The impact of AI social responsibility on service loyalty: a mixed-method approach

As artificial intelligence (AI) becomes increasingly integral to service industries, understanding how AI Social Responsibility (AISR) shapes customer relationships is critical. This paper aims to develop a dimensional framework of AISR and investigate the distinct mechanisms through which it influences service loyalty. A mixed-methods approach was employed, combining qualitative and quantitative techniques. First, in-depth interviews with 20 consumers who had used AI-enabled services were analyzed using Thematic Analysis, identifying two core dimensions: Technical AISR and Institutional AISR. Subsequently, two scenario-based experiments were conducted across different service contexts to test the proposed model. The results reveal a dual mediation mechanism: technical AISR primarily enhances service loyalty by boosting perceived AI competence, whereas institutional AISR primarily increases perceived AI empathy. Additionally, self-AI connection positively moderates these relationships, amplifying the effects of both AISR dimensions on their respective mediators. The paper concludes that AISR is a multidimensional construct that influences service loyalty through cognitive and affective pathways, with its effectiveness contingent on consumers' psychological bond with AI. These findings offer a novel theoretical lens for understanding AISR's role in service relationships and provide actionable guidance for firms seeking to strategically deploy responsible AI practices to cultivate lasting customer loyalty.