Artificial intelligence applications for loyalty management in the retail industry: qualitative evidence from the socio-technical systems theory

PurposeThis article aims to investigate how artificial intelligence (AI) applications are transforming loyalty management in the retail sector, generating unprecedented potential benefits and challenges. The research applies the conceptual lens of socio-technical systems (STS) theory based on six blocks.Design/methodology/approachTo pursue this objective, the article adopts a qualitative approach based on semi-structured interviews with loyalty managers from 39 grocery and nongrocery retailers. The interviews were analyzed using an abductive approach that combines the principles of grounded theory with the six-block STS conceptual model to identify new insights, coding each verbatim in the bright or dark side of AI in loyalty management.FindingsThe analysis showed how AI acts as a stressor within the typical tensions of loyalty management, intensifying certain conflicts between predictive analysis versus opacity, personalization versus privacy and excessive communication, and automation versus the erosion of human relationships. In particular, these tensions intensify when misalignments are created within STS blocks, failing to align the technological aspect with the organizational and human aspects in order to achieve loyalty goals.Originality/valueDespite the disruptive impact of AI in various sectors, there is a scarcity of empirical studies on AI applications in retail and even fewer on context-specific loyalty management practices supported by AI. This research provides new insights to uncover the potential benefits and drawbacks related to AI-based loyalty management approaches.