Impact of AI-Based Recommendation Systems on Consumer Purchase Behaviour in Swiggy

The rapid integration of Artificial Intelligence (AI) in digital platforms has transformed consumer purchasing behaviour, particularly in online food delivery services. This study examines the impact of AI-based recommendation systems on consumer purchase intention, ordering behaviour, satisfaction, and repeat purchase behaviour in Swiggy. The research specifically investigates how personalization, trust, and perceived usefulness of AI recommendations influence consumer decision-making and loyalty. A structured questionnaire was administered to 180 Swiggy users, and statistical tools such as descriptive statistics, correlation, and regression analysis were applied to analyze the data. The findings reveal that AI-based recommendation systems significantly influence purchase intention and ordering frequency. Among the influencing factors, perceived usefulness emerged as the strongest predictor of repeat purchase behaviour, followed by personalization and trust. The results indicate that consumers are more likely to place orders and make impulse purchases when recommendations are relevant, timely, and personalized. Additionally, trust in AI-driven suggestions enhances customer satisfaction and loyalty toward the platform. The study concludes that AI recommendation systems serve as a strategic tool in enhancing consumer engagement and increasing sales performance in digital food delivery platforms. The findings provide valuable insights for Swiggy and similar platforms to optimize their AI algorithms, improve customer trust, and strengthen long-term consumer relationships. This research contributes to the growing literature on AI-driven personalization and consumer behaviour in the digital commerce environment.