Purpose

There is a growing body of conceptual work considering the potential of AI in supply chain and procurement, and there is great interest in AI among managers. But, according to a recent study, digital strategies for procurement are often missing or not satisfactory. Literature offers conflicting guidance on possible adoption areas for AI in core procurement processes. Given the need for better digital strategies for procurement and the need to further develop the understanding of adoption potential, the purpose of this paper is to explore actual adoption levels, experienced benefits, readiness levels and barriers to implementation in industry. This informs nuanced, not hyped, managerial consideration and identifies further research opportunities.

Design/methodology/approach

Leveraging items used in literature to study adoption of other technologies, the authors conduct the first empirical exploration of actual adoption levels of AI in procurement. The authors do so by collecting survey responses in three manager workshops, and the authors use the workshops to seek manager input in the interpretation of findings and the identification of implications for managers and researchers.

Findings

There appears to be less consideration given to AI in procurement than interest in the topic might imply. Adoption levels are generally low, implying that there is a lot of room for the development of consideration, use cases and possible pilots by managers and researchers. The authors find procurement benefits of AI adoption to be broader than costs and productivity alone, including visibility and innovation. But, readiness appears to be at relatively low levels with factors commonly considered in literature, such as executive support and willingness to invest, less relevant than less widely considered elements such as human sense making and supplier readiness.

Originality/value

This first empirical exploration moves past conceptualization and the study of potential adoption into the study of actual adoption levels in different procurement core processes. The authors expand the consideration of readiness by including additional items of human sense making as called for in literature. The authors also include and develop supplier readiness consideration, which is often missing from research. With the help of participating managers, the authors are able to develop a more comprehensive framework for the consideration of AI adoption. This can help bring nuance, not hype, to consideration and provides a rich portfolio of research items and constructs to further explore.

中文翻译：

---

行业早期关于在核心采购流程中采用人工智能的经验教训以及管理者和研究人员的方向

 目的

越来越多的概念性工作考虑到人工智能在供应链和采购方面的潜力，管理者对人工智能表现出极大的兴趣。但是，根据最近的一项研究，采购的数字化策略往往缺失或不令人满意。对于核心采购流程中人工智能可能采用的领域，文献提供了相互矛盾的指导。鉴于需要更好的采购数字化策略以及进一步加深对采用潜力的了解，本文的目的是探讨实际采用水平、体验到的好处、准备水平和行业实施的障碍。这为管理考虑提供了细致入微的而非夸张的信息，并确定了进一步的研究机会。

设计/方法论/途径

作者利用文献中使用的项目来研究其他技术的采用，对采购中人工智能的实际采用水平进行了首次实证探索。作者通过在三个经理研讨会上收集调查回复来做到这一点，并利用研讨会寻求经理对调查结果的解释以及对经理和研究人员的影响的识别。

 发现

采购中对人工智能的考虑似乎比对该主题的兴趣所暗示的​​要少。采用率普遍较低，这意味着管理者和研究人员的考虑、用例和可能的试点还有很大的发展空间。作者发现，采用人工智能的采购效益比单纯的成本和生产力更广泛，包括可见性和创新。但是，准备度似乎处于相对较低的水平，与文献中通常考虑的因素（例如高管支持和投资意愿）相比，与不太广泛考虑的因素（例如人类意义建构和供应商准备度）相关性较低。

 原创性/价值

第一个实证探索超越了概念化和潜在采用的研究，转向了不同采购核心流程中实际采用水平的研究。作者通过纳入文献中所要求的人类意义构建的其他项目来扩展对准备就绪的考虑。作者还纳入并制定了供应商准备情况的考虑因素，而这在研究中经常被遗漏。在参与管理人员的帮助下，作者能够开发一个更全面的框架来考虑人工智能的采用。这有助于考虑细微差别，而不是炒作，并提供丰富的研究项目和结构组合以供进一步探索。