The impact of artificial intelligence on digital enterprise innovation

The digital economy is transitioning into a new phase characterized as the intelligent economy, propelled by advancements in artificial intelligence (AI). This shift is poised to inject renewed dynamism into the global economy. This paper develops a theoretical framework that elucidates the relationship between AI adoption and innovation within digital enterprises, drawing upon resource-based theory (RBT) and absorptive capacity theory (ACAP). Utilizing a sample of Chinese digital enterprises listed overseas from 2000 to 2023, this study employs Python to extract keywords associated with “artificial intelligence” from corporate annual reports, thereby constructing a proxy measure for AI adoption. We empirically investigate the impact of AI adoption on innovation within digital enterprises. Our findings demonstrate that AI adoption significantly enhances innovation in digital enterprises, a result that remains robust across a series of robustness tests. Additional analysis reveals that the absorptive capacity of enterprises mediates the relationship between AI adoption and innovation, while slack resources act as a moderating factor, attenuating the link between absorptive capacity and innovation. This paper extends our understanding of the implications of AI on broader innovation entities, elucidating the mechanisms and boundary conditions of AI application in digital enterprises. It also offers insights into how enterprises can effectively integrate AI technology, strategically configure and utilize slack resources, and ultimately enhance their innovation performance.