What participants take away from the course

• A well-founded understanding of why AI transformation is sociotechnical and why traditional change models alone are no longer sufficient.
• Confident handling of Lewin, Kotter, ADKAR, Bridges, McKinsey 7-S, and Burke-Litwin and their targeted combination in the AI context.
• A repeatable, artifact-based approach ranging from mandate and diagnosis to target vision and architecture, all the way to institutionalization: Align, Structure, Enable, Anchor.
• Operational confidence in dealing with anxiety, resistance, and identity issues, as well as a clear understanding of psychological safety as a prerequisite for learning processes.
• Structural anchoring of governance, human-in-the-loop, and ethics, including the legal guardrails of the EU AI Act and GDPR.
• Practical knowledge on AI agents: architecture, application areas, and governance requirements with growing autonomy.
• Develop, present, and defend a reasoned transformation approach of your own for your professional context during the expert discussion.

These points are deliberately not an additive toolkit, but rather a cohesive development of competencies: whoever understands the socio-technical logic of AI transformation can deploy models more purposefully; whoever masters models can set up a change process more cleanly; whoever sets up a process cleanly can lead people more credibly. At the end of this chain lies the ability to anchor responsibility—technically, humanly, and legally—in such a way that AI transformation is not merely introduced, but becomes permanently viable.

What it is about

The introduction and scaling of artificial intelligence is not merely a technological question for organizations, but a profound sociotechnical transformation. AI directly intervenes in knowledge work, decision-making logics, competence requirements, and power structures, thereby placing different demands on change management than previous waves of digitalization.
The AI Transformation Manager training course bridges precisely this gap. It combines the academic depth of change psychology and change theory with a field-tested operating system for change, supplemented by AI agents as well as law, data protection, and compliance.
In the end, there is no certificate for passive listening, but rather a personalized, scientifically grounded and practically conceived transformation approach that participants present before an expert audience.

Who this course is made for

The course is aimed at executives, change managers, and project and transformation leaders who are responsible for, guide, or actively shape AI-related change processes in their organization, particularly from organizational development, human resources, IT and digitalization management, business consulting, and affected departments.
No prior technical AI knowledge is required, but rather the willingness to engage with scientifically grounded models as well as one's own leadership practice, along with a specific professional use case on which the content can be tested.
Participants who are already in the middle of implementing AI and realize that technical progress alone is not enough—because acceptance is lacking, roles are unclear, or governance issues remain unresolved—will particularly benefit. The course is equally suitable for leaders who are just planning an AI transformation and want to avoid falling into the typical traps of unclear mandates, lack of diagnosis, or purely tool-driven communication right from the start.

• Target group: Leaders, change managers, project and transformation leads
• Instructors: Katharina Müller-Pommer, Nicola Maria Graul, Norman Müller and Stephanie Iraschko-Luscher
• Duration: 50 teaching units
• Live classes: 20 teaching units in eight evening blocks and one final workshop
• Self-study: 18 periods of supervised self-study
• Term paper and exam: 12 EU
• Previous knowledge: No prior technical AI knowledge required
• Format Online evenings plus final workshop

Spring semester 2027

• Mon, 01/25/2027, 6:00-7:30 PM: Evening A1-A2, Katharina Müller-Pommer
• Mon, 02/01/2027, 6:00 PM - 7:30 PM: Evening A3-A4, Katharina Müller-Pommer
• Mon, Feb 15, 2027, 6:00-7:30 PM: Evening B-I, Nicola Maria Graul
• Mon, Feb 22, 2027, 6:00 PM - 7:30 PM: Evening B-II, Nicola Maria Graul
• Mon, 03/01/2027, 6:00-7:30 PM: Special Topic AI Agents, Norman Müller
• Mon, 03/08/2027, 6:00 PM - 7:30 PM: Evening Block Legal, Stephanie Iraschko-Luscher
• Sat, Mar 13, 2027, 9:00 AM – 5:00 PM: Final workshop, Katharina Pommer and Nicola Maria Graul

summer semester 2027

• Mon, 04/05/2027, 6:00-7:30 PM: Evening A1-A2, Katharina Müller-Pommer
• Mon, Apr 19, 2027, 6:00-7:30 PM: Evening A3-A4, Katharina Müller-Pommer
• Mon, Apr 26, 2027, 6:00-7:30 PM: Evening B-I, Nicola Maria Graul
• Mon, May 3, 2027, 6:00 PM – 7:30 PM: Evening B-II, Nicola Maria Graul
• Mon, May 10, 2027, 6:00–7:30 p.m.: Special Topic: AI Agents, Norman Müller
• Mon, 05/31/2027, 6:00 PM - 7:30 PM: Evening Block Legal, Stephanie Iraschko-Luscher
• Sat, June 12, 2027, 9:00 AM – 5:00 PM: Final Workshop, Katharina Pommer and Nicola Maria Graul

Fall semester 2027

• Mon, Sep 20, 2027, 6:00-7:30 PM: Evening class A1-A2, Katharina Müller-Pommer
• Mon, Sep 27, 2027, 6:00-7:30 PM: Evening A3-A4, Katharina Müller-Pommer
• Mon, Oct 4, 2027, 6:00-7:30 PM: Evening B-I, Nicola Maria Graul
• Mon, Oct 11, 2027, 6:00-7:30 PM: Evening B-II, Nicola Maria Graul
• Mon, Oct 18, 2027, 6:00-7:30 PM: Special Topic AI Agents, Norman Müller
• Mon, Nov 8, 2027, 6:00 PM – 7:30 PM: Evening session Legal, Stephanie Iraschko-Luscher
• Sat, Nov 13, 2027, 9:00 AM – 5:00 PM: Final workshop, Katharina Pommer and Nicola Maria Graul

Teaching methods

The course combines scientific foundation with lived practice: keynote speeches and instructional discussions convey theoretical depth, case analyses and role plays make psychological dynamics tangible, and workshop sessions on mandate and diagnostic documents create direct practical transfer.
Group work, reflection exercises, and peer case consultations encourage interaction among participants, while transfer assignments after each evening apply what has been learned to their own transformation projects.

Completion and examination

The course concludes with a three-part examination: a written term paper of 3,000 to 4,500 words, the development of an individual transformation concept as a presentation, as well as its presentation and defense in an expert discussion.
The quality of the change concept, the theoretical foundation, the systemic analysis, the clarity of the problem definition, the depth of reflection, as well as structure and academic rigor, will be evaluated. Those who pass the exam and attend at least 80 percent of the live sessions will receive the „AI Transformation Manager“ certificate.

The program of the certificate course