Insight from industry-early lessons learned about AI adoption in core procurement processes, directions for managers and researchers

Remko van Hoek
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Abstract

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.

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行业洞察--核心采购流程采用人工智能的早期经验教训,为管理者和研究人员指明方向
目的考虑到人工智能在供应链和采购方面的潜力的概念性工作越来越多,管理人员对人工智能也非常感兴趣。但是,根据最近的一项研究,采购的数字化战略往往缺失或不尽如人意。在核心采购流程中可能采用人工智能的领域方面,文献提供了相互矛盾的指导。鉴于需要更好的采购数字化战略,以及需要进一步了解采用潜力,本文旨在探讨行业中的实际采用水平、经验效益、准备水平和实施障碍。作者利用文献中用于研究其他技术采用情况的项目,首次对人工智能在采购中的实际采用水平进行了实证探索。作者通过在三个经理研讨会上收集调查反馈来完成这项工作,并利用这些研讨会征求经理们的意见,以解释研究结果并确定对经理和研究人员的影响。采用水平普遍较低,这意味着管理者和研究人员还有很大的发展空间来考虑、使用案例和可能的试点。作者发现,采用人工智能带来的采购效益比成本和生产率更广泛,包括可见性和创新。但是,准备程度似乎相对较低,文献中通常考虑的因素,如高管支持和投资意愿,与人的感知能力和供应商准备程度等较少被广泛考虑的因素相比,相关性较低。作者根据文献中的要求,增加了人的感觉决策项目,从而扩大了对准备程度的考虑。作者还纳入并发展了供应商准备情况的考虑因素,而这往往是研究中所缺乏的。在参与研究的管理人员的帮助下,作者能够为人工智能的采用制定一个更全面的考虑框架。这有助于将细微差别而非炒作纳入考虑范围,并为进一步探索提供了丰富的研究项目和结构组合。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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