Leveraging AI-Powered Recommendations to Foster Ethical Consumption: The Mediating Role of Customer Relationships

Abstract

With the help of AI-powered recommendation systems, consumer engagement has been revolutionized to provide data driven personalized suggestion that influence the decision making processes. Although these systems are good at improving user experience, their ability to affect ethical consumption patterns is yet to be investigated. In this study, I look at customer relationships as a middleman between AI powered recommendations and ethical consumption. Building upon trust, engagement and relationship marketing theories, it postulates that trust based customer relationships amplify the effectiveness of algorithms in steering customers towards sustainable and ethical choices. The research also furthers understanding of how transparency, fairness and user control within AI recommendations boosts trust and loyalty which, in turn, motivates consumers to favour ethical consumption. The study uses a mixed methods approach incorporating both qualitative consumer interviews and quantitative analysis of behavioral data from AI powered platforms. By integrating relational dynamics with AI-driven personalization, the study offers a dual benefit: It offers useful strategies for firms specifying technological innovation with sustainability goals as well as proceeds to enhance theoretical comprehension of ethical AI. The work will guide the design of recommender systems that deliver profitability, but also benefit society broadly, showing the way forward for ethical commercial AI. Through this research, the relationships formed between technology, relationship management and ethical consumerism in a rapidly digitizing marketplace is of critical importance.