Challenges and Dilemmas of Artificial Intelligence Implementation in Supply Chain Management

Artificial intelligence is increasingly transforming supply chain management by supporting demand forecasting, inventory optimization, route planning, warehouse operations, and data-driven decision-making. While previous research has mainly emphasized the benefits and applications of AI in logistics, less attention has been paid to the practical challenges and managerial dilemmas associated with its implementation. The aim of this study is to identify the key challenges and dilemmas related to the implementation of artificial intelligence in modern supply chain management. The study is based on a literature review and quantitative research conducted among 236 logistics managers in Poland using the CAWI method. The findings indicate that the most important implementation challenges include integration with existing IT infrastructure, data security, and cooperation within the partner ecosystem. The main managerial dilemmas concern third-party risk management, workforce-related concerns, cybersecurity risks, and algorithmic bias. The study contributes to the literature by shifting attention from the technological potential of AI to the organizational, managerial, and ethical conditions of its effective use in supply chains. From a practical perspective, the findings may support logistics companies in making more informed decisions about AI adoption, particularly in relation to infrastructure readiness, cybersecurity, partner selection, employee adaptation, and responsible algorithmic decision-making.