The relationship between artificial intelligence, geopolitical risk, and green growth: Exploring the moderating role of green finance and energy technology

IF 12.9 1区管理学 Q1 BUSINESS

Technological Forecasting and Social Change Pub Date : 2025-04-28 DOI:10.1016/j.techfore.2025.124135

Xiyue Yang , Hui Chen , Baoxi Li , Danning Jia , Mahmood Ahmad

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Abstract

Artificial intelligence (AI), viewed as a driver of progress in modern societies, is accompanied by uncertainties regarding its impact on green growth within the intricate background of geopolitical risk (GR). This study examines the relationship between AI, geopolitical risk and green growth, further exploring the moderating roles of green finance and energy technology on geopolitical risks affecting green growth. Using panel data from 20 OECD countries spanning from 1993 to 2021 and advanced econometric techniques, we find that the impact of AI on green growth exhibits a “U”-shaped trajectory, initially inhibiting but ultimately fostering growth. Additionally, GR exerts a negative influence on green growth, however, this adverse effect can be mitigated by green finance and energy technology, which drive green development. We also applied a suite of methodologies, including Two Stage Least Squares (2SLS), Fully Modified Ordinary Least Squares (FMOLS), quantile regression, and Artificial Neural Networks (ANN), to assess the robustness of the results. The findings of this study underscore the critical importance of incorporating artificial intelligence into the green growth agenda of OECD nations. Moreover, OECD countries should proactively address geopolitical risks by expanding green finance initiatives and intensifying investments in energy technology to strengthen their green growth frameworks.

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人工智能、地缘政治风险与绿色增长的关系：探讨绿色金融和能源技术的调节作用

人工智能（AI）被视为现代社会进步的驱动力，但在地缘政治风险（GR）的复杂背景下，其对绿色增长的影响也存在不确定性。本研究考察了人工智能、地缘政治风险和绿色增长之间的关系，进一步探讨了绿色金融和能源技术对影响绿色增长的地缘政治风险的调节作用。利用1993年至2021年20个经合组织国家的面板数据和先进的计量经济学技术，我们发现人工智能对绿色增长的影响呈“U”型轨迹，最初抑制增长，但最终促进增长。此外，GR会对绿色增长产生负面影响，但这种负面影响可以通过推动绿色发展的绿色金融和能源技术来缓解。我们还应用了一套方法，包括两阶段最小二乘法（2SLS）、完全修正普通最小二乘法（FMOLS）、分位数回归和人工神经网络（ANN），来评估结果的稳健性。这项研究的结果强调了将人工智能纳入经合组织国家绿色增长议程的重要性。此外，经合组织成员国应积极应对地缘政治风险，扩大绿色金融倡议，加大能源技术投资，强化绿色增长框架。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Technological Forecasting and Social Change Multiple-

CiteScore

21.30

自引率

10.80%

发文量

813

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