Agile Collaboration with AI: Coordination, Knowledge Work, and Limits of AI Use

Course overview

The training "Agile Collaboration with AI: Coordination, Knowledge Work, and Limits of AI Use" combines theoretical foundations with application-oriented exercises on the topics of "Coordination", "Knowledge Work", and "Limits of AI Use". Professional situations are examined to determine how Artificial Intelligence is classified and what role Agile Collaboration plays in this context. The structure is oriented towards planning, prioritization, collaboration, progress control, and continuous improvement. Limits, dependencies, and suitable control steps for Artificial Intelligence are taken into account. The guiding theme is the task "Agile Collaboration with AI"; it is addressed from a professional, methodological, and quality-related perspective. Documented results show how Artificial Intelligence and Agile Collaboration interact in the respective field of work. Participants work on comprehensible practical cases from AI-supported work and application situations, compare solution paths, and document assumptions, decisions, and results. The goal is a structured understanding of the fields of tasks described in the title and their application in different work situations. Program The learning progress regarding Artificial Intelligence is made visible through a documented transfer task. The educational content is divided into seven interrelated learning sections: - Application scenarios and framework conditions: The focus on "Agile Collaboration with AI" is classified in terms of task framework, typical areas of application, and the necessary work steps. The orientation is specified through task management, role coordination, visible progress, and the gradual adjustment of the approach. Knowledge about Artificial Intelligence is built up for the practical cases and linked to professional references to Agile Collaboration. - Coordination: Collaboration is designed based on clear responsibilities, suitable conversation formats, and comprehensible agreements. - Knowledge Work: This subtopic is addressed using central terms, typical work steps, and a comprehensible application case. In the result control, both Artificial Intelligence and Agile Collaboration are considered based on understandable criteria. - Limits of AI Use: Participants formulate suitable tasks, examine generated results, and document assumptions and uncertainties. Participants independently apply Artificial Intelligence in a defined task section. - Task flow and continuous adjustment: Work is made visible, bottlenecks are identified, and the approach is gradually improved based on feedback. The transfer part deepens the understanding of Artificial Intelligence and translates the insights into a coherent task regarding Agile Collaboration. - Control and responsible use: Inputs, results, and human review steps are connected to a comprehensible quality process. - Practical case and transfer: Participants work on a coherent case, justify their approach, and transfer the insights gained t…

Upcoming dates

• 2026-08-16T22:00:00.000Z · 2026-10-11T22:00:00.000Z · München · Combined Learning
• 2026-08-16T22:00:00.000Z · 2026-12-06T23:00:00.000Z · München · Combined Learning
• 2026-09-13T22:00:00.000Z · 2026-11-08T23:00:00.000Z · München · Combined Learning
• 2026-09-13T22:00:00.000Z · 2027-01-03T23:00:00.000Z · München · Combined Learning