This study conducts a systematic literature review and practical case analysis to comprehensively understand how artificial intelligence (AI) technologies affect efficiency and sustainability in the logistics industry. A total of 1,944 relevant papers indexed in the Scopus database between 2017 and 2025 were analyzed. Through the analysis of keyword relationships, four major application domains were identified: transportation management and last-mile delivery, warehouse and inventory optimization, reverse logistics and waste management, and digital transformation. By comparing and analyzing leading corporate cases in the United States, China, and Korea, this study examines the practical impact of AI adoption in the logistics industry. Although the specific AI techniques and application trajectories vary across domains and nations, combined evidence from the literature analysis and practical comparisons confirms that research and implementation have been actively pursued not only to improve efficiency but also to enhance sustainability. This study aims to provide meaningful implications for both academia and industry by presenting current trends and suggesting future research directions in AI-based sustainable logistics.