. This creates a program that combines technological orientation, organizational transfer, and concrete application.

Combining AI and Change Management: The training course combines technological fundamentals with organizational implementation, leadership, and communication.
Practical AI application: Participants work with current approaches regarding generative AI, agents, assistants, and automation.
Use-case orientation The training course helps to identify, structure, and prioritize relevant application areas within one's own company.
Realistic transformation perspective: In addition to technology, the focus is on acceptance, resistance, communication, leadership issues, and sustainable integration.
Interactive workshops: In the workshops, content is applied to specific practical cases, term papers, and usage scenarios.
Exchange in a safe environment: The community platform fosters communication with instructors and participants beyond the course.
High reliance on transfer payments: The goal is not only the acquisition of knowledge, but also its reflective application in the respective corporate context.

The program of the IHK certificate course

Part A | Orientation, Setup, and AI Practice

Kickoff and orientation in the course

Welcoming the participants
Introduction of the Lecturers and Mentors
Overview of procedure, learning objectives, and collaboration
Introduction to the platform, exchange, and guidance in the course

Building AI agents in hybrid organizations

Introduction to target vision, benefits, and use cases of AI agents
Differentiation: Chatbot versus Agent
Agent roles, skills, knowledge logic, and specialization
Data protection classification and use as a work surface
Hands-on: Creating your first own agent
Quality assurance, hallucination reduction, and iterative improvement
Outlook on automation and workflow integration

Part B | Change Management for AI Transformations

Module 1

Fundamentals of AI-related change processes

Introduction to Key Concepts of Change Management
Characteristics of AI transformations in companies
Differences Between Traditional Change and AI-Related Changes
Typical Organizational Response Patterns During Change Processes
Uncertainty, acceptance, and resistance in the organizational context
Importance of communication and orientation in transformation processes
Reflection of organizational dynamics and change logics

Module 2

Milieus, perception, and attribution of meaning in AI change

Introduction to Habitus and Social Milieus
Perception and attribution of meaning in change processes
Professional identity and changes through AI
Different perspectives on AI systems and technological changes
Psychological mechanisms in AI change
uncertainty, loss of control, and threat to competence
Connectability of communication in organizations
Reflection of different reaction patterns in organizational change

Module 3

Leadership, communication, and New Authority in the context of AI

Leadership in change processes
Presence and communication in organizational change
Transparency and psychological safety
Relationship and trust in a corporate context
Reflection of modern leadership approaches
Self-Discipline and Perseverance in Change Processes
Support and Networking Mechanisms
Communication in conflict and uncertainty situations
Leadership as a Guiding and Interpretive Function in the AI Transformation

Module 4

Structuring and Designing AI Transformation Processes

Introduction to Simplified Change Models
Classification of the 4-Phase Model
Reflections on the 6-Phase Model in the Context of AI
Definition of Objectives and Impact Assessment
Organization-related analytical perspectives
Planning and structuring change processes
Practical examples from companies
Transfer Approaches for Small and Medium-Sized Enterprises
Limits of linear change logics

Module 5

Implementation, learning processes, and sustainable anchoring

Iterative Implementation Logics
Learning and Feedback Loops in Organizations
Sustainable Implementation of AI Initiatives
Reflection of organizational learning capability
Dealing with Uncertainty and Change
Meaning of participation and communication
Ensuring the Long-Term Implementation of Change Processes
Limitations of Traditional Stabilization Approaches in the AI Transformation

Workshop

Practical work, transfer, and term paper support

Revising and Further Developing Your Own Term Paper
Reflection on Personal Practice and Business Examples
Applying the Models Taught to Specific Change Situations
Development of custom transfer and communication approaches
Practical exercises and case studies
Exchange and Peer Reflection

Part C | AI Competence for Executives and Decision-Makers

Module 1

Introduction to AI

Types of AI
Machine Learning
Supervised and Unsupervised Learning
Neural networks
Basic terms and concepts

Module 2

Generative AI

Large Language Models
Prompt Writing and Prompt Engineering
Generative AI for spreadsheets and metrics
Generative AI for data analytics
Limits and distortions

Module 3

Identify and prioritize use cases

Legal framework: AI Act and GDPR/Data Protection
Find and prioritize use cases
Practical tools and methods, e.g., Data Science & AI Canvas
Cross-industry application examples
Assessment of benefits, feasibility, and implementability

Module 4

Automation with projects and assistants

Tools, plug-ins, and connectors in ChatGPT and Claude
AI for presentations, visualizations, and graphics
Create Automation Projects
Creating, using, and combining assistants and skills

Module 5

Coding Tools for Agents and Automations

Function and operation of AI agents
Tools for building agents, e.g. n8n, Zapier, Relay, Google Opal, OpenAI Agent Builder
OpenAI Codex
Claude Code
Live applications and classification for enterprise use

Workshop

Practical workshop for application, prototyping, and transfer

Future Skills: What competencies people need when AI transforms large parts of knowledge work
Guest Keynotes and Discussion
Group work: Development of a concrete use case and MVP/prototype
Presentation of the results
Discussion, feedback and joint transfer

Part D | Practical Transfer and Conclusion

Change Reality Check

What really works

Practical reality check on change management in AI transformations
Analysis of typical success factors and pitfalls
Meaning of business ownership, leadership, and clear accountability
Dealing with stakeholders, participants, and those affected
Application of selected models and best practices to real-world contexts

Graduation

Joint reflection on the learning content
Transfer to one's own company
Completion of the training course
Discussion on next implementation steps

This certificate course combines in-depth knowledge with practical exercises and offers participants a comprehensive basis for independently developing and implementing AI strategies for their own company.