Artificial Intelligence Powered Recommendation Systems and Their Impact on Customer Loyalty

Abstract

The fast-paced introduction of artificial intelligence (AI) in customer-facing application has revolutionized the way businesses interact with consumers. The study research question is the effect of AI-based recommendation systems on customer loyalty, with the consideration of the following key predictors; personalization, perceived usefulness, trust in the system, customer satisfaction, and perceived protection of privacy. Using regression analysis of data collected with students and young professionals in the Tamil Nadu region, the findings indicate that customer satisfaction, perceived usefulness, trust, and personalization are the most significant factors to predict customer loyalty with customer satisfaction being the most influential factor. Perceived privacy protection, on the other hand, did not demonstrate a large difference, indicating that convenience and utility might be more important than privacy in this group. The findings point out that AI-based recommendation systems increase loyalty mainly by promoting satisfaction and perceived usefulness, whereas trust and personalization serve as pillars. These insights can be used by managers of businesses to make transparency, utility and satisfaction one of the priorities in the design of AI systems. Nevertheless, the research has a drawback due to the small sample size and the small demographic focus since it concerns only students and young professionals in Tamil Nadu. To validate and extend these findings, future research ought to extend to include different population, industries, and longitudinal designs. The research adds to the developing literature on AI in marketing by showing that customer satisfaction is the most essential predictor of loyalty in the setting where AI is involved.