AI-Driven Burnout Detection & Eco-Volunteering: A Sustainable Employee Well-Being Model

Abstract

In today’s fast-paced work environments, employee burnout has become a critical challenge, leading to diminished productivity, disengagement and mental health struggles. Traditional workplace wellness strategies often fail to proactively identify burnout, leaving employees without timely support. This paper explores the transformative role of AI in detecting early signs of burnout and introduces eco-volunteering as a sustainable intervention to restore employee well-being. The research addresses the lack of effective burnout detection mechanisms in organizations and aims to demonstrate how AI-driven tools can identify, track and mitigate workplace stress. By leveraging sentiment analysis, predictive analytics, and biometric tracking, AI can provide real-time insights into employee mental health, allowing HR teams to take proactive action. This study further examines the impact of eco-volunteering, engaging employees in environmental and community service activities, as a natural, restorative solution that enhances mental resilience and fosters a sense of purpose. Through a mixed-method approach combining case studies, employee surveys and organizational data, the study evaluates the effectiveness of AI-driven burnout detection and the therapeutic benefits of eco-volunteering. Expected findings suggest that AI can revolutionize HR decision-making by enabling early intervention, while eco-volunteering offers a meaningful, nature-based recovery model that enhances employee engagement, satisfaction and productivity. The insights from this research hold significant implications for HR strategies, advocating for a holistic, technology-enabled and sustainability-driven approach to employee well-being. By integrating AI with eco-volunteering, organizations can cultivate a healthier, more resilient workforce while reinforcing corporate social responsibility.