AI and IoT integration in Green HRM: A Framework for Eco-Friendly Talent Management and Optimization - Khan, Rehan Ali; Abbas, Ali; Saba, Noor; Syed, Muhammad Irfan; Ansari, Adeel (Inverge Journal of Social Sciences, 2026)
This study examined the integration of Artificial Intelligence (AI) and the Internet of Things (IoT) within Green Human Resource Management (GHRM) to develop a comprehensive framework for eco-friendly talent management and organizational optimization. The research adopted a qualitative and conceptual approach, systematically synthesizing recent literature to explore how AI-driven analytics and IoT-enabled systems enhance sustainable HR practices. Thematic analysis was employed to identify key dimensions, including green recruitment, digital training, performance management, employee engagement, and environmental monitoring. The findings indicated that AI significantly improves HR efficiency through automation, predictive analytics, and data-driven decision-making, enabling paperless recruitment, personalized e-learning, and objective performance evaluation. Concurrently, IoT facilitates real-time monitoring of workplace environments, energy consumption, and resource utilization, enhancing transparency and accountability. The integration of these technologies, termed AIoT, creates a synergistic effect that significantly enhances green recruitment, intelligent training, sustainable performance management, and employee engagement. This synergy enables organizations to optimize resource allocation, promote pro-environmental behaviour among employees, and achieve long-term environmental and operational goals. However, the study identified critical barriers to effective adoption, including technological complexity, data privacy concerns, high implementation costs, skill gaps, and organizational resistance. The study proposed a structured conceptual framework integrating AI and IoT into GHRM practices, offering practical insights for organizations and policymakers. 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