AI-Powered Recommendation Systems: Exploring their Impact on Customer-Business Interaction
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.
Authors
- Fatma SBIAI
Publication Details
- Published
- 2025-04-25
- DOI
- https://doi.org/10.38124/ijisrt/25apr623
- Primary Topic
- Recommender Systems and Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00