AI-DRIVEN EMPATHY IN UX DESIGN: ENHANCING PERSONALIZATION AND USER EXPERIENCE THROUGH PREDICTIVE ANALYTICS

Abstract

This paper explores how AI predictive analytics can enhance UX design, creating more personalized and empathetic user experiences. Traditional UX approaches often overlook users' changing emotions, highlighting the need for adaptive, empathy-driven AI models. This study, which includes a literature review and interviews, aims to identify the current limits and abilities of AI in UX design. The research, involving UX designers, AI developers, and users, proposes a framework that places a strong emphasis on the user. This framework combines AI, multimodal data, and empathy, including behavioral, physiological, and contextual data, with the goal of improving predictive models. Key findings underscore the benefits of personalization but also raise concerns over data privacy, algorithmic bias, and the integration of multimodal data. The study provides clear recommendations for ethical AI practices and advocates for ongoing model updates to ensure AI-driven UX designs remain user-centric, transparent, and supportive. The result is interfaces that are not just intelligent, but also socially accountable.