AI-enabled Risk Mitigation Framework for Micro Supply Chains

Abstract

Micro supply chains (MSCs) have become indispensable enablers of local and regional economies, supporting micro, small, and medium enterprises (MSMEs), community-based producers, and consumer-centric markets. Despite their agility, MSCs are disproportionately exposed to risks in the current VUCA environment characterized by volatility, uncertainty, complexity, and ambiguity. Demand fluctuations, financial constraints, supply disruptions, and regulatory ambiguity undermine their resilience, while traditional risk management approaches designed for large-scale supply chains remain ill-suited to their scale and resources. Artificial Intelligence (AI) presents a transformative paradigm for risk mitigation under VUCA conditions. Through predictive analytics, digital twins, blockchain, and IoT integration, AI enhances visibility, anticipates disruptions, and supports adaptive decision-making. This paper develops an AI-enabled risk mitigation framework for MSCs, structured around four resilience layers: prediction, prevention, adaptation, and recovery. The framework is contextualized within the challenges of VUCA, ensuring that MSCs can proactively manage volatility, reduce uncertainty, simplify complexity, and clarify ambiguity. Additionally, the study proposes strategies for implementation, including MSME adoption roadmaps, workforce reskilling, and policy-level interventions. Hypothetical applications in agriculture, healthcare, and local manufacturing are also explored. The findings demonstrate how AI, when aligned with VUCA realities, can transform MSCs into resilient, sustainable, and innovation-driven networks capable of thriving in turbulent environments.