Kanban and AI: Flow Data, Bottleneck Indicators, and AI Application Limits

Course overview

The training "Kanban and AI: Flow Data, Bottleneck Indicators, and AI Application Limits" combines theoretical foundations with application-oriented exercises on the topics of "flow data", "bottleneck indicators", and "AI application limits". Work results related to Artificial Intelligence are discussed and improved based on clear criteria. The focus is on clear work agreements, understandable decisions, and the gradual management of projects. Commonalities, differences, and meaningful transitions between Artificial Intelligence and Kanban are elaborated. The guiding theme is the task "Kanban and AI"; it is addressed from a professional, methodological, and quality-related perspective. Professional situations are examined to determine how Artificial Intelligence is classified and what role Kanban plays in this context. 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 task areas described in the title and their application in different work situations. Program The professional focus is on the competence field of Artificial Intelligence and the application focus of Kanban. The educational content is divided into seven interrelated learning sections: - Task Areas and AI Reference: The focus "Kanban and AI" is classified regarding 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 of Artificial Intelligence is built for the practical cases and linked to professional references to Kanban. - Flow Data: Participants classify requirements, choose an appropriate approach, and document the resulting outcomes. The professional classification of Artificial Intelligence is supplemented by concrete tasks related to Kanban. - Bottleneck Indicators: Terms, processes, and decision points are connected and applied in a practical task. - AI Application Limits: Application possibilities are described based on clear tasks; inputs, outputs, limits, and control steps are examined together. The exercises address Artificial Intelligence in a clear workflow and incorporate Kanban at suitable decision points. - Planning and Control Process: Goals are translated into tasks, priorities are aligned, and progress as well as open points are transparently tracked. - Result Quality, Limits, and Responsibility: Outputs are checked for plausibility, traceability, and possible errors; limits of application are documented. For Artificial Intelligence, limits, dependencies, and suitable control steps are considered. - Transfer to Professional Situations: Several typical situations are compared so that approaches can be adapted and justified for new requirements. Participants independently apply Artificial Intelligence in a defined task section. T…

Upcoming dates

• 2026-07-26T22:00:00.000Z · 2026-09-20T22:00:00.000Z · München · Combined Learning
• 2026-07-26T22:00:00.000Z · 2026-11-15T23:00:00.000Z · München · Combined Learning
• 2026-08-23T22:00:00.000Z · 2026-10-18T22:00:00.000Z · München · Combined Learning
• 2026-08-23T22:00:00.000Z · 2026-12-13T23:00:00.000Z · München · Combined Learning