Citation

Ng, Tuan Hock and Lye, Chun Teck and Lim, Ying San and Lim, Ying Zhee (2026) Economic policy uncertainty and artificial intelligence (AI) innovation: A cross-country analysis. Journal of Open Innovation: Technology, Market, and Complexity, 12 (1). p. 100698. ISSN 21998531

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Abstract

As nations vie for a strategic edge in artificial intelligence (AI), sustaining innovation has shifted from priority to imperative. Yet, economic policy uncertainty (EPU) presents a particularly salient threat, capable of derailing the investment and research and development (R&D) activities that underpin AI breakthroughs. Against this back drop, this study examines the relationship between EPU and AI innovation in 34 countries from 2017 to 2023, using quantile regression to delineate heterogeneous effects across the innovation distribution. The results indicate that EPU exerts a significantly negative effect on AI innovation, with disproportionately stronger adverse effects observed in countries at lower innovation quantiles. These results remain robust across pooled ordinary least squares (OLS), fixed and random effects models, generalised method of moments (GMM), and placebo tests. As one of the earliest empirical investigations into the asymmetric effects of EPU on AI innovation, this study contributes novel insights to the open innovation literature and ongoing policy dialogue. Collectively, the findings highlight the importance of stable and predictable policy environments in bolstering national innovation ecosystems and narrowing the global AI innovation gap.

Item Type:	Article
Uncontrolled Keywords:	Economic policy uncertainty, artificial intelligence
Subjects:	H Social Sciences > HD Industries. Land use. Labor > HD72-88 Economic growth, development, planning
Divisions:	Faculty of Business (FOB)
Depositing User:	Ms Rosnani Abd Wahab
Date Deposited:	10 Feb 2026 02:44
Last Modified:	10 Feb 2026 02:44
URII:	http://shdl.mmu.edu.my/id/eprint/15274

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