Application of Artificial Intelligence in Automation of Supply Chain Efficiency in Oman

Abstract

Oman’s supply chain sector is currently facing increasing pressure to improve efficiency due to rising demand, rapid digitalization, and growing expectations for faster and more reliable logistics services. However, many organizations continue to struggle with limited adoption of advanced technologies and varying levels of organizational readiness. In response to these challenges, this study investigates how Artificial Intelligence Technologies (AIT) and the Level of Automation (LOA) influence supply chain efficiency (SCE), and whether Organizational Readiness (OREAD) moderates these relationships. Data were collected via structured questionnaires distributed to 350 participants, including verified supply chain experts accessed through Oman’s Ministry of Labour and employees in supply chain roles reached through social media platforms, ensuring both expertise and broad representation. Regression analysis was conducted using SPSS/AMOS to test the proposed hypotheses. The results show that both AIT and LOA have significant positive effects on SCE, and that OREAD strengthens these relationships by enhancing the effectiveness of technology adoption. These findings suggest that organizations in Oman’s public and private sectors can improve supply chain performance by integrating AI and automation, particularly when supported by strong organizational readiness. This study contributes to the supply chain management literature by providing empirical evidence on the direct and moderated effects of AIT and LOA on SCE, emphasizing the crucial role of organizational readiness in maximizing technological benefits.