Artificial intelligence in supply chain management: enhancing customer engagement through real-world cases

Supply chain disruptions, such as those triggered by the COVID-19 pandemic, have exposed vulnerabilities in customer engagement due to delays in communication and delivery. This study investigates how artificial intelligence (AI) can address emergent challenges in supply chain management (SCM) and enhance customer engagement across multiple supply chain functions. Drawing on twenty-six real-world cases, we develop an integrative framework that maps AI applications to seven key SCM operations and identifies their impact on customer engagement parameters including trust, convenience, satisfaction, personalisation, connectedness, profitability, and loyalty. The study also examines five AI failure cases to highlight potential risks and mitigation strategies. Interpreting the findings through a Dynamic Capabilities lens clarifies how AI-enabled sensing, decision making, and process reconfiguration translate operational gains into customer engagement outcomes. Findings suggest that AI-augmented supply chains can improve automation, resilience, and efficiency, but require careful implementation to avoid unintended consequences. The paper contributes a holistic blueprint for AI integration in SCM and offers practical recommendations for managers seeking to enhance customer engagement through intelligent technologies.