AI and Environmental Performance in Pakistani SMEs: A Sustainable Path Forward

Despite global concerns about climate and sustainability, Pakistani small and medium-sized enterprises (SMEs) face significant challenges. These include inadequate resources, outdated technologies, and weak infrastructure, which hinder their ability to improve environmental performance (EP). AI, through automated monitoring systems and predictive analytics, offers a solution by enabling efficiencies, reducing energy consumption, and enhancing waste management.

How AI Enhances Environmental Performance

AI helps SMEs align their operations with the United Nations’ Sustainable Development Goals (SDGs) by providing real-time data and insights. These technologies enable businesses to monitor and optimize their operations, leading to reduced carbon emissions and improved environmental impact. For instance, AI can predict energy usage patterns, helping SMEs implement more efficient practices.

Addressing Common Challenges

SMEs often struggle with inefficient energy utilization and waste management, which negatively affect their environmental performance. AI systems can track and analyze these issues, providing actionable insights to improve operations. By integrating AI, SMEs can not only reduce their environmental footprint but also enhance their overall sustainability.

The Role of External Environmental Factors

External environmental factors, such as regulatory pressures and market trends, play a crucial role in enhancing the effectiveness of AI in improving EP. Regulatory authorities and strategic initiatives are essential to ensure that SMEs leverage AI for sustainability goals. Combining AI with external environmental variables ensures long-term compliance with SDGs.

Empirical Evidence and Research Methodology

A quantitative research approach was used to investigate the impact of AI on EP in Pakistani SMEs, with the mediating role of external environmental factors. Primary data was collected through structured questionnaires from 387 SME employees. The data was analyzed using Smart PLS 4.0.9 software, employing Partial Least Squares Structural Equation Modeling (PLS-SEM). This method was chosen for its ability to handle complex models with accurate findings.

Practical Implications

This study provides valuable insights for policymakers and business leaders in emerging economies. It highlights the importance of AI in improving environmental performance and the need for regulatory support to ensure its effective implementation. By adopting AI, SMEs can achieve better environmental outcomes and contribute to global sustainability goals.

Dynamic Capacity Theory

Dynamic capacity theory (DCT) emphasizes an SME’s ability to adapt to changing contexts by using resources and capabilities. AI is a dynamic capability that allows businesses to detect environmental challenges, capitalize on technological opportunities, and alter their processes for improved EP. External environmental factors serve as pivotal components that help SMEs increase AI’s role in promoting flexibility and compliance with sustainability goals.