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How does generative artificial intelligence promote firms’ key core technological innovation?

Author

Listed:
  • Liu, Jun
  • Chen, Junwei
  • Zhao, Ying
  • Forrest, Jeffrey Yi-Lin
  • Song, Melody C.

Abstract

Accurately evaluating the impact of generative artificial intelligence (GAI) on firms' key core technological innovation is essential. Using enterprise-level data from China covering the period 2010 to 2022, this study applies a double/debiased machine learning (DML) framework together with mediation effect models to examine the effect of GAI on firms' key core technological innovation and its underlying mechanisms. The results show that GAI significantly promotes firms’ key core technological innovation. Mechanism analysis reveals that this effect is primarily achieved by enhancing knowledge diversity and optimizing the labor skill structure. Heterogeneity analysis further indicates that GAI has a pronounced enabling effect on key core technological innovation in state-owned enterprises (SOEs), non–high-tech enterprises, and non-Specialized, Refined, Unique, and Innovative (SRUI) “Little Giant” firms, whereas no significant effect is observed for non-SOEs, high-tech enterprises, or SRUI “Little Giant” firms. These findings provide robust empirical evidence to guide firms with different characteristics in leveraging GAI to advance key core technological innovation and offer valuable insights for emerging economies seeking technological catch-up through intelligent transformation.

Suggested Citation

  • Liu, Jun & Chen, Junwei & Zhao, Ying & Forrest, Jeffrey Yi-Lin & Song, Melody C., 2026. "How does generative artificial intelligence promote firms’ key core technological innovation?," Socio-Economic Planning Sciences, Elsevier, vol. 105(C).
    • Handle: RePEc:eee:soceps:v:105:y:2026:i:c:s003801212600039x
    DOI: 10.1016/j.seps.2026.102453
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