Artificial intelligence, data elements, digital economy, and corporate innovation performance

In an era defined by digital transformation, artificial intelligence (AI) has emerged as a critical driver of corporate competitiveness, yet the mechanisms through which it enhances innovation remain a key area of inquiry. This study investigates this relationship by examining how AI adoption directly influences innovation performance, and how this effect is channeled through the mediating pathway of data elements and conditioned by the moderating influence of the external digital economy. Analyzing a large panel of Chinese A-share listed firms from 2008 to 2022, we find robust evidence that AI applications significantly boost corporate innovation. Our analysis reveals that this is not merely a direct technological impact; the effect is substantially mediated by a firm’s data resources, confirming that data acts as a vital strategic asset that translates AI’s potential into tangible outcomes. Furthermore, we demonstrate that the innovation returns on AI are not uniform across all environments. The positive relationship is significantly stronger for firms operating in regions with a more developed digital economy, highlighting the critical role of a supportive external ecosystem, including advanced infrastructure and digital services. The benefits are also uneven across firm types, with non-state-owned, large, and technology-intensive firms realizing the most significant gains due to their superior market incentives, resource endowments, and absorptive capacities. Collectively, these findings underscore that maximizing AI's innovative potential requires a holistic strategy. It necessitates the internal alignment of AI and data capabilities, complemented by public policies designed to cultivate a robust national digital infrastructure, thereby fostering sustainable, innovation-led corporate growth.

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Publication Details

Journal
International Review of Economics & Finance
Published
2025-08-30
DOI
https://doi.org/10.1016/j.iref.2025.104560
Citations
7
Primary Topic
Innovation Diffusion and Forecasting
Type
article
Field-Weighted Citation Impact
14.75

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article

Artificial intelligence, data elements, digital economy, and corporate innovation performance

J. F. Hu, Chengxiang Ma, Wenchao Zhang, Yanqiu Ai et al.
7 citations
International Review of Economics & Finance
Innovation Diffusion and Forecasting
14.75
article

Artificial intelligence, data elements, digital economy, and corporate innovation performance

J. F. Hu, Chengxiang Ma, Wenchao Zhang, Yanqiu Ai, Yuan Ma
article en
7 citations

Abstract

In an era defined by digital transformation, artificial intelligence (AI) has emerged as a critical driver of corporate competitiveness, yet the mechanisms through which it enhances innovation remain a key area of inquiry. This study investigates this relationship by examining how AI adoption directly influences innovation performance, and how this effect is channeled through the mediating pathway of data elements and conditioned by the moderating influence of the external digital economy. Analyzing a large panel of Chinese A-share listed firms from 2008 to 2022, we find robust evidence that AI applications significantly boost corporate innovation. Our analysis reveals that this is not merely a direct technological impact; the effect is substantially mediated by a firm’s data resources, confirming that data acts as a vital strategic asset that translates AI’s potential into tangible outcomes. Furthermore, we demonstrate that the innovation returns on AI are not uniform across all environments. The positive relationship is significantly stronger for firms operating in regions with a more developed digital economy, highlighting the critical role of a supportive external ecosystem, including advanced infrastructure and digital services. The benefits are also uneven across firm types, with non-state-owned, large, and technology-intensive firms realizing the most significant gains due to their superior market incentives, resource endowments, and absorptive capacities. Collectively, these findings underscore that maximizing AI's innovative potential requires a holistic strategy. It necessitates the internal alignment of AI and data capabilities, complemented by public policies designed to cultivate a robust national digital infrastructure, thereby fostering sustainable, innovation-led corporate growth.

International Review of Economics & FinanceVol. 103
Rutgers, The State University of New Jersey (US), Nanjing University of Finance and Economics (CN), Peking University (CN), Harbin Institute of Technology (CN), Nanyang Institute of Technology (CN)
National Social Science Fund of China, Henan Provincial Science and Technology Research Project
Industry, innovation and infrastructure
Openalex Percentile: Top 1%
Innovation Diffusion and Forecasting
14.75
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