The impact of artificial intelligence on green economy efficiency under integrated governance - Zhichun Song; Yao Deng (Scientific Reports)
Abstract This study investigates the impact of Artificial Intelligence (AI) on Green Economic Efficiency (GEE) using panel data from 30 Chinese provinces spanning from 2011 to 2020. The empirical results demonstrate that AI significantly enhances GEE, with its effects varying across regions and governance types. Specifically, AI’s impact is stronger in economically advanced and technologically intensive provinces. In terms of policy governance, excessive Market-based Environmental Regulations (MER) diminish AI’s effect on GEE, while stronger Administrative-command Environmental Regulations (CER) and Informal Environmental Regulations (IER) amplify it. Technological governance, particularly Substantive Green Technological Innovations (SUG), reduces AI’s effectiveness due to high investment thresholds, whereas Symbolic Green Technological Innovations (SYG) increase AI’s impact on GEE. In legal governance, both Administrative Intellectual Property Protection (AIP) and Judicial Intellectual Property Protection (JIP) can reduce AI’s marginal effect, with AIP showing a stronger threshold effect. These findings empirically support the theoretical models of AI-driven green development, highlighting the varying roles of governance mechanisms in promoting GEE and offering actionable insights for policymakers to optimize governance frameworks for sustainable growth.