Automated leadership, where AI-driven systems perform tasks traditionally handled by human leaders, is increasingly relevant in today’s evolving workplace. Yet, their application in traditional organizational settings remains limited. This study explores how to design such systems for effective adoption. Drawing on semi-structured interviews with 24 German leaders and three focus groups with employees (plus a fourth focus group for validation), we identify 13 critical design requirements: personalization, transparency, fairness, co-creation, autonomous operation with human veto, no visible control function, functionality, data security, privacy, visible benefit, avatars, playfulness, and usability. These factors expand the leadership-technology acceptance model (L-TAM) by emphasizing leadership-specific requirements (e.g., personalization and fairness) and pointing to broader considerations like co-creation and data privacy. The findings offer a structured foundation for researchers and practitioners to develop automated leadership systems that enhance efficiency while maintaining user acceptance.