Many retailers invest in artificial intelligence (AI) to improve operational efficiency or enhance customer experience. However, AI often disrupts employees’ ways of working causing them to resist change, thus threatening the successful embedding and sustained usage of the technology. Using a longitudinal, multi-site ethnographic approach combining 74 stakeholder interviews and 14 on-site retail observations over a 5-year period, this article examines how employees’ practices change when retailers invest in AI. Practice co-evolution is identified as the process that undergirds successful AI integration and enables retail employees’ sustained usage of AI. Unlike product or practice diffusion, which may be organic or fortuitous, practice co-evolution is an orchestrated, collaborative process in which a practice is co-envisioned, co-adapted, and co-(re)aligned. To be sustained, practice co-evolution must be recursive and enabled via intentional knowledge transfers. This empirically-derived recursive phasic model provides a roadmap for successful retail AI embedding, and fruitful future research avenues.

许多零售商投资人工智能 (AI) 以提高运营效率或增强客户体验。然而，人工智能经常扰乱员工的工作方式，导致他们抵制变革，从而威胁到该技术的成功嵌入和持续使用。本文采用纵向的多地点人种学方法，结合 5 年期间的 74 次利益相关者访谈和 14 次现场零售观察，研究当零售商投资人工智能时员工的做法如何变化。实践协同进化被确定为支持成功的人工智能集成并使零售员工能够持续使用人工智能的过程。与可能是有机的或偶然的产品或实践扩散不同，实践协同进化是一个精心策划的协作过程，其中实践是共同设想、共同适应和共同（重新）调整的。为了持续下去，实践协同进化必须是递归的，并通过有意识的知识转移来实现。这种经验派生的递归阶段模型为成功的零售 AI 嵌入提供了路线图，并为未来的研究提供了富有成果的途径。