Artificial intelligence and predictive analytics to develop evidence-based migration policies for optimal integration and economic empowerment of migrants

Adebayo, Yusuf Olalekan and Adeusi, Oluwakemisola Omolola and Adjadeh, John-Paul and Obion, Sandra Mefoude and Abdulsalam, Rukayat Oyindamola (2025) Artificial intelligence and predictive analytics to develop evidence-based migration policies for optimal integration and economic empowerment of migrants. World Journal of Advanced Research and Reviews, 25 (1). pp. 2147-2155. ISSN 2581-9615

Migration policy development faces increasing complexity in today's interconnected world, necessitating innovative approaches to data analysis and decision-making. This review examines the emerging role of artificial intelligence and predictive analytics in shaping evidence-based migration policies, with particular emphasis on migrant integration and economic empowerment. Through analysis of recent literature and implementation cases, we explore how AI-driven approaches are transforming policy development across various jurisdictions. The review reveals significant advances in predictive modeling for migration flows, resource allocation optimization, and integration outcome assessment. While these technological solutions show promise in enhancing policy effectiveness, challenges persist regarding data quality, algorithmic bias, and ethical implementation. Current applications demonstrate particular success in labor market integration and service delivery optimization, though gaps remain in long-term outcome prediction and cross-border data integration. This review identifies critical research needs in model validation, ethical framework development, and standardization of success metrics. As migration patterns become increasingly complex, the integration of AI and predictive analytics offers valuable tools for policymakers, while simultaneously demanding careful consideration of implementation challenges and ethical implications.