AI-process integrative framework for driving deep digital supply chain transformation

Artificial Intelligence has emerged as a pivotal driver of deep digital transformation across Supply Chain processes. However, this disruptive change poses several challenges, particularly in incorporating AI algorithms into these processes, which necessitates their reengineering often carried out through siloed actions among practitioners. To address this gap, integrative models to unify these actions are needed. While some studies have explored such models, the literature lacks a consolidated model applicable to both industry and research. This study aims to bridge this gap by proposing an integrative AI-Process Framework, developed through an in-depth exploratory approach built upon multiple conceptual components. Experimental application to three industrial cases revealed three critical findings: poor coordination and fragmented AI adoption among supply chain stakeholders, challenges with early-stage AI integration due to its complexity, and deficient consideration of social implications in AI deployment. These findings pave the way for future research to focus on developing a more coordinated strategy for effective AI-value creation in modern supply chains.