AI Manager (m/f/d)

Course overview

Artificial intelligence is fundamentally changing the economy, work, and society - and it's happening faster than many companies can keep up with. In this transformation, there is a need for bridge builders between technology, strategy, and corporate culture: AI Managers are exactly that. They recognize potentials, think in solutions, and responsibly bring innovation into practice. As an AI Manager, you will steer the strategic implementation of artificial intelligence in the company - economically, securely, and in compliance with regulations. This training enables you to implement the introduction, management, and scaling of AI in the company responsibly and economically effectively. You will learn to identify strategic application areas, accurately classify technical fundamentals, and coordinate operational measures - with special consideration of regulatory frameworks such as the EU AI Act. The focus is on benefit orientation, risk assessment, data strategy, and the establishment of sustainable AI governance structures, so that AI is perceived as an opportunity rather than a threat. Key areas of training for AI Managers: Fundamentals and Strategic Framework Artificial Intelligence in the economic and social context Understanding technology for decision-makers: AI, ML, LLM, Generative AI Opportunities and risks in the corporate environment Competitive advantages through AI integration Identifying and Evaluating Use Cases Methodology for selecting meaningful application areas Economic viability, scalability, and data availability Quick Wins vs. structural transformation Best practices from industry and services Data Strategy, Infrastructure & Generative AI Fundamentals of data architecture for AI Data protection, data quality, and data ownership Cloud, API interfaces & system integration Understanding and classifying Generative AI & Prompt Engineering Governance, Ethics & EU AI Act Overview of the EU AI Act and its relevance for companies Risk classes, transparency, and documentation obligations Responsible AI: Ethics, fairness, and sustainability Establishing an internal AI governance framework Implementation & Change Management Project planning, stakeholder management, and piloting Collaboration with tech teams and external partners Successfully shaping change processes in organizations Creating acceptance through communication and empowerment Application & Practical Transfer Development of an AI roadmap in the corporate context Practical workshop: Implementation using a concrete case study Practice-oriented result presentation and peer feedback

Upcoming dates

• 2026-08-02T22:00:00.000Z · 2026-11-01T23:00:00.000Z · München · Combined Learning
• 2026-08-02T22:00:00.000Z · 2027-01-01T23:00:00.000Z · München · Combined Learning