Burnout significantly impacts individuals, organizations, and society, resulting in major financial, health, and productivity costs. Generative Artificial Intelligence (GenAI) offers new possibilities for addressing burnout through cognitive-behavioral tools that provide real-time, personalized support, potentially mitigating symptoms before escalation. Research in occupational psychology and health sciences has extensively documented burnout’s symptoms and progression, using frameworks like the Job Demands-Resources Model, Conservation of Resources Theory, Freudenberger’s Stages of Burnout, and Maslach’s Burnout Inventory. While these theories provide valuable insights, a gap remains in integrating biological and psychosocial indicators into a unified framework for effective burnout management. Traditional human resource interventions, such as surveys and broad organizational strategies, often fail to deliver the personalized, real-time support needed for meaningful prevention. GenAI offers innovative solutions for human resource management, enabling personalized interventions such as tailored development plans and real-time feedback systems. These tools create a proactive approach to burnout prevention, surpassing the limitations of conventional methods. This conceptual study addresses the gap by proposing an integrated model that synthesizes biological, psychological, and social indicators across burnout’s stages—from the Honeymoon Phase to full burnout. Drawing on established theories, the model empowers researchers and practitioners to deliver targeted interventions at critical stages, advancing organizational and individual prevention strategies. The study lays the groundwork for future research on integrating this model into a GenAI-based agent for detecting and addressing burnout, offering a novel pathway to mitigate its far-reaching consequences.
