The following chapter illustrates recent efforts of AVL – a leading engineering service provider – to address Knowledge Management (KM) in industrial practice. Due to its intricate complexity, battery development has been selected as a use case to investigate the chosen approach. Batteries as a black box may seem simple, but the view inside battery development reveals a combination of technological and organizational complexities, emphasizing the technological and organizational challenges involved. Battery development encompasses various disciplines, including chemistry, thermodynamics, electronics, software engineering, and mechanical engineering. Organizational complexities arise from the need of the involved stakeholders to deal with evolving requirements, varying global standards, and different use cases for batteries. Effective project communication and data management are crucial, in particular if multiple stakeholders from various disciplines are involved. Model-Based Systems Engineering (MBSE) is deployed in AVL to manage these complexities. This divides the battery system into subsystems and focuses on 17 key functionalities that are common for every battery system. Variant management is used to handle product variability and to identify synergy potentials between projects. Finally, KM efforts aim to capture project management knowledge in ongoing projects and to provide gained insights to future projects, again. The case study shows that manual maintenance of knowledge resources yields only limited success. The chapter hence concludes with a deep dive into the potentials of integrating artificial intelligence (AI) to enhance KM and engineering processes.