Enhancing Human-AI Collaboration through Emotional Intelligence: The Mediating Role of Trust and the Moderating Effect of Technological Readiness in Knowledge-Intensive Industries

Abstract

The growing integration of Artificial Intelligence (AI) in knowledge-intensive industries is transforming traditional workplace dynamics, making human-AI collaboration a critical success factor. However, while technical and operational efficiencies of AI are widely discussed, the role of human emotional intelligence (EI) in enhancing this collaboration remains underexplored. This study investigates the strategic importance of EI in fostering effective human-AI synergy and proposes that EI-driven human resource management (HRM) practices can significantly improve organizational adaptability and performance. Utilizing a mixed-method approach, data will be collected from 300 employees and 30 HR professionals across IT, healthcare, and education sectors in Pakistan. The research draws on Goleman’s Emotional Intelligence Model and Socio-Technical Systems Theory to frame the analysis. Preliminary expectations suggest a positive relationship between EI levels and the perceived success of human-AI collaboration. The findings are anticipated to guide HRM strategies in building EI competencies to optimize AI integration, thereby offering actionable insights for organizations navigating the era of workforce automation. This study explores how emotional intelligence (EI) influences human-AI collaboration in knowledge-intensive industries, introducing trust in AI systems as a mediator and technological readiness as a moderator. Drawing on Goleman’s EI model and Socio-Technical Systems Theory, the research adopts a mixed-method approach, surveying 300 employees and 30 HR professionals from the IT, healthcare, and education sectors in Pakistan. Findings are expected to show that EI enhances trust in AI, which subsequently improves collaboration. Moreover, the effect of EI on collaboration is stronger when technological readiness is high. These results offer actionable insights for HRM practices in optimizing AI integration through emotional and technological preparedness.