AI Ambient Intelligence Adaptive XR Framework: Optimizing Immersion and the Psychological Experience of Digital Media Art

Immersive extended reality environments increasingly require adaptive simulations responsive to users' affective and behavioral states. Existing systems often rely on rule-based interactions, limiting presence and flow. In this study, the author presents an artificial intelligence-driven ambient intelligence framework for context-aware extended reality that combines affective semantic–action mapping, reinforcement learning-based multisensory control, flow prediction, and adaptive narrative generation in a closed-loop architecture. A 60-participant experiment using heart rate variability, galvanic skin response, interaction logs, and experience measures showed significant improvements in presence and flow, with reduced cognitive workload and stress. Results demonstrated the promise of context-aware AI for enhancing immersive human–computer interaction.