Exploring the Privacy Paradox in AI Adoption: A Data-Driven Analysis of User Engagement
Samuel Olatunde, Atef Mohamed · 2025
Artificial intelligence (AI) has revolutionized various industries by enhancing efficiency and user experiences. However, as AI systems process vast amounts of personal data, concerns about privacy, security, and potential misuse have intensified. This study examines the relationship between AI adoption and data privacy concerns, analyzing behavioral patterns from a dataset of 656 participants using Orange Data Mining for descriptive statistical analysis, comparative analysis, clustering, and correlation techniques. The research investigates how AI trust influences Chatbot and virtual assistant usage, payment preferences, and demographic trends. The findings reveal a privacy paradox, where many users who distrust AI privacy still engage with AI-powered tools, highlighting the need for greater transparency and user awareness. This paper advocates stronger AI privacy policies, ethical data practices, and regulatory frameworks to ensure that AI development remains both innovative and privacy-conscious.