Artificial intelligence-driven resilience: Revolutionizing supply chain risk management in entrepreneurial projects

This paper explores the role of Artificial Intelligence (AI) in supply chain risk management (SCRM) in the context of international entrepreneurial projects across diverse industries. Using a qualitative multiple case study design, the research draws on 20 semi-structured interviews conducted across 10 projects to examine how AI technologies support risk management in dynamic and uncertain environments. Template analysis revealed that entrepreneurial ventures typically adopt a five-stage risk management process: risk mentoring, risk identification, risk analysis, risk mitigation, and continuous adaptation. AI tools facilitate each stage by enabling real-time monitoring (through the Internet of Things), predictive risk identification (via Machine Learning and Natural Language Processing), secure mitigation strategies (using Blockchain and Robotic Process Automation), and adaptive learning (through reinforcement learning). These capabilities allow entrepreneurs to proactively respond to external disruptions, foster operational flexibility, and continuously refine their approaches. As a result, AI emerges as a transformative enabler of agile, data-driven SCRM practices tailored to the unique vulnerabilities of entrepreneurial projects. This study provides a practical framework to guide decision-makers in selecting and implementing AI solutions strategically across the SCRM lifecycle. It offers actionable insights to strengthen resilience, minimize disruptions, and enhance competitiveness in increasingly volatile global supply chains.