Title: Investments, Connections, and Innovation: Evidence from Chinese Artificial Intelligence Startups

Author: Jian Xie and Kang Zhou

Abstract: Large technology firms have advantages in new technologies such as Artificial Intelligence, due in part to data and network effects. For Artificial Intelligence (AI) startups, investments by these large technology firms could be more effective at increasing innovation than investments by firms without the same data and network advantages. We use a staggered difference-in-difference approach to show that Chinese AI startups innovate more after they receive direct investments from large technology firms. These startups increase their AI technology output, as measured by both AI-related patent applications and registered software. Using a triple-difference approach, we show that the impacts of investments from large technology firms are more pronounced than those from venture capital firms and other investors. We confirm these findings using an instrumental variables approach based on previous investments by large technology firms in peer startups. Our evidence suggests that investments by data-rich technology firms shape AI innovation by startups and contribute to the rise of AI industry.

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