This article presents a systematic literature review (SLR) of empirical studies concerning Artificial Intelligence (AI) in the field of Supply Chain Management (SCM). Over the past decade, technologies belonging to AI have developed rapidly, reaching a sufficient level of maturity to catalyze transformative changes in business and society. Within the SCM community, there are high expectations about disruptive impacts on current practices. However, this is not the first instance where AI has sparked business excitement, often falling short of the hype. It is thus important to examine both opportunities and challenges emerging from its actual implementation. Our analysis clarifies the current technological approaches and application areas, while expounding research themes around four key categories: data and system requirements, technology deployment processes, (inter)organizational integration, and performance implications. We also present the contextual factors identified in the literature. This review lays a solid foundation for future research on AI in SCM. By exclusively considering empirical contributions, our analysis minimizes the current buzz and underscores relevant opportunities for future studies intersecting AI, organizations, and supply chains (SCs). Our effort is also meant to consolidate existing research insights for a managerial audience.

中文翻译：

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供应链管理中的人工智能：实证研究和研究方向的系统文献综述


本文对供应链管理 (SCM) 领域人工智能 (AI) 的实证研究进行了系统文献综述 (SLR)。在过去的十年中，人工智能技术发展迅速，达到了足够的成熟度，可以催化商业和社会的变革。在 SCM 社区内，人们对当前实践的颠覆性影响抱有很高的期望。然而，这并不是人工智能第一次引发商业兴奋，但往往没有达到炒作的程度。因此，审视其实际实施中出现的机遇和挑战非常重要。我们的分析阐明了当前的技术方法和应用领域，同时围绕四个关键类别阐述了研究主题：数据和系统要求、技术部署流程、组织（间）集成和性能影响。我们还介绍了文献中确定的背景因素。该综述为未来单片机中人工智能的研究奠定了坚实的基础。通过专门考虑实证贡献，我们的分析最大限度地减少了当前的讨论，并强调了未来与人工智能、组织和供应链 (SC) 相交叉的研究的相关机会。我们的努力还旨在为管理受众巩固现有的研究见解。