Without good data, there can be no good AI. But who is actually responsible for data management and AI projects? How do you set up a Data or AI center of excellence? And should it be organized centrally or decentrally? What does the work of these centers of excellence involve? How do they organize AI ethics and AI responsibility so that these are taken into account in projects in business areas?

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One thing is also fundamental: AI and data management cannot simply be delegated. Everyone in an organization must participate. This requires a sociocratic organizational model and a culture of data management and AI responsibility that must be lived out in everyday life. The concept of data mesh organization and culture is a good fit.

 

Participants in this course will learn the basics of data and AI organization/governance. They will learn best practices regarding structures, centralized and decentralized approaches, as well as the areas of responsibility and collaboration with stakeholders in individual business units. In addition, they will learn how to successfully and sustainably establish a culture for data and AI throughout the organization.​​​​​​​​​