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<p>Countries face significant challenges in the extraction, management, and consumption of natural resources, which are crucial for sustainable development and the responsible use of finite natural assets. This study investigates the impact of artificial intelligence (AI) technology innovation on natural resource extraction (NRE) using panel data from 32 advanced and emerging economies between 1999 and 2020. Employing advanced econometric techniques, including the augmented mean group estimator, the study examines AI’s role in shaping resource extraction. The findings reveal that AI technology independently reduces NRE but increases it when socio-economic factors such as economic growth, industrialization, and human development are taken into account. Industrialization has a significant positive effect on NRE, whereas economic growth and human development have no significant effect. Financial development and institutional quality have opposing effects: financial development negatively affects NRE, while institutional quality has a positive and significant impact. Moderation analysis reveals that financial development weakens the AI-NRE relationship, whereas institutional quality strengthens it. Asymmetric effects are upheld for advanced and emerging countries but rejected for the overall sample. The study concludes that AI can optimize resource extraction, but its benefits depend on adequate capital investment and effective institutional frameworks. Aligning AI with robust financial systems and governance is essential for sustainable resource management and achieving long-term development goals.</p>

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Artificial intelligence technology innovation and natural resource extraction intensity: The moderating roles of financial development and institutional quality

  • 期刊论文

  • 发表日期：

    2026年6月18日

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  • Emmanuel Baffour Gyau,
  • Genanew Bekele Worku,
  • Michael Appiah

摘要

Countries face significant challenges in the extraction, management, and consumption of natural resources, which are crucial for sustainable development and the responsible use of finite natural assets. This study investigates the impact of artificial intelligence (AI) technology innovation on natural resource extraction (NRE) using panel data from 32 advanced and emerging economies between 1999 and 2020. Employing advanced econometric techniques, including the augmented mean group estimator, the study examines AI’s role in shaping resource extraction. The findings reveal that AI technology independently reduces NRE but increases it when socio-economic factors such as economic growth, industrialization, and human development are taken into account. Industrialization has a significant positive effect on NRE, whereas economic growth and human development have no significant effect. Financial development and institutional quality have opposing effects: financial development negatively affects NRE, while institutional quality has a positive and significant impact. Moderation analysis reveals that financial development weakens the AI-NRE relationship, whereas institutional quality strengthens it. Asymmetric effects are upheld for advanced and emerging countries but rejected for the overall sample. The study concludes that AI can optimize resource extraction, but its benefits depend on adequate capital investment and effective institutional frameworks. Aligning AI with robust financial systems and governance is essential for sustainable resource management and achieving long-term development goals.