Emotional Intelligence and Mental Well-Being in The Age of AI and Automation: Redefining The HR Role
Abstract
The rapid integration of artificial intelligence (AI) and automation into organizational systems has fundamentally transformed the nature of work, employee roles, and human resource management practices. While AI-driven technologies promise efficiency, precision, and scalability, they also introduce new psychosocial challenges for employees, including job insecurity, techno-stress, emotional disengagement, and mental health strain. In this evolving context, emotional intelligence (EI) and mental wellbeing have emerged as critical organizational capabilities rather than individual-level soft skills.This conceptual research paper examines the interrelationship between emotional intelligence, employee mental wellbeing, and AI-enabled workplaces, with a specific focus on how these dynamics necessitate a redefinition of the HR role. Drawing upon contemporary literature in organizational psychology, strategic HRM, and technology-driven work design, the paper argues that traditional HR functions are insufficient to address the emotional and psychological consequences of automation. Instead, HR must transition toward a more strategic, human-centric role that integrates EI-based leadership, wellbeing-focused policies, and ethical AI governance. The study develops a conceptual framework linking AI adoption, emotional intelligence, employee mental wellbeing, and HR interventions. It highlights the role of EI in mitigating AI-related anxiety, resistance to technological change, and workplace stress, while positioning HR as a key architect of emotionally resilient and psychologically sustainable organizations. The paper contributes to HR scholarship by offering strategic insights and practical recommendations for managing human capital effectively in AI-driven organizational environments.
Fields of Study & Subjects
AI and HR Technologies
Emotional Labor in Professions
Technostress in Professional Settings
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 5 January 2026