Artificial Intelligence, Green Technology Innovation, and Green Total Factor Productivity: Evidence and Pathways Toward Sustainable Economic Growth

Abstract

Amid the global pursuit of sustainable economic growth under Sustainable Development Goal (SDG) 8, nations face the pressing challenge of improving productivity while minimizing environmental harm. Although artificial intelligence (AI) and green technology innovation (GTI) are widely recognized as potential drivers of sustainability, most existing studies focus on single‐country contexts or specific industries and often rely on conventional productivity measures that overlook environmental factors. This leaves a critical gap in understanding their combined effects on green total factor productivity (GTFP) at a broader level. This study addresses these gaps by investigating how AI influences GTFP and how GTI strengthens this relationship, while also examining the role of energy efficiency as a channel through which AI affects sustainable productivity. To achieve this, the study uses data from 28 countries spanning 2000–2019 and applies a dynamic Generalized Method of Moments (GMM) estimator with instrumental variables to address endogeneity and ensure robust results. The findings show that AI significantly enhances GTFP, with an inverted U‐shaped pattern where initial gains are strong but excessive use without supportive strategies leads to diminishing returns and sustainability challenges. GTI amplifies this effect, and improvements in energy efficiency further support these gains by optimizing resource use and reducing emissions. These insights guide policymakers to implement supportive regulations, promote green innovation incentives, and invest in infrastructure and human capital to integrate AI and GTI into sustainability strategies, thereby advancing SDG 8 and fostering long‐term ecological resilience.