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<p>Assessing the effects of the interaction between artificial intelligence (AI) and economic complexity on environmental sustainability is crucial for achieving sustainable development goals. The structural transformations driven by AI development and economic complexity can lead to either positive or negative outcomes for the environment. Furthermore, considering AI’s potential impact on economic complexity, these two factors together can alter environmental impacts. In this context, the study focuses on the relationship between economic complexity and ecological footprint in Asia–Pacific Economic Cooperation (APEC) countries between 2003 and 2023, as well as AI’s moderating role in this relationship. The study employs second-generation panel methods, Cup-FMOLS and Ba-OLS, which account for cross-sectional dependence, heterogeneity, and endogeneity to identify long-term relationships. Additionally, the panel quantile regression method was applied. Empirical results confirm that AI has a nonlinear effect on environmental degradation. Accordingly, AI initially increases environmental degradation but reduces it beyond a certain threshold. The positive effect of AI on environmental degradation diminishes at higher quantile levels. Furthermore, it was found that economic complexity reduces environmental degradation. The effect of economic complexity on environmental pressure decreases at higher quantiles. Furthermore, unlike AI’s direct effect, the interaction between economic complexity and AI reduces the ecological footprint. Additionally, we confirm that renewable energy consumption reduces environmental pressure, whereas human development increases environmental degradation in APEC countries. Our findings indicate that in APEC countries, AI exhibits a technological rebound effect during its development phase. Still, this effect disappears after a certain threshold value, and when it interacts with economic complexity. Given these findings, it is recommended that APEC countries integrate AI applications into sustainable production models to promote environmentally friendly technologies and knowledge-based production systems.</p>

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Exploring the influence of artificial intelligence and economic complexity on the ecological footprint in apec countries

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年6月16日

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  • Daniel Balsalobre-Lorente,
  • Tugba Nur,
  • Emre E. Topaloglu,
  • Ladislav Pilar

摘要

Assessing the effects of the interaction between artificial intelligence (AI) and economic complexity on environmental sustainability is crucial for achieving sustainable development goals. The structural transformations driven by AI development and economic complexity can lead to either positive or negative outcomes for the environment. Furthermore, considering AI’s potential impact on economic complexity, these two factors together can alter environmental impacts. In this context, the study focuses on the relationship between economic complexity and ecological footprint in Asia–Pacific Economic Cooperation (APEC) countries between 2003 and 2023, as well as AI’s moderating role in this relationship. The study employs second-generation panel methods, Cup-FMOLS and Ba-OLS, which account for cross-sectional dependence, heterogeneity, and endogeneity to identify long-term relationships. Additionally, the panel quantile regression method was applied. Empirical results confirm that AI has a nonlinear effect on environmental degradation. Accordingly, AI initially increases environmental degradation but reduces it beyond a certain threshold. The positive effect of AI on environmental degradation diminishes at higher quantile levels. Furthermore, it was found that economic complexity reduces environmental degradation. The effect of economic complexity on environmental pressure decreases at higher quantiles. Furthermore, unlike AI’s direct effect, the interaction between economic complexity and AI reduces the ecological footprint. Additionally, we confirm that renewable energy consumption reduces environmental pressure, whereas human development increases environmental degradation in APEC countries. Our findings indicate that in APEC countries, AI exhibits a technological rebound effect during its development phase. Still, this effect disappears after a certain threshold value, and when it interacts with economic complexity. Given these findings, it is recommended that APEC countries integrate AI applications into sustainable production models to promote environmentally friendly technologies and knowledge-based production systems.