Under CopyrightNitsche, Anna-MariaAnna-MariaNitscheSchumann, Christian-AndreasChristian-AndreasSchumannFranczyk, BogdanBogdanFranczykReuther, KevinKevinReuther2022-08-032022-08-032021https://publica.fraunhofer.de/handle/publica/41927610.1109/ICE/ITMC52061.2021.9570266This paper presents a novel method for the analysis and implementation of Artificial Intelligence (AI) inspired collaborative supply chain management (SCM) processes. The evolving nature of supply networks and the underlying information systems drives the application of AI in this context. Within information systems research, design-science approaches have become more relevant in recent years while systems thinking is proven to be a useful method for the analysis of complex issues. The paper thus aims to present a novel approach for the analysis and optimization of collaborative supply networks. For this purpose, the topicality of and potential gains from the integration of AI for supply chain collaboration as well as the shared characteristics of systems thinking and design-science research are discussed. The paper contributes to the academic debate on approaches towards future SCM and collaboration as the methodological and research theoretical focus consolidates systems thinking and design-science research and is transferable to other application areas with dynamic processes. Furthermore, this paper presents a valuable contribution to supply chain processes in organizations of all sectors by providing a macro level perspective on the topic of collaborative SCM. A systemic viewpoint enables better understanding and incorporation of all aspects of sustainability and thus facilitates the development and optimization of future digital, collaborative and resilient SCM and the underlying information systems through the application of AI.ensupply chain collaborationdesign-science researchartificial intelligencesystems thinkingsystem dynamicsartificial intelligenceconference paper