Neuroethical implications of AI-driven productivity tools on intellectual capital: a theoretical and econometric analysis

Purpose This study explores the dual impact of AI-driven productivity tools on employee performance, well-being and sustainability, focusing on the key metrics of productivity, innovation, stress, job satisfaction and sustainability. Design/methodology/approach The study uses econometric models and simulated data and applies difference-in-differences and regression analysis to assess the effects of AI tools on 1,000 simulated employees. Findings AI tools enhance productivity but offer limited support for innovation. They increase stress and reduce job satisfaction while improving governance outcomes and transparency. Research limitations/implications Using simulated data may limit real-world applicability. Future studies should validate findings with empirical data regarding long-term sustainability impacts. Practical implications A balanced AI strategy combining training and well-being support is vital to mitigate stress and sustain employee satisfaction during AI integration. Social implications Monitoring employee well-being and sustainability metrics is fundamental to ensure responsible AI adoption. Originality/value This research provides new insights into balancing AI’s productivity benefits with its psychological and ethical implications, offering guidelines for responsible implementation.