Amal Dabbous, May Merhej Sayegh, Karine Aoun Barakat, Eleonora Veglianti
Amidst the profound disruptions resulting from sanitary, political, and economic crises, companies have had to re-assess the resilience of their supply chains. In parallel, the appearance of Artificial Intelligence (AI) has been heralded as a technological enabler that potentially enhances supply chain resilience. However, the literature tackling this phenomenon is still in a nascent stage. The present study builds on the Resource-Based View and Dynamic Capabilities theories as a theoretical foundation. It uses ‘fuzzy-set Qualitative Comparative Analysis’ (fsQCA) software on data from 51 surveys distributed to supply chain managers in Italy to depict how AI readiness combined with other factors helps companies achieve high supply chain resilience under different complexity levels. Results show four distinct configurations. In the case of highly complex supply chains, high proactiveness, risk management, and AI readiness appear essential for achieving supply chain resilience. For low-complexity supply chains, high proactiveness coupled with high risk management or high innovation combined with high AI readiness and proactiveness enables supply chain resilience. The study is among the first to empirically show the contribution of AI readiness in enhancing resilience. It advances prior literature by proposing several combinations of factors that yield resilience depending on a company’s supply chain complexity.