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March 10, 2026International Review of Economics & Finance2 citationsOpen Access

The Impact of the Integration of Artificial Intelligence and Data Assetization on Enterprise Total Factor Productivity: Evidence from China

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JLJiubiao LiuLHLiuhao HuHFHaiyang Fan

Key Points

  • The aim is to analyze the effects of AI-data assetization integration on total factor productivity in Chinese firms.
  • Analyzed data from Chinese A-share listed firms from 2013 to 2023.
  • Constructed a firm-level measure of AI-data assetization integration.
  • Employed a coupling coordination degree model to evaluate integration impact.
  • AI-data assetization integration significantly boosts total factor productivity.
  • Benefits are observed particularly in firms with low financing constraints and high digital transformation.
  • Mechanism analyses reveal reduced operating costs and enhanced innovation as key drivers of productivity gains.

Abstract

In the era of the digital economy, data and artificial intelligence (AI) are reshaping firms’ core competitiveness. Using Chinese A-share listed firms from 2013 to 2023 as the sample, this study constructs a firm-level measure of AI-data assetization (DA) integration based on a coupling coordination degree model and examines its impact on enterprise total factor productivity (TFP) as well as the underlying mechanisms. The research findings show that AI-DA integration significantly promotes enterprise TFP, and this conclusion still holds after various robustness tests. Mechanism tests indicate that AI-DA integration promotes TFP by reducing operating costs, strengthening firms’ innovation capability, and improving investment efficiency. Moreover, the positive effect of AI-DA integration on TFP is more pronounced among firms with low financing constraints, high degree of digital transformation, those operating in highly competitive markets, and those in non-high-tech industries. This study provides micro-level empirical evidence on enhancing enterprise TFP amid the digital economy, and offers policy implications for improving data property rights and circulation mechanisms, refining AI-related institutional arrangements, and fostering an institutional environment conducive to advancing AI-DA integration.

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Cite This Study

Liu et al. (2026) studied this question.

synapsesocial.com/papers/69af94c970916d39fea4ba98https://doi.org/10.1016/j.iref.2026.105091
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