AI and Employee Well-being: A Case Study of Mental Health Chatbot Implementation in a Tech Company

Abstract

The integration of artificial intelligence (AI) into workplace well-being strategies has generated growing interest, particularly through the use of mental health chatbots as scalable and accessible interventions. This study investigates the implementation of a mental health chatbot within a Jakarta-based technology company to explore its role in supporting employee well-being. Guided by a qualitative case study design, the research draws on semi-structured interviews, focus groups, and participant observations to capture employees’ lived experiences and perceptions of the chatbot. Data were analyzed thematically, following Braun and Clarke’s reflexive approach, with attention to cultural and organizational context. The findings reveal four overarching themes: accessibility and convenience, emotional safety and stigma reduction, limitations of empathy and personalization, and organizational integration and trust. Employees appreciated the immediacy and privacy afforded by the chatbot, which lowered barriers to help-seeking and contributed to reducing stigma surrounding mental health. However, participants also noted the chatbot’s limitations in conveying empathy and expressed concerns about data privacy and potential managerial oversight. These results suggest that mental health chatbots can serve as valuable adjuncts to existing well-being programs, offering first-line support and normalizing mental health conversations in the workplace. Yet, their effectiveness is contingent upon transparent data governance, cultural adaptation, and integration with human-based care. The study contributes to theoretical debates on AI and employee well-being, while offering practical and policy implications for organizations and regulators seeking to balance technological innovation with ethical responsibility.