A methodological framework addressing challenges and opportunities in Supply Chain AI

The advancements and accessibility of AI technologies offer a lot of opportunities for supply chain management (SCM) research to address current challenges, such as environmental, societal and geopolitical needs. While the prominence of e.g., reinforcement learning has been applied for quantitative optimization techniques, the opportunities for qualitative data and approaches have not yet received a lot of emphasis. This new situation (with LLMs) enables joint research approaches to build on capabilities from AI technology together with supply chain management research. To ensure effective, scalable, and trustworthy AI systems in SCM a structured approach is imperative. In this paper, starting from current supply chain AI research, a methodological framework is proposed to build on both AI and SCM capabilities to support qualitative research along the SCM research cycle. Copyright (C) 2024 The Authors. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/)