Artificial intelligence in retailing: Strategic implications and key areas of concern

Jones, Peter ORCID: https://orcid.org/0000-0002-9566-9393 and Wynn, Martin G ORCID: https://orcid.org/0000-0001-7619-6079 (2025) Artificial intelligence in retailing: Strategic implications and key areas of concern. Business and Management Theory and Practice, 2 (2). pp. 1-14. doi:10.54517/bmtp3180 (In Press)

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Abstract

Within the retail industry the continuing introduction of AI is generating considerable excitement. While there is a rapidly growing literature on the role of AI in retailing, how individual retailers have publicly reported on their introduction of AI has attracted little or no attention in the business and management literature. This article makes a contribution to addressing that gap by providing some simple illustrations of how four leading retailers, namely Amazon, Carrefour, J. Sainsbury and Walmart are developing their relationship with AI. The paper concludes that while the four retailers paint a very positive picture of the benefits AI will generate, there are also a number of issues surrounding the increasing use of AI within retailing that will require careful and vigilant management. These include ethical concerns, balancing personalization and privacy, cybersecurity, the upskilling challenges for retailers, impacts on their employees, sustainability and consumption, environmental problems and corporate social responsibility. This is an exploratory paper and is limited to a secondary research focus, but may provide a useful platform for future research endeavors that could include, for example, empirical research on one or more of the large retailers.

Item Type:	Article
Article Type:	Article
Uncontrolled Keywords:	Retailers; Artificial intelligence; AI; Case examples; Impact areas; Future concerns
Subjects:	H Social Sciences > HF Commerce > HF5001 Business > HF5428 Retail Trade T Technology > T Technology (General)
Divisions:	Schools and Research Institutes > School of Business, Computing and Social Sciences
Depositing User:	Martin Wynn
Date Deposited:	29 Apr 2025 08:30
Last Modified:	29 Apr 2025 08:45
URI:	https://eprints.glos.ac.uk/id/eprint/15006

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