SBIAI, Fatma (2025) AI-Powered Recommendation Systems: Exploring their Impact on Customer-Business Interaction. International Journal of Innovative Science and Research Technology, 10 (4): 25apr623. pp. 1332-1339. ISSN 2456-2165
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Abstract
AI-powered recommendation systems have revolutionized customer-business interactions by leveraging machine learning to deliver personalized experiences. This study investigates their multifaceted impact across sectors like e- commerce, streaming services, and social media. Through a mixed-methods approach—including a literature review, case studies (Netflix, Amazon), and a 15-participant survey—the research highlights how these systems enhance engagement, satisfaction, and revenue. Ethical challenges such as privacy concerns, algorithmic bias, and filter bubbles are critically analyzed. Findings reveal that while AI recommendations drive loyalty and discovery, addressing transparency and user control remains vital for sustainable adoption. The study concludes with actionable insights for businesses and policymakers to balance innovation with ethical responsibility.
Item Type: | Article |
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Subjects: | T Technology > T Technology (General) |
Divisions: | Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science |
Depositing User: | Editor IJISRT Publication |
Date Deposited: | 29 Apr 2025 08:50 |
Last Modified: | 29 Apr 2025 08:50 |
URI: | https://eprint.ijisrt.org/id/eprint/603 |