USER EXPERIENCE (UX) IN INTELLIGENT SYSTEMS: A SYSTEMATIC REVIEW OF HUMAN CENTERED AI DESIGN FOCUS ON UI/UX + AI + HCI

Abstract

Artificial intelligence (AI) is increasingly embedded in digital products and services, making user experience (UX), user interface (UI), and human-computer interaction (HCI) central to how people understand, trust, and use intelligent systems. This systematic review examines how human-centered AI design approaches can improve interaction with AI-enabled systems, with particular attention to explainability, trust, transparency, control, accessibility, and UX evaluation. The review synthesizes peer-reviewed and scholarly literature addressing UX, HCI, human-AI interaction, explainable AI, interface design, accessibility, and intelligent systems. The literature was organized thematically around human-centered design, interaction and interface principles, explainability and trust, evaluation methods, and unresolved challenges. Findings indicate that effective AI UX requires more than conventional usability: users need understandable system behaviour, appropriate explanations, practical opportunities to correct or override outputs, and interaction designs that support calibrated trust. The review also identifies fragmented evaluation practices, uneven accessibility considerations, and difficulties in translating technical explanations into useful interface experiences as continuing research gaps. Overall, the evidence supports designing AI systems around human goals, capabilities, responsibilities, and contexts. Future research should strengthen longitudinal evaluation, standardize reporting and core UX measures, and develop inclusive, actionable, and human-centered AI interfaces.