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Deconstruct artificial intelligence's productivity impact: A new technological insight

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  • Sun, Zhiyao
  • Che, Shuai
  • Wang, Jie

Abstract

Some viewpoints suggest that IT investment seems to fail to significantly stimulate enterprise productivity in some cases. Therefore, revealing the impact of AI on firm productivity is an important topic to analyze whether Solow's paradox can be valid in the digital age. Based on panel data of 3235 listed companies in China from 2007 to 2021, we comprehensively discuss the impact and mechanism of AI on firm productivity using fixed-effects model, systematic GMM model, and mediated-effects model. Key findings include: AI significantly improves firm productivity, especially in state-controlled, internationally minded, and innovative firms. Mitigating information asymmetry is a key channel, while specialized division of labor and independent green innovation are potential ones. Supply chain digital transformation policies enhance the productivity effect of AI, and AI shows green development benefits. Additionally, the dynamic decomposition effect shows that the productivity-enhancing effect of AI is slowing down in the long run. This research provides important insights into understanding AI's role in the digital age and holds significance for firms and policymakers.

Suggested Citation

  • Sun, Zhiyao & Che, Shuai & Wang, Jie, 2024. "Deconstruct artificial intelligence's productivity impact: A new technological insight," Technology in Society, Elsevier, vol. 79(C).
    • Handle: RePEc:eee:teinso:v:79:y:2024:i:c:s0160791x24003002
    DOI: 10.1016/j.techsoc.2024.102752
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    Cited by:

    1. Yingji Liu & Ju Guo & Fangbing Shen & Yuegang Song, 2025. "Can artificial intelligence technology improve green total factor efficiency in energy utilisation? Empirical evidence from 282 cities in China," Economic Change and Restructuring, Springer, vol. 58(2), pages 1-34, April.

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