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<p>This study investigates the non-linear impact of artificial intelligence (AI) on economic growth in 19 G20 countries, using data from 2005 to 2023 and employing the Generalized Method of Moments (GMM) with both linear and quadratic models. The linear model indicates that AI-related innovation has a positive and significant effect on economic growth, while the negative quadratic term confirms a concave relationship between AI and growth. Regarding the effects of AI interactions with various mechanisms on economic growth, the results show that AI’s interactions with financial innovation have a positive and significant impact, highlighting the mediating role of innovative finance in transforming AI’s technological potential into tangible economic gains. The interaction between AI and trade openness is also positive and significant, underscoring the role of international trade in technological diffusion and competitiveness. Finally, the interaction between AI and government final consumption expenditure helps strengthen economic growth by improving public infrastructure, institutional quality, and the capacity to leverage new technologies. These findings suggest that, to maximize the economic benefits of AI, regulators and policymakers should combine support for technological development with strategic investments in finance, trade, and public infrastructure. By promoting financial innovation, facilitating integration into global markets, and enhancing the quality of public spending, authorities can create an enabling environment for AI adoption, thereby transforming its potential into sustainable and inclusive economic growth.</p>

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Artificial intelligence and economic growth in G20 economies: investigating nonlinear effects through a GMM method

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年5月13日

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  • MaleK Abaab,
  • Mohamed Drira,
  • Kamel Helali

摘要

This study investigates the non-linear impact of artificial intelligence (AI) on economic growth in 19 G20 countries, using data from 2005 to 2023 and employing the Generalized Method of Moments (GMM) with both linear and quadratic models. The linear model indicates that AI-related innovation has a positive and significant effect on economic growth, while the negative quadratic term confirms a concave relationship between AI and growth. Regarding the effects of AI interactions with various mechanisms on economic growth, the results show that AI’s interactions with financial innovation have a positive and significant impact, highlighting the mediating role of innovative finance in transforming AI’s technological potential into tangible economic gains. The interaction between AI and trade openness is also positive and significant, underscoring the role of international trade in technological diffusion and competitiveness. Finally, the interaction between AI and government final consumption expenditure helps strengthen economic growth by improving public infrastructure, institutional quality, and the capacity to leverage new technologies. These findings suggest that, to maximize the economic benefits of AI, regulators and policymakers should combine support for technological development with strategic investments in finance, trade, and public infrastructure. By promoting financial innovation, facilitating integration into global markets, and enhancing the quality of public spending, authorities can create an enabling environment for AI adoption, thereby transforming its potential into sustainable and inclusive economic growth.