Artificial Intelligence Adoption, Green HRM, and Employee Behavior: Driving Environmental Sustainability in SMEs with Organizational Culture as a Moderator

Abstract

This study investigates the role of Artificial Intelligence (AI) in promoting environmental with in the manufacturing sector of small and medium enterprises (SMEs) in Pakistan. Grounded in Social Cognitive Theory (SCT), Resource-Based View (RBV), and Organizational Culture Theory (OC Theory), this research integrates AI adoption with Green Human Resource Management (GHRM) to explore how advanced technologies facilitate sustainable practices. Social Cognitive Theory (SCT) emphasizes the role of individual behavior in shaping organizational outcomes. In this study, it specifically highlights how AI-enabled tools can influence Green Employee Behavior (GEB), empowering employees to engage in eco-friendly practices that contribute to sustainability. Resource-Based View (RBV) suggests that organizations can achieve a competitive advantage by leveraging valuable, rare, and inimitable resources. This theory justifies the integration of AI adoption and sustainability-driven HR practices as strategic resources that SMEs can use to enhance their environmental performance. Organizational Culture Theory (OC Theory) underscores the importance of shared organizational values and norms in supporting the adoption of sustainability practices. It suggests that a strong pro-environmental culture enhances the acceptance and effectiveness of AI-driven GHRM practices. The study introduces GEB as a mediating factor, emphasizing the importance of employee-driven actions in translating AI-powered HR strategies into tangible environmental improvements. Additionally, Organizational Culture (OC) is assessed as a moderator, demonstrating how a pro-environmental culture strengthens the impact of AI and GHRM on sustainability outcomes. A quantitative research approach was employed, collecting data from 427 SMEs in Pakistan`s manufacturing sector. The PLS-SEM technique was used for empirical validation, confirming that AI adoption significantly enhances environmental sustainability through its influence on GHRM and GEB. Moreover, the results indicate that a strong pro-environmental culture amplifies these effects, reinforcing the role of OC as a critical moderator. This study advances theoretical discussions by integrating AI, GHRM, and sustainability within the SME context, offering a novel framework for understanding technology-driven sustainability initiatives. The findings provide actionable insights for SME leaders and policymakers, emphasizing the need for AI adoption, employee engagement, and the cultivation of sustainability-oriented organizational cultures. These insights contribute to the broader discourse on AI-driven sustainability strategies in emerging economies, providing a pathway for SMEs to achieve long-term environmental resilience.