An Analytical Study on Advantages of Artificial Intelligence in Last-Mile Operations: Enhancing Tracking, Accountability, and Efficiency

Abstract

Last-mile, or, say the final stop in the process of delivery, is gripped with challenges of various sorts-like shipment traceability, insurgent rejections, ineffective sorting, and real-time prioritization errors. There is room for artificial intelligence (AI) to transform these problems through improving tracking accountability, ensuring delivery accountability, optimally sorting given shipment, and maximizing priority of deliveries deemed critical (P0, P1). Here, we conduct an extensive literature review on the emergence of AI in last-mile hub operations and set forth a mixed-methodological approach, responding to and combining qualitative insights with quantitative data obtained through stakeholder survey measures. AI applications under discussion include systems for tracking in real-time, predictive analytics, and automated sorting algorithms, considering ethical and practical challenges. The results suggest that AI can indeed improve operational performance, decrease error rates, and increase client satisfaction, thereby launching reliable and greatly transparent last-mile delivery ecosystems.