Navigating the Privacy–Personalization Paradox: Understanding User Adoption of AI-Powered Fitness Apps
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2025-07-03
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en
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This study explores how AI-driven service personalization and privacy concerns influence the adoption of AI-powered fitness applications. While users appreciate the benefits of tailored fitness recommendations, they simultaneously express concerns about the privacy of their personal data. This creates a privacy-personalization paradox, which is an important issue in the context of AI-powered fitness apps, since they use sensitive data to create personalized content. The hypothesized model is tested through a hierarchical regression analysis, using research data from 103 valid survey responses. The findings reveal that personalization positively affects the intention to adopt AI-powered fitness apps, while privacy concerns have a negative effect, both in line with previous research. Surprisingly, privacy concerns did not moderate the relationship between personalization and adoption, which suggests that privacy concerns and personalization do not interact, but operate as independent forces on adoption intention. The study contributes to AI adoption literature by highlighting the nuanced and independent roles of personalization and privacy concerns in shaping user behavior regarding AI-powered fitness apps. The study also provides directions for future research, and practical insights for app developers and fitness tech companies, and personal trainers.
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Faculteit der Managementwetenschappen