This article examines the key factors and underlying reasons driving the adoption of artificial intelligence (AI) in supply chain management within the context of rapid digitalization and the evolution of Industry 4.0 and 5.0. The study is grounded in a conceptual and literature-based methodology, synthesizing existing academic and practical insights related to digital transformation, AI technologies, and supply chain operations. The paper highlights that the growing complexity of global markets, along with increasing competition and the need for operational agility, has compelled organizations to integrate advanced digital solutions into their supply chains. Digitalization—supported by technologies such as the Internet of Things (IoT), big data analytics, and cyber-physical systems—serves as a critical enabler of AI implementation. These technologies facilitate the collection and processing of large volumes of real-time data, allowing AI systems to enhance decision-making processes, improve forecasting accuracy, optimize logistics, and increase overall supply chain visibility. Furthermore, the article identifies several major drivers of AI adoption, including the necessity to improve efficiency, ensure resilience against disruptions, and enhance customer satisfaction. AI contributes significantly by automating routine processes, reducing human error, and enabling predictive and adaptive supply chain strategies. The integration of AI also supports better coordination among supply chain partners and accelerates the transition toward fully digitalized business ecosystems. Despite these advantages, the study acknowledges several challenges that hinder widespread AI adoption, particularly in developing and emerging economies. These challenges include high implementation costs, a lack of skilled human resources, issues related to data quality, and difficulties in integrating AI systems with existing infrastructure. The article concludes by emphasizing the need for further empirical research, especially in low-income and transitional markets, where context-specific factors influencing AI adoption remain underexplored. Overall, the study contributes to the existing body of knowledge by linking Industry 4.0 and 5.0 developments with AI-driven supply chain transformation, while also emphasizing the importance of sustainable and human-centered approaches in digital innovation. Purpose: This paper will investigate the major aspects and motives of the adoption of artificial intelligence (AI) in supply chain management in the framework of the rapid digitalization and Industry 4.0/5.0 advancements. Methodology: The article follows a conceptual and literature-based approach, integrating the available literature on the topic of digital transformation, AI technologies, and supply chain management. It discusses the technological, organizational, and environmental aspects that affect the adoption of AI. Findings: The findings demonstrate that one of the biggest enablers of AI integration within the supply chains is digitalization and Industry 4.0 technologies, including Internet of Things (IoT), big data analytics, and cyber-physical systems. The use of AI results in improved efficiency, resiliency, and customer satisfaction due to the improvement of decision-making, forecasting accuracy, logistics optimization, and real-time visibility. The most prominent factors that have led to AI adoption are the complexity of the market, competition, managerial goodwill, and the necessity of agility in operations. Nevertheless, there are still issues like the cost of implementation, the unavailability of a skilled labour force, data quality, and barriers to system integration that are major challenges, especially in developing economies. Implications: The paper is restricted to a conceptual review and points out the necessity to conduct an empirical study, particularly in low-income and emerging markets, where context-specific determinants to AI adoption are under-researched. Value: The proposed study will add to the existing research on the topic by combining the insights of Industry 4.0 and 5.0 with AI-driven supply chain change, with a focus on both technological changes and human-centered, sustainable solutions.
Tehmina Rafi (Sat,) studied this question.