Adoption of AI-based order picking in warehouse: benefits, challenges, and critical success factors

Abstract This research assesses the adoption of artificial intelligence (AI)-based batch order picking in a warehouse, focusing on benefits, challenges, and critical success factors. Using customer order data and simulation, the study employs a quantitative approach, combining mathematical and statistical estimations with qualitative examinations centered on interviews with the warehouse staff, its Enterprise Resource Planning (ERP) developer, and the AI developer. The findings of this mixed-method study reveal that the AI-based order-picking system (AI-based system) has improved order-picking efficiency by reducing travel distance and time. Nevertheless, challenges hinder maximum utilization of the system. In addition, the research highlights critical success factors and other benefits of adopting the system tailored to warehouse management. Understanding the lessons learned in this research is essential for businesses seeking to adopt AI to enhance their efficiency.