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

Zhiyao Sun, Shuai Che and Jie Wang

Technology in Society, 2024, vol. 79, issue C

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.

Keywords: Solow's paradox; Artificial intelligence; Firm productivity; Policy regulation; Dynamic effects (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:teinso:v:79:y:2024:i:c:s0160791x24003002

DOI: 10.1016/j.techsoc.2024.102752

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