This research investigates the complex relationship between Artificial Intelligence (AI) and employee well-being in the manufacturing sector of Metropolitan Lima, with a focus on the growing concerns of burnout and technostress. As AI technologies are increasingly implemented in industrial environments, new questions arise: can these tools simultaneously be a cause of stress and a solution for it The study follows a critical research approach, aiming to question and evaluate the social and organizational consequences of digital transformation. Methodologically, it adopts a mixed-methods design. On one hand, the research is empirical and quantitative, based on structured surveys conducted with manufacturing workers, assessing their stress levels, perceptions of AI, and workplace experiences. On the other hand, it incorporates a qualitative component, drawing from secondary data sources such as industry case studies, academic literature, and policy documents, to contextualize and deepen the analysis. A central line of inquiry is how AI driven systems are perceived by workers: are they tools for support, or instruments of control and surveillance? The study explores how these perceptions influence technostress and burnout, considering factors such as digital workload, perceived autonomy, and job security. Simultaneously, the potential of AI to serve as a preventive tool, monitoring well-being indicators, detecting early signs of emotional exhaustion, and enabling tailored interventions is critically examined. The findings of this study are expected to offer practical value to HR professionals, organizational leaders, policymakers, and technology designers. They provide insight into how AI can be implemented in ways that support mental health, enhance job satisfaction, and create more sustainable and inclusive work environments. Moreover, the research aligns with the United Nations Sustainable Development Goals (SDGs), especially those focused on promoting decent work and well-being. By framing AI as both a challenge and an opportunity, this study invites a deeper discussion about how to humanize technological innovation in labour-intensive industries undergoing digital transformation.
Figueroa et al. (Fri,) studied this question.