The Role of AI Recommendation Systems in Shaping FMCG Buying Behavior among Chennai Consumers

The study explores the impact of AI driven recommendation systems on FMCG purchase behaviour among consumers in online retailing in Chennai. With a sample size of two hundred, The study is quantitative, and employs regression, correlation, chi-square, t-test factor analysis SEM to explore linkages among AI personalization, trust engagement and consumer purchase intentions. The findings suggest that AI-based recommendation systems play a critical role in facilitating product discovery, building trust on the online platforms and impacting impulse buying. Tailoring and transparency represents two of the driving factors behind consumer adoption and satisfaction. We add to existing literature by providing empirically driven evidence for how AI recommendation features influence purchase behaviour in these settings. The implications are some recommendations based on the ethical, transparency and contextually adaptive recommendation strategies for retailers to achieve sustainable loyal consumers and beat competition. Limitations and implications for future research are addressed.