.png){kind=icon}
.png){kind=icon}
Return
Artificial intelligence, environmental innovation, and climate-related sustainable development: evidence from BRICS economies
.png){kind=icon}
PRE
AI
M
L
Q
A
G
Q
DOI：10.1007/s10668-026-08040-7.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
This study investigates the interaction between environmental innovation technologies (EITs) and AI-driven technologies in promoting climate-related SDGs across the BRICS countries from 2000 to 2023. The analysis employs the Cross-Sectional Autoregressive Distributed Lag (CS-ARDL), the Cross-Sectional Distributed Lag (CS-DL), and the System Generalized Method of Moments (SYS-GMM) model. The results indicate that: (i) climate-related sustainable development index (SDI) have worsened on average across these countries (a directional decline) of 0.16 standard deviation in recent years; (ii) EITs on their own show limited and weakly significant associations with the SDI, indicating that green patents alone do not guarantee improved SDI performance; and (iii) AI-driven technology helps scale and improve the effectiveness of EITs in achieving SDI by 0.03 and 0.05 standard deviations over the short- and long-terms, respectively. The findings highlight the importance of AI-driven technology as a system-level enabler of sustainability transitions in emerging economies. Following the findings, the study offers policy recommendations that support aligning innovation incentives, data infrastructure, and capacity building to convert green inventions into measurable climate gains.
Keywords:
Artificial intelligence
Environmental innovation
Sustainability transition theory
CS-ARDL
Climate-related SDGs
BRICS
Journal
IF:
4.2
Papers:
945
Citations:
2.3W
Organization
Cited Papers