Exploring Challenges and Opportunities in Developing Resilient and Risk-Aware AI-Enabled Supply Chain Systems

This study aimed to explore the challenges and opportunities involved in developing resilient and risk-aware AI-enabled supply chain systems in the context of increasing global uncertainty and complexity. A qualitative research approach was adopted, relying on a systematic review and thematic analysis of secondary data from recent academic and industry sources related to artificial intelligence, supply chain resilience, and risk management. The analysis identified key themes associated with technological, organizational, and environmental dimensions of AI adoption. The findings revealed that AI significantly enhances supply chain resilience through predictive analytics, real-time visibility, and adaptive decision-making capabilities. However, several challenges persist, including data fragmentation, lack of interoperability, cybersecurity risks, skill shortages, and ethical concerns related to AI usage. At the same time, opportunities were identified in the integration of advanced technologies, improved collaboration among stakeholders, and the alignment of sustainability objectives with AI-driven strategies. The study implies that organizations must adopt a holistic approach to AI implementation by strengthening data infrastructure, fostering organizational readiness, and establishing robust governance frameworks. It also highlights the importance of combining human expertise with AI capabilities to ensure effective and responsible decision-making. These insights contribute to both academic understanding and practical application in building resilient and future-ready supply chain systems.