Authors : Fatma SBIAI

Volume/Issue : Volume 10 - 2025, Issue 4 - April

Google Scholar : https://tinyurl.com/yzakjjb2

Scribd : https://tinyurl.com/z48jpk2e

DOI : https://doi.org/10.38124/ijisrt/25apr623

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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.

Keywords : Ai, Recommendation Systems, Customer-Business Interaction, Privacy, Algorithmic Bias, Filter Bubbles, Cold Start.

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