Green Artificial Intelligence (Green AI) holds the potential to revolutionize sustainability efforts in emerging economies—but new research shows that without committed leadership, targeted investment, and stronger institutions, adoption may remain limited to a few early adopters.
In a large-scale empirical study published in Sustainable Futures (Elsevier), researchers surveyed 399 manufacturing SMEs across Pakistan's major industrial sectors. They found that Green AI—AI designed to minimize energy use, emissions, and waste—significantly improves both operational and environmental performance, but only when critical enabling conditions are met.
"Green AI isn't a silver bullet. Our findings show it works—but only in organizations prepared to lead, invest, and evolve," said lead author Faizan ul Haq, Director at Bentham Science Publishers and researcher at Universiti Utara Malaysia.
Adoption Works—But Only Under the Right Conditions
Using Partial Least Squares Structural Equation Modeling (PLS-SEM), the study demonstrated that Green AI adoption strongly predicts gains in sustainability, including a 30% increase in energy efficiency and 25% reduction in waste among top-performing SMEs.
However, only perceived ease of use and usefulness—core tenets of the Technology Acceptance Model (TAM)—directly influenced adoption behavior. Internal organizational readiness factors like resource availability and change management capability showed limited or no effect on ease of use, signaling that even interested firms struggle to implement AI in their workflows unless systems are intuitive and visibly beneficial.
Investment and Leadership Are Game-Changers
The study revealed that Green Investment—spending on infrastructure, software, and training—amplified the impact of Green AI on sustainability performance. Yet, access to green finance in Pakistan remains low, limiting broad diffusion.
Even more decisive was Green Servant Leadership—leaders who model environmental values and empower teams. This leadership style significantly strengthened adoption by increasing how useful and usable AI tools were perceived. But such leadership remains rare in Pakistan's typically hierarchical and cost-driven SME culture.
Policy, Regulation, and Culture: The Missing Links
While market demand for greener production increased adoption, regulatory and competitive pressures showed little influence. This reflects gaps in policy enforcement, weak institutional guidance, and low consumer awareness, according to the authors.
"Regulations exist on paper, but without monitoring or incentives, they lack teeth. And many SMEs simply don't have the digital or human capital to act without support," Haq noted.
A Call for Systemic Reform
The researchers urge policymakers to:
- Introduce green financing schemes tailored for SMEs (e.g., concessional loans, tax incentives).
- Promote sustainability-focused leadership development across SME ecosystems.
- Enforce coherent, credible environmental standards, drawing on regional models like Vietnam and Malaysia.
- Launch nationwide digital and environmental literacy campaigns, especially for manufacturing-intensive regions like Lahore, Sialkot, and Faisalabad.
The authors also advocate for multi-stakeholder collaborations, including academia, industry clusters, NGOs, and donor-backed innovation hubs to drive scalable Green AI deployment.
