Advances in AI-Augmented User Experience Design for Personalized Public and Enterprise Digital Services

The integration of Artificial Intelligence (AI) into user experience (UX) design is fundamentally transforming the way digital services are delivered across public and enterprise platforms. As digital interactions become increasingly complex and data-driven, AI-augmented UX design offers the potential to create highly personalized, intuitive, and adaptive digital environments that cater to diverse user needs. This paper explores the latest advances in AI-augmented UX design, focusing on how emerging AI techniques such as machine learning, natural language processing, computer vision, and behavioral analytics are being deployed to enhance personalization, usability, accessibility, and service delivery efficiency in both public and enterprise contexts. We examine how public sector institutions are leveraging AI-driven UX to improve citizen engagement, streamline service delivery, and foster digital inclusion through personalized portals, chatbots, and predictive interfaces. In parallel, enterprises are adopting intelligent UX systems to tailor customer journeys, increase operational efficiency, and gain competitive advantage through real-time adaptation to user behavior and preferences. The study highlights the integration of AI with UX methodologies such as design thinking and user-centered design to create responsive interfaces that evolve continuously with user feedback and contextual data. Key challenges such as data privacy, algorithmic bias, ethical AI use, and user trust are critically analyzed, with emphasis on strategies to ensure transparency, fairness, and inclusivity in AI-driven UX solutions. Additionally, the paper identifies emerging trends including AI-driven accessibility for persons with disabilities, emotion-aware interfaces, and zero UI (voice- or gesture-based interaction) as frontiers for future development. Our findings emphasize that AI-augmented UX design is not only a technological evolution but also a strategic enabler of personalized digital transformation. It requires interdisciplinary collaboration among designers, engineers, policymakers, and stakeholders to harness its full potential responsibly. The paper concludes by offering actionable frameworks and policy recommendations for integrating AI into UX design to deliver more inclusive, personalized, and efficient digital services.