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Artificial intelligence technology application and corporate green productivity: A study on financial transmission mechanisms

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  • Fu, Jincun
  • Liu, Yunhe
  • Jiang, Lisha

Abstract

This paper uses Chinese A-share listed companies (2010–2023) to examine the impact of AI application on enterprise green productivity. The results show that AI significantly improves green productivity, a finding robust to endogeneity and robustness tests. Mechanism analysis reveals that AI works through two channels: improving the green finance index and alleviating financing constraints. Heterogeneity tests show the effect is stronger for firms with higher intelligent investment, smarter equipment, and greater AI adoption, as well as for cities with higher robot density, higher carbon emissions, and weaker environmental regulations. This paper demonstrates that AI is an important driver of green productivity, providing theoretical and empirical support for enterprises to deploy AI and enhance green productivity.

Suggested Citation

  • Fu, Jincun & Liu, Yunhe & Jiang, Lisha, 2026. "Artificial intelligence technology application and corporate green productivity: A study on financial transmission mechanisms," Finance Research Letters, Elsevier, vol. 101(C).
    • Handle: RePEc:eee:finlet:v:101:y:2026:i:c:s1544612326004654
    DOI: 10.1016/j.frl.2026.109936
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