Artificial Intelligence (AI) is a set of methods and technologies that enable computers to perform tasks which previously required human intelligence, including understanding and generating language, classification and image recognition, decision-making, planning, and learning from patterns. Contemporary approaches to AI are based primarily on machine learning, deep learning, generative models, and increasingly on hybrid neuro-symbolic methods that combine statistical learning with logic and rule-based reasoning. In logistics management, AI represents a powerful source of competitive advantage—through route optimization, demand forecasting, warehouse automation, and enhanced resilience of supply chains – while also bringing significant practical challenges: from data quality issues, through costs and skills requirements, to legal, security, and ethical concerns. Successful implementation depends on a systemic approach that integrates high-quality data, human expertise, and responsible algorithm engineering.