Background: This study examines the influence of AI-driven supply chains on the adoption of automation and robotics within Jordanian manufacturing firms, emphasizing the role of supply chain adaptability and agility as mediators and market turbulence as a moderator. Methods: Drawing on dynamic capabilities theory and institutional theory, the study develops a conceptual model and tests it using data collected from 337 managers through an online survey. The analysis was carried out through partial least squares structural equation modeling (PLS-SEM). Results: The results show that AI-driven supply chains significantly enhance both adaptability and agility. However, only agility has a direct and significant effect on the adoption of automation and robotics, while market turbulence significantly moderates the connection between supply chain adaptability and the adoption of automation and robotics, but not the relationship between agility and adoption. Conclusions: Theoretically, the study provides insight into the interplay among internal dynamic capabilities in shaping technology adoption under external uncertainty. These results provide actionable implications for managers operating in developing economies like Jordan, highlighting the significance of building agile capabilities and adopting AI technologies to support innovation. The study is limited by its focus on a single country and sector; future research should explore other industries and incorporate additional moderating or mediating variables.
Zaid et al. (2026) studied this question.