User Perspectives on AI-Supported Emotion Monitoring and Regulation: A Focus Group Study in Non-Clinical Contexts

Though emotional problems spread worldwide, existing emotion monitoring and regulation (EMR) tools often fail to capture the complexity of everyday experiences. Empowered by AI-driven technology, recent HCI researchers have begun to examine how these emotional technologies affect people across social contexts. However, less is known about how users conceptualize AI-supported emotion monitoring and regulation workflows in non-clinical contexts, particularly from a design-oriented, qualitative perspective. To address this gap, we conducted six focus group sessions with 30 participants from diverse backgrounds in non-clinical contexts. Our study reveals a wide range of emotional narratives, expectations, and concerns regarding AI-based emotion monitoring and regulation strategies. Our findings reframe AI not as a healer but as a helper, and offer design implications for future EMR systems. Building on these insights, we propose a design-oriented, user-informed hybrid EMR workflow that integrates AI’s strengths in routine and reactive tasks with the irreplaceable nuance of human judgment.