This study examines a real-world case of artificial intelligence (AI) implementation in Operations and Supply Chain Management (OSCM) projects at Robert Bosch GmbH, showcasing how leadership adapted to AI applications in logistics and operations to enhance operational outcomes.
Over six years, the authors studied over 30 OSCM projects at Bosch, supplemented by semi-structured interviews with 10 managers at the final step of this research. Adaptive leadership theory was applied as the theoretical framework to explore leadership’s role in facilitating AI adoption and improving logistics and operations.
We find that initial AI adoption did not yield immediate improvements in logistics and operations and, in some cases, can be detrimental when leadership is actively involved. We found a three-phase maturity model for leadership participation in AI applications: (1) structuring, (2) implementation and (3) scaling. In the first phase, leadership focused on enabling AI adoption and fostering partnerships for its development, while playing a back-office role in supporting the technical team’s learning curve in AI applications. A digital excellence committee was established in the second phase to guide AI-enabled OSCM projects, where leaders had an active role in emphasising alignment and collaboration. Finally, leadership transitioned to a strategic oversight role, emphasising strategy and monitoring AI’s impact on logistics and operations in the scaling phase.
We offer practical recommendations for leadership on when having an active or supportive role is more beneficial in AI applications in OSCM projects, showcasing three adaptive behaviours.
This study provides a deeper understanding of leadership roles in AI applications within OSCM projects, highlighting that leaders’ influence must be exerted to support successful implementation and operational outcomes.
