Artificial intelligence (AI) is increasingly used by e-commerce platforms to recommend products based on browsing behaviour, purchase history, product preferences and other signals. These recommendations may help consumers discover relevant products and make shopping more convenient. However, consumer trust can be affected by recommendation accuracy, transparency, the quality of product information, customer reviews and concerns about personal data. This study examines consumer trust in AI-recommended products on e-commerce platforms with particular reference to Flipkart. It considers awareness of recommendations, perceived relevance, trust, factors influencing purchase intention, privacy concerns and preferred improvements. A descriptive research framework and structured questionnaire are used. For demonstrating the required analysis format, the tables in this draft contain an illustrative dataset of 55 responses. These figures are simulated for project preparation and must be replaced with actual questionnaire results before the project is submitted as empirical research. The illustrative pattern suggests that consumers are more likely to engage with recommendations when they appear relevant and are supported by reliable product details and reviews. Clear explanations and accessible privacy controls are proposed as ways to strengthen trust.

Mrs. Srilaya Babu, James Christopherm, "A Study on Consumer Trust In AI-Recommended Products Towards E-Commerce Platforms With Reference to Flipkart" International Journal of Scientific Research and Engineering Development, V9(5): Page(2248-2255) September - October 2026. ISSN: 2581-7175. www.ijsred.com. Published by Scientific and Academic Research Publishing.