Enhancing User Experience through AI-Driven Personalization in User Interfaces
DOI:
https://doi.org/10.62802/m7mqmb52Keywords:
AI-driven personalization, user interfaces, user experience, adaptive design, predictive analytics, machine learning, real-time customization, privacy, algorithmic bias, user-centered designAbstract
Artificial intelligence (AI) has revolutionized user interface (UI) design by introducing personalization techniques that cater to individual user preferences, behaviors, and contexts. This research explores the integration of AI-driven personalization in user interfaces to enhance user experience (UX), focusing on adaptive design, predictive analytics, and real-time customization. By leveraging machine learning algorithms and behavioral data, AI enables interfaces to evolve dynamically, aligning with the unique needs of each user. This study investigates the role of personalization in improving engagement, satisfaction, and efficiency across various applications, such as e-commerce platforms, healthcare systems, and educational tools. Additionally, it examines the challenges of implementing personalized interfaces, including privacy concerns, data ethics, and algorithmic bias. By addressing these challenges, the research aims to develop best practices for ethical AI integration in user-centered design. The findings contribute to the growing body of knowledge on AI’s transformative potential in creating intuitive, efficient, and user-friendly interfaces, ultimately redefining the standards for digital interaction.
References
Acharya, P. S., Sahu, T., & Dixit, P. (2024). Ethical Considerations in AI-Driven User Interfaces. Journal of Informatics Education and Research, 4(1).
Costa, A., Silva, F., & Moreira, J. J. (2024). Towards an AI-Driven User Interface Design for Web Applications. Procedia Computer Science, 237, 179-186.
Khamaj, A., & Ali, A. M. (2024). Adapting user experience with reinforcement learning: Personalizing interfaces based on user behavior analysis in real-time. Alexandria Engineering Journal, 95, 164-173.
Juli, M. (2024). Revolutionizing ERP: Elevating User Experience with AI-Powered Enhancements (No. 12749). EasyChair.
Liu, Y., Xu, Y., & Song, R. (2024). Transforming User Experience (UX) through Artificial Intelligence (AI) in interactive media design.
Paneru, B., Paneru, B., Poudyal, R., & Shah, K. B. (2024). Exploring the Nexus of User Interface (UI) and User Experience (UX) in the Context of Emerging Trends and Customer Experience, Human Computer Interaction, Applications of Artificial Intelligence. International Journal of Informatics, Information System and Computer Engineering (INJIISCOM), 5(1), 102-113.
Siricharoien, W. V. (2024). Elevating User-Centered Design with AI: A Comprehensive Exploration using the AI-UCD Algorithm Framework. EAI Endorsed Transactions on Context-aware Systems and Applications, 10.
Visnudharshana, R., & Kishore, H. S. (2024). AI-Driven Language Enhancement Strategies for Libraries: Empowering Information Access and User Experience in an English Language Context. In Improving Library Systems with AI: Applications, Approaches, and Bibliometric Insights (pp. 244-253). IGI Global.
Xu, Y., Liu, Y., Xu, H., & Tan, H. (2024). AI-driven UX/UI design: Empirical research and applications in FinTech. International Journal of Innovative Research in Computer Science & Technology, 12(4), 99-109.
Zhou, S., Zheng, W., Xu, Y., & Liu, Y. (2024). Enhancing User Experience in VR Environments through AI-Driven Adaptive UI Design. Journal of Artificial Intelligence General science (JAIGS) ISSN: 3006-4023, 6(1), 59-82.