BUILDING AI-DRIVEN ECONOMIC RESILIENCE SYSTEMS TO SUPPORT STABILITY DURING FUTURE PANDEMIC LOCKDOWNS

Abstract

This systematic review examines the diverse and transformative role of artificial intelligence (AI) in strengthening economic resilience amid pandemic-induced lockdowns, with a particular focus on its deployment in public governance systems, crisis mitigation protocols, and digital service architectures. Guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework, the review analyzed 175 peer-reviewed journal articles, institutional white papers, and technical documentation published between 2000 and 2025. The literature was drawn from interdisciplinary domains, including economics, public policy, data science, and computational systems engineering. Core areas of investigation encompassed AI applications in predictive economic modeling, real-time emergency resource allocation, digital identity-driven welfare targeting, labor market reconfiguration, smart taxation and fiscal governance, and supply chain continuity management. The findings indicate that AI-enabled predictive analytics facilitated the early detection of economic disruptions such as inflation surges, sectoral downturns, and unemployment spikes, thus empowering governments to undertake preemptive budget adjustments and sector-specific relief planning. Algorithmic targeting systems, particularly those utilizing supervised learning and digital identity verification, demonstrated substantial gains in delivering emergency cash transfers, food aid, and subsidies with improved precision and efficiency. AI-supported labor market platforms helped reduce job-matching latency, enabled skill-based employment redirection, and provided digital vocational guidance in the face of widespread labor displacement. Furthermore, Geo-AI technologies and dynamic inventory models played a crucial role in optimizing logistical routes, managing cold chain integrity, and reallocating medical and food supplies based on epidemiological trends and real-time geospatial constraints. While technical efficacy was widely acknowledged, the review also highlights persistent governance challenges, including algorithmic bias, data privacy concerns, transparency gaps, and limited ethical oversight. Overall, the evidence underscores AI’s growing potential as a policy instrument for crisis-responsive economic planning and the imperative for robust regulatory frameworks to safeguard fairness and accountability in its deployment.