Abstract
The adoption and diffusion of Artificial Intelligence (AI) in organizations are significantly influenced by many sociotechnical factors such as people, processes, or regulations. However, previous research has mostly focused on a reactive description of individual influencing factors and lacks an overarching perspective that enables active management of an organization’s various AI capabilities. Therefore, this paper provides a first overarching perspective by identifying all relevant activities for the management of AI in literature and grouping them into eight different fields of action. These fields of action are then evaluated by practitioners and combined into a cross-industry reference model for AI Management. While this reference model is the first of its kind and is already making a valuable contribution to the emerging field of AI Management in Information Systems Research, further insights are expected from the future refinement and application of the model.
Recommended Citation
Fukas, Philipp and Thomas, Oliver, "Developing a Reference Model for Artificial Intelligence Management" (2023). ECIS 2023 Research-in-Progress Papers. 89.
https://aisel.aisnet.org/ecis2023_rip/89