Government adoption of generative artificial intelligence and ambidextrous innovation

Zhikai Zhou, Dewen Liu, Zhongjie Chen and Martin Pancho

International Review of Economics & Finance, 2025, vol. 98, issue C

Abstract: Every information technological revolution has brought about new possibilities for governmental organizational innovation, and the rapid development of Generative artificial intelligence (Gen-AI) is poised to profoundly impact government governance models and public service supply methods. Understanding the factors influencing government adoption of Gen-AI, and analyzing the impact of such adoption on governmental organizational innovation behavior, have emerged as urgent and cutting-edge topics. Based on the Technology-Organization-Environment (TOE) framework and the ambidextrous organization theory, this study systematically analyzes the three-layered driving factors that influence government organizations' adoption of Gen-AI, and examines the impact of Gen-AI on exploratory and exploitative innovation within government organizations. Furthermore, it delves into the influence mechanisms of technology adoption on different innovation behaviors from the meso-institutional and micro-implementation perspectives. At the theoretical level, this study constructs a conceptual framework for understanding the adoption of Gen-AI technology, extends the application scope of the TOE theory and enhances its explanatory power, while also providing new insights into the complexity of technology-enabled organizational innovation. At the practical level, it offers a more strategic perspective and profound implications for government organizations to maintain innovative vitality and achieve sustainable development amidst the wave of intelligent transformation.

Keywords: Generative artificial intelligence; TOE framework; Technology adoption; Organizational ambidextrous innovation (search for similar items in EconPapers)
JEL-codes: H83 M15 O33 (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:reveco:v:98:y:2025:i:c:s1059056025001169

DOI: 10.1016/j.iref.2025.103953

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