Artificial Intelligence Enabled Green Human Resource Management and Environmental Sustainability: An Empirical Analysis of Pakistani Organizations

Mohi  ud Din; Uzma  Javed; Atallah   Mohammed Tayser Alsharah; Manal  Abdulrazzag Almarshd; Muhammad Faizan Khan

doi:10.48161/qaj.v6n2a2249

Authors

Mohi ud Din College of Business, Beaconhouse International College, Lahore 54000, Pakistan; https://orcid.org/0000-0003-2704-7020
Uzma Javed Effat College of Business, Effat University, Jeddah 21442, Saudi Arabia; https://orcid.org/0000-0003-1271-6471
Atallah Mohammed Tayser Alsharah College of Business, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh 13318, Saudi Arabia; https://orcid.org/0000-0002-7407-2010
Manal Abdulrazzag Almarshd College of Business, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh 13318, Saudi Arabia;
Muhammad Faizan Khan Department of Management Sciences, Kohsar University Murree, Murree 47180, Punjab, Pakistan. https://orcid.org/0009-0009-3676-7311

DOI:

https://doi.org/10.48161/qaj.v6n2a2249

Keywords:

Green Human Resource Management (GHRM), Artificial Intelligence (AI), Environmental Sustainability, Sustainable Human Resource Management, Organizational Sustainability.

Abstract

The growing environmental challenges confronting organizations have increased the importance of integrating sustainable human resource practices with advanced digital technologies. This study examines the impact of Green Human Resource Management (GHRM) practices green recruitment, green training and development, green compensation and rewards, and employee empowerment on organizational environmental sustainability, while investigating the moderating role of Artificial Intelligence (AI). Data were collected from employees working in organizations across multiple sectors in Pakistan, and Structural Equation Modeling (SEM) using WarpPLS 8.0 was employed to test the proposed relationships. The findings reveal that green training and development is the strongest predictor of environmental sustainability, followed by green compensation and rewards, green recruitment, and employee empowerment. Furthermore, AI significantly strengthens the relationship between GHRM practices and sustainability outcomes by enhancing HR analytics, monitoring efficiency, predictive accuracy, and environmentally responsible decision-making. The study contributes to the emerging literature on AI-enabled sustainable HRM by providing empirical evidence on the integration of intelligent technologies with green HR practices in developing economies. The findings offer practical insights for policymakers, HR managers, and organizational leaders seeking to implement AI-driven sustainability strategies that improve environmental performance and long-term organizational sustainability.

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