The Integration of Artificial Intelligence in Retail: Benefits, Challenges and a Dedicated Conceptual Framework

Ionut Anica-Popa (), Liana Anica-Popa, Cristina Radulescu and Marinela Vrincianu
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Ionut Anica-Popa: University of Economic Studies, Bucharest, Romania
Liana Anica-Popa: University of Economic Studies, Bucharest, Romania
Cristina Radulescu: University of Economic Studies, Bucharest, Romania
Marinela Vrincianu: University of Economic Studies, Bucharest, Romania

The AMFITEATRU ECONOMIC journal, 2021, vol. 23, issue 56, 120

Abstract: The aim of this study is to identify the practical benefits and associated risks generated by the implementation of artificial intelligence (AI) in retail and capitalize on the results by developing a conceptual framework for integrating AI technologies in the information systems of retail companies. To this end, a systematic study of recent literature was conducted by carefully examining the topic of AI implementations. The main results of the documentation were used to substantiate the conceptual framework introduced by the paper. The research revealed a variety of advanced solutions, benefits, but also risks that AI generates in retail, in different segments of the value chain, abbreviated CECoR, from improving the customer experience (Customer Experience, CE) with the help of virtual agents (chatbots, virtual assistants, etc.), to cost reductions (Cost, Co) by using smart shelves, and to increasing revenues (Revenue, R) due to product recommendations and personalized offers or discounts. The proposed conceptual framework is focused on customer profiles and includes recommendations on AI implementations in a retail company, from the perspective of CECoR drivers. The results of the research can be capitalized by practitioners and researchers in the field, who are presented with concrete examples of benefits, challenges, and risks generated by AI technologies. The CECoR framework could be a useful tool for both retail and AI specialists, providing common and clear guidelines for initiating and overseeing projects for integrating AI in a company’s information systems. Literature-based CECoR analysis dimensions have allowed the restriction of the research area, which is particularly wide, at the confluence of retail and AI. The originality of the article lies in the CECoR orientation of the research and the conceptual framework focused on customer profiling.

Keywords: artificial intelligence; retail; customer experience; cost reduction; revenue increase; CECoR conceptual framework. (search for similar items in EconPapers)
JEL-codes: F43 M15 N70 O33 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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