Purpose

Digital transformation and digital technologies, such as AI, pose major challenges for organizational members. For example, existing research postulates that leaders should take on novel roles and show the accompanying behavior to face such challenges successfully. However, knowledge is still scarce on whether role incumbents have (un)equal role expectations regarding their respective roles (e.g., role as a leader and role as a follower), as well as the impact of (un)equal role expectations on role incumbents’ behavior and, consequently, on individual-related outcome variables. Thus, the first research project within this research cluster aims to conceptually introduce a new (combined) perspective of respective role incumbents (i.e., leaders and followers) and the underlying mechanisms influencing individual-related outcome variables. Moreover, the research project empirically applies this new perspective to digital transformation. The second research project within this research cluster focuses explicitly on how human-AI collaboration impacts employees’ roles, addressing the tasks suitable for employee-AI collaboration, suitable skill allocations, and the relationship structures between employees and AI.

Approach

In addition to conceptual studies, the research projects within this research cluster will contain experimental and dyadic studies with leaders and their followers.

Keywords

leader role, employee role, role theory, human-AI collaboration, task types, skill types

Involved Persons

Dr. Ellen Weber, Irini Tsaga, Prof. Dr. Marion Büttgen, Prof. Dr. Ulrike Fasbender