Exploring the patterns of international technology diffusion in AI from the perspective of patent citations

This paper presents the findings from a thorough analysis of international technology diffusion (ITD) in artificial intelligence (AI) technologies. We construct a novel framework to explore the patterns of ITD in AI based on patent data published from 1970 to 2019. To this aim, we establish a nexus between technology innovation (TI) capacity and international technology diffusion (ITD) degree, and divide the countries/regions into three different groups—the leading, middle and backward. Considering the intersecting characteristic of AI technology, this paper examines the ITD patterns in the whole, single-field and intersecting-field AI technology areas. Empirical results show that: (1) Similar patterns are observed in the whole and single-field AI technology. ITD degree decreases significantly as TI capacity increases in leading countries, while it always remains high though the TI capacity improves in backward countries. Middle countries, however, show a transitional state between the two. (2) Compared to the whole AI and single-field AI technology, the pattern of ITD in intersecting-field AI technology is different. The number of nodes in the intersecting-field AI technology has decreased significantly, and the trend is more pronounced in middle and backward countries than in leading countries. These patterns imply that the technological innovation achievements of middle and backward countries will be first identified and utilized by leading countries, which will broaden the growing digital divide between countries and pose a more significant challenge to achieving technological catch-up in the future.